Bridging the Imaginary Research and Practice Gap by Responsive Learning

EAPRIL and UAS-journal

This special issue is initiated by EAPRIL (The European Association for Practitioner Research on Improving Learning). EAPRIL is a platform for practitioner and practice-based research. This year it will hold its 11th annual conference for practitioner research on improving learning in education and professional practice . EAPRIL was initiated 11 years ago by the well-known ‘European Association for Research on Learning and Instruction’ (EARLI). EARLI wanted to support practitioner research through establishing  a platform where practitioners and researchers conducting practice-based research can meet and exchange research results  in a highly interactive way.  Nowadays, EAPRIL and EARLI collaborate as independent research associations.

EAPRIL research conference presentations are reflected in the articles in this special international issue of the UAS journal and address practice-based research as a form of inquiry that can be used and implemented to support life long workplace learning for a variety of professionals and occupations (EAPRIL conference proceedings, 2014, 2015 ).

The broad interpretations of ‘practitioner research’, and practice-based research require a clear epistemological basis demonstrating the relationship between research and practice. According to Heikkinen, de Jong and Vanderlinde  (2016) such clarification goes back to Aristotelian  philosophy which explored the ways that knowledge is obtained, what purpose it serves, and how practitioner research differs from academic research. This yields  theoretical knowledge as well as  two kinds of practical knowledge. Although all three are relevant, the so called ‘practitioner knowledge’ (the phronesis and the techne), need more attention in judging the merit of practitioner research. Heikkinen, et al. (2016) stated that good practitioner research needs its own methodological principles. De Jong, Beus, Richardson and Ruijters (2013) emphasized that practitioner research is more than just the old way of doing research in its search for the truth. It also has to do with enhancing co-creation and wisdom of practitioners and their praxis. It might even have a total different epistemic underpinning.

After EAPRIL’s first special issue ‘Studies in Vocational and Professional Education’ (April 2016, Journal Vocations and Learning) EAPRIL and UAS journal were talking about a collaboration for the next special issue. This resulted in the current issue with eleven wonderful insights, from five different European countries.. Some contributions even cover many other European countries. You will find articles about activities in UAS by UAS teacher-researchers, inquiry-innovators writing about educational innovations which reflect their passion to improve the education offered in UAS; to support the development of their students; and to offer them learning experiences in enhancing the collaboration and interaction between education and practice. The focus is on improving the activity system of practice, as well as students’ development and research by trying to make UAS education more responsive to students, responsive to practice and responsive to society.

From the Finnish viewpoint this UAS Journal (est. 2011) special issue in collaboration with EAPRIL organization is important in many ways. Firstly, it includes interesting articles and shows that the problems and challenges in European higher education are rather similar. This issue, as itself, is bridging researchers and practitioners from different European countries.

Secondly, this issue is a reflection on the history of the UAS Journal. The roots of UAS eJournal are in KeVer network (2000-2009) and KeVer eJournal which was published as one part of networking activities. The purpose of Kever was to develop and strengthen pedagogical, methodological and RDI actions in UAS education, which began in Finland in 1991. The method of working in KeVer was to combine research and practice, researchers and practitioners. The backgrounds of the network members were  researchers working in the universities and research institutions and teachers, as well as researchers and developers working in universities of applied sciences. When KeVer network activities finished,  the ejournal transformed from a research-based journal  to a magazine format. So,this special issue  after some years, makes visible the research linked to UASs.

Finally, this issue is hopefully a beginning for a fruitful collaboration among Europeans who share an interest in combining research and practice as a method of developing teaching and learning. Complexity and uncertainty in the world demands strong networks and communities, feelings of shared interests and goals. EAPRIL and UAS-journal wants to support such networks as being places to exchange and build insights together in  the development of praxis.


Reading the articles in this issue, you will notice that the responsivity to students and practice is seen as a crucial element of the UAS education as a means for students’ development into competent professionals for their future working life and contribution to society. In some more conceptual oriented articles, for instance, from Meijer and Kuijpers (in this issue) this education-practice relationship is seen as a gap that has to be bridged. According to others like Van den Berg (in this issue) it is more a matter of crossing borders, which requires certain abilities. Kukokonen (in this issue) integrates this dilemma in five key elements of good student experiences, such as authenticity and collaboration.

The articles show that in general the core issue in being responsive to students’ learning on the one hand and professional practice on the other hand, seems to enhance interaction, collaborative learning, co-creation of knowledge in the efforts to support and improve the relationship between research, education and working life (practice) as a responsive educational activity system. An activity system in which students develop abilities, skills and knowledge that anticipate the (future) needs of working practice, society and personal life. Such activity systems and the diverse educational examples illustrated in this issue, should be considered regarding  the different perspectives and emphasis of the learning processes described: for example cooperative, collaborative and knowledge creation and  derivative pedogagical methods. This means that emphasis on transfer of knowledge is based on a totally different epistemic basis from the co-creation of knowledge. In addition, cooperation does not always mean that students are engaged in a mutual learning process, or that collaborative learning might be a collective group learning but that it differs from collective knowledge creation in order to contribute to the idea development of the community.

Moreover, it is sometimes important to reflect on generally accepted theories of learning from a different perspective. For example De Jong (2015) approaches learning not as matter of knowledge transfer or acquisition, but as a semiotic, meaning-constructing process to combine incoming information with already held personal and community cognitive concepts and ideas. Even the stimulus-response learning is a process of giving meaning to a stimulus in relation to an action.

Table 1: Different manifestations of learning as a semiotic, meaning building process and the impact on change, the thinking that is learned and relatedness to practice (world 1), school knowledge (world 2) and knowledge creating Popper’s world 3.

Table 1: Different manifestations of learning as a semiotic, meaning building process and the impact on change, the thinking that is learned and relatedness to practice (world 1), school knowledge (world 2) and knowledge creating Popper’s world 3.
Table 1: Different manifestations of learning as a semiotic, meaning building process and the impact on change, the thinking that is learned and relatedness to practice (world 1), school knowledge (world 2) and knowledge creating Popper’s world 3.

A process in which ‘the other’ might be at a very distant or might be very close to the interaction of the process of meaning construction. This semiotic process manifests itself in learning in three ways:

  • Zero learning and Learning 1) e.g. natural biological learning in daily practice;
    You can think of habituation, sentization, stimulus-response learning
  • Learning 2) cognitive learning in schools, courses, trainings; and
    You can think of Piagetian cognitive constructivism; accumulative and  accommodative learning.
  • Learning 3) social interactive learning in groups, teams, communities.
    You can think of cooperative, collaborative learning and knowledge building/creation.

These levels differ in what leads to change; what kind of thinking is learned and if the impact goes beyond current practice and habits, current knowledge and thinking or becoming familiar with and enculturate in the world of building knowledge and understanding (see table 1). In relation to the articles in this issue the level of social interactive learning is seems to be very relevant because it is mentioned almost in all of them. To provide you as reader a lens to reflect on the articles in this special issue we will elaborate more in depth about this level and its consequences in the next paragraphs[1].

Social interaction and Cooperative learning

Let’s take a look at cooperative learning settings such as: Learning Together & Alone; Teams-Games-Tournaments (TGT); Group Investigation; Constructive Controversy; Jigsaw Procedure; Student Teams Achievement Divisions (STAD); Complex Instruction; Team Accelerated Instruction (TAI); Cooperative Learning Structures; Cooperative Integrated Reading & Composition (CIRC) (Johnson, Johnson, & Stanne, 2000; Loeser, 2008).

Cooperative learning involves students working together to accomplish shared learning goals. (Johnson et al., 2000; Johnson & Johnson, 1999). Each student can achieve his or her learning goal if – and only if – the other group members achieve theirs (Deutsch 1962, as cited in Johnson et. al., 2000). Review studies show, that cooperative learning significantly increases students’ achievement in comparison with competitive, individual learning situations. It does not mean that all operationalizations are effective in the same way (Johnson & Johnson, 2009; Slavin, 1980). From the above mentioned studies ‘Learning together’ seems to be the most effective (David W Johnson et al., 2000). The five most basic pillars of cooperative learning are: individual accountability, positive interdependence, face-to-face promotive interaction, group processing, and interpersonal and small group skills. Students feel that they cannot work without the participation of one or more group members. The central principle of cooperative learning is that students learn through interaction and dialogue with others, mostly in small groups, around a topic of study to achieve a common goal according to David Johnson and Robert Slavin[2] .

Another view

‘Learning with others’ enables social interaction as a kind of ”cognitive apprenticeship to learn the school learning material and enhance the individual learning” (Hartmann, Angersbach, & Rummel, 2015). Social interdependence enables  individual motivation and cognitive learning (Slavin, 1980, 1996). What we see is that information, complex codes, models and scientific theory are interpreted and reconstructed by labour division in a group (Dillenbourg, 1999). It is the cumulative collection of interpretations of a group, not yet the group cognition (Stahl, 2006) of collective knowing. Or as Hartmann et al., (2015) interprets this, as an endogenous form of constructivism: the source of knowledge construction is the individual processes. No new artefacts are created collectively. You can regard it as a kind of individual cognitive learning. Cognitive learning on a group level where the social interaction scaffolds the individual interpretation of information. So reading a book with others gives you access to interpretations of information by others that helps you to reconstruct the knowledge represented in school textbook. This is because you see things you did not notice or others together contribute more foreknowledge than your own. Communication then becomes learning. It focuses on what is known already and the subjective learning in the mind of (Popper’s world 2 (refered by Bereiter, 2002) school books and standard tests. It is effective in an improved study achievement (David W Johnson et al., 2000).

What epistemologically develops is an awareness that people think differently and interpret differently and you can learn from each other. Social interactive process skills are learnt together with dialogue to understand content.

Collaborative learning

The difference between cooperative and collaborative learning is roughly described by Dillenbourg: “(…)in cooperation, partners split work, solve subtasks individually and then assemble the partial results in the final output. In collaboration, partners do the work “together” (Dillenbourg, 1999, p. 8). This doing together is according to Dillenbourg a process by which individuals negotiate and share meanings. The difference lies in the fact that, in collaborative learning, the knowledge construction is not an assembly of individual understandings, such as in cooperative learning, but collaborative, group interactions such as negotiations and sharing of meanings (Stahl, Koschmann, & Suthers, 2006, 2014).

According to Beers, Boshuizen, Kirschner, & Gijselaers, (2005; 2008) collaborative learning can be characterized as social interaction focusing on the development of a common ground and shared knowledge. The two are formed through negotiation and knowledge exchange. This may be in a dialectic conversation of agreeing and disagreeing with messages, making your position known to group members, posting rejections to messages that are unintelligible or objectively incorrect in the eyes of someone else. A process from unshared knowledge externalisation to knowledge construction integration takes place (Beers et al., 2005, see fig. 1). Despite this formalism of the process, their studies show different effects concerning, for instance, reaching a common ground (Beers et al., 2005).

However, the main point is that groups are seen as a major source of knowledge construction with a social and interactive dimension (Miyake & Kirschner, 2014). This social dimension involves aspects such as interdependence, social and task cohesion, group potency and psychological safety. Often these social aspects are underestimated in (Computer Supported) Collaborative learning (CSCL) in contrast to co-construction and constructive conflict in the sharing and meaning making group process (Kreijns & Kirschner, 2003). In this social process learning ability in the sense of (co-)regulating content and community processes is vital for people to become used to share knowledge, deepening their own and common understanding and creating further insights (De Laat, De Jong, & Ter Huurne, 2000).

Figure 1: Collaborative learning has divers phases starting form unshared knowledge to constructed knowledge (Beers et al., 2005).

Stahl (2006, 2010) emphasises much more  group cognition and collaborative knowledge building as the character of collaborative learning. One could call this kind of knowledge building  ‘co-creation’ of knowledge. Stahl describes that this happens in an ecology where teachers act as facilitators and less as instructors or in the case of CS computer environment act to “supports the interactions among the students themselves” (Stahl, 2006, p. 3). According to Stahl, collaborative knowledge building is effective when the group is engaged in high level cognitions of “thinking together about a problem or task and produce knowledge artefacts like verbal problem clarification, a textual solution proposal, or a more developed theoretical inscription that integrates their different perspectives on the topic and represents a shared group result that they have negotiated” (Stahl, 2006, p 3).

Another view

The eco-semiotic process in collaborative learning can be seen as a dialectical negotiating in small groups (Hartmann et al., 2015) about the difference in signs, information, consisting of the different individual opinions, perspectives formed from individual eco-semiotic process based on their own experience (world 1) and information of schoolbooks (world 2), perhaps also scientific information (world 3) and the perspectives of others in the collaborative group. The sharing of the perspectives and the negotiation, debate, discussion is the process of finding common ground for the co-construction of a group knowledge perspective.

 The interactions with others reveals the difference in individual perspectives, which form a source of knowledge. Hartmann et al., (2015) indicate this in the context of collaborative learning as a dialectical process. So a social interaction where the difference is synthesized in a process of thesis and anti-thesis becomes a group cognition. Others are important in (CS)CL in getting to know the difference between the various interpretations of individuals as a source to understand by negotiating them in group dialogue, debate, discussion and arriving at a consensus or perspectives of what a phenomenon, theory is about or what a creative solution is for a problem or question in the context of a learning or work task.

In the social interaction the personal practical experience (world 1) and the ideas of the personal subjective mind (world 2) become part of the collective conversation and knowledge construction process. This thinking the past may reveal different modes of thinking, old ways of looking at particular phenomena. In the first place this is in the ecology of ideas of the subjective mind (world 2). Students develop an epistemic awareness of the common ground and subjectivity, the man-made character of knowledge artefacts.

From a transition viewpoint, where multidisciplinary approaches are desirable, collaborative learning has, for example,  high potential because of the negotiability of knowledge and the interdependent process of finding a common ground and cohesion in something such as group cognition (whatever this epistemological means). Learning becomes knowledge construction and is no longer a solitary individual process, but also a group process.

Knowledge creation/building

Knowledge building (Bereiter, 2002; Bereiter & Scardamalia, 2006a)(Bereiter, 2002; Bereiter & Scardamalia, 2006a) or knowledge creation (Nonaka, 2006; Nonaka & Toyama, 2003; Nonaka, 1994) concerns the same processes, although knowledge building is more education related and encompasses a greater range of concerns (Scardamalia & Bereiter, 2014). Both certainly consist of the social and group dynamic processes as is the case in collaborative learning. However, the latter does not always include the systematic, methodological, empathic and hermeneutic process of knowledge creation (see also Kukkonen this issue). In knowledge building the social interactions are also an enculturation in world 3 of scientific knowledge, the world of conceptual artefacts.

Despite the formulated collaborative learning formalizations such as scripts (Dillenbourg & Hong, 2008), roles (Strijbos, 2004) or orchestrating graphs and workflows (Dillenbourg, 2015), they don’t support such an enculturation, but they do support the group process in CL. Tools in knowledge building environments support the development of ideas, theories, conceptual thinking and artefacts and enculturation in World 3. It refers to a set of social practices that advance the state of knowledge within a community over time (Paavola et al. 2004). The knowledge building principles are guidelines for idea improvement; they are not scripts, not linear steps to follow. The knowledge building principles “serve multiple purposes like pedagogical guides, technology design specifications, and evaluating ’existing’ practices” (Scardamalia & Bereiter, 2010, p. 9).

An example of this collaborative learning and knowledge building is described by Willemse, Boei and Pillen (2016) reporting on communities in which secondary teacher educators  with a variety of educational background (eg. History, fysics, geography) collaboratively conducted research into  shared problems identified from practice, thus supporting the process of collaborative learning and improving practice. This process contributed to shared languages, knowledge creation and improved practices.

According to Van Aalst, (2009, p. 260) knowledge creation involves more than the creation of a new idea; it requires discourse (talk, writing, and other actions) to determine the limits of knowledge in the community, set goals, investigate problems, promote the impact of new ideas, and evaluate whether the state of knowledge in the community is advancing. Van Aalst distinguishes three modes of discourse—knowledge sharing, knowledge construction, and knowledge creation.

Knowledge sharing refers to the transmission of information between people. According to Van Aalst, knowledge construction refers to the processes by which students solve problems and construct understanding of concepts, phenomena, and situations by making ideas meaningful in relating to prior knowledge and the problem situation mediated by social interactions within a group and technologies. Knowledge construction, with its emphasis on building on students’ prior ideas, concepts and explanations, and their metacognition, produces deeper knowledge in complex domains than does knowledge sharing (Bransford et al. 1999; Hmelo-Silver et al. 2007). Van Aalst connects knowledge creation to expertise of the situations, and the requirement of environments (companies, organizations, academic disciplines) where ideas are needed to sustain innovation in order to survive as an organization, being an organic system in a big relational world.

The big difference with cooperative and collaborative learning is that knowledge building takes you directly into the process of knowledge creation as the basis of education. It is “acquiring competence in knowledge creation by actually doing it” (Scardamalia & Bereiter, 2014, p. 399). It is enculturating students in their role as collaborative knowledge creators in the sense of improving ideas. Knowledge building is much more an idea improvement centred process by means of collaboration in advancement of a community.

According to Scardamlia and Bereiter (2014; Bereiter, 2002) knowledge building derives from a Popperian epistemology e.g. Popper’s ”three world” ontology. Here world 3 consists of an objective knowledge world created by the human mind. It is knowledge in the form of conceptual artefacts which can be acted on as an object. So you can work with knowledge because you can grasp it, build on it, modify it and develop it further. This is different from co-constructing knowledge as in Collaborative learning.

In relation to education, Scardamalia and Bereiter (2014) put forward 5 of the 12 principles as vital themes. 1) Community knowledge advancement. Knowledge is not a proposition of a person, but of a culture and community and it contributes to the wisdom of the community and its members. 2) Idea improvement. There is not such a thing as a final truth, perfect theory, technology or living together. It can always be improved. All ideas can be improved and in this sense all ideas are valuable. 3) knowledge building discourse as a creative role instead of a critical role and a collaborative process. 4) constructive use of authoritative information. This means all kinds of information, first-hand experience, secondary sources, etc, that has value in the knowledge building process in a constructive transliteracy practicing. 5) Understanding as collaborative explanation building: producing principled practical knowledge by connecting concrete experiences to more generalizable knowledge. Knowledge building is innovation, based on ‘principle practical knowledge’ and theoretical concepts in a coherent explanation for practical use (know-how combined with know-why).

The process of knowledge building and co-creating as responsive learning

The Popperian ontological world 3 underlies the semiotic process in knowledge building. This world makes understanding knowledge possible because we can grasp the knowledge in its form as a conceptual artefact. A concept that can be dealt with as an object, that you can work with, build on, modify and improve.

Indeed, the conceptual artefact as such form an independent entity, but not the codes, signs, language of the mind’s thinking embedded in it. That is why a student might not receive and understand the whole insight, understanding of Jeroen (Jheronimus)Bosch’s world, given by him to the community when looking at his painting Last Judgment triptych (fig. 2).

Figure 2: Hieronymus (Jheronimus) Bosch: The Garden of Earthly Delights

To arrive at a responsivity for the embedded codes, symbol, and signs, the artefact has to come into the mind again so that you can build on it. You have to stand in front of a Rothko painting, according to his instructions as closely as possible, to become immersed in the life, the thought, the understanding of his world embedded in the artefact to experience the change in time, space and experience resonations of a reality. In this way you can experience the redefinition of essence, and perception of scale and matter looking at Anish Kapoor creatures (fig. 3).  Going into the artefact and the artefact getting into our minds is a process of transformation of our frame of reference. This process is a starting point for opening up our mind to perceive signs, codes and information as they manifest themselves in our problem, question, complexity. It is the process of noticing difference and potentials that we never perceived and understood before.

Figure 3: Sculptures by Anish Kapoor. On the lef:t ‘Anish Kapoor in the Pont, Tilburg, The Netherlands, November 2012; on the right: “Cloud Gate’ Chicago, Ilinois, USA, April 2015. (photos private collection).
Figure 3: Sculptures by Anish Kapoor. On the lef:t ‘Anish Kapoor in the Pont, Tilburg, The Netherlands, November 2012; on the right: “Cloud Gate’ Chicago, Ilinois, USA, April 2015. (photos private collection).

Looking at a theory is like looking at any other conceptual artefact. One has to become engaged and has to explore the thinking of theory. It is these kinds of knowledge building conversations with the others in the artefact, and with others about the artefact in which relations, e.g. differences come into language in the conversation. Not as an individual property of the interlocutors. ‘What is’, is ‘laid down in the middle’ as a ‘rising above’ in collective, in community, as a common language of collective understanding (a hermeneutic ‘collective Verstehen’). The process is a rising above by a grounded language of understanding in which the ‘old thinking’ is revealed in its inclusive principles. Higher problem formulations and new syntheses are build. Partners, knowledge builders, in the conversation, ”transcend trivialities, oversimplifications and move beyond current (best) practice” (Scardamalia & Bereiter, 2010, p. 10; Scardamalia, 2002, p. 79).

The principle is the ‘knowledge building conversation’ which distinguishes itself from interpersonal dialectical dialogue, debate and discussion. The knowledge building conversation is not an adjusting to each other as partners in the conversation. Partners become engaged in the artefact, coming to the truth of the matter or praxis, under the resonation of understanding reality: a resonance of organic connectedness and dependency of our being as part of others and nature. Resonations that partners in the knowledge building conversation combine in a new common ground. In the ‘knowledge-building-conversation’ it is not merely against each other and putting your own positions forward, but a transformation into the common, into the collective. A transformation in which one does not remain who one was. (Gadamer, 1975, p. 360)[3].

The epistemic development being involved in such a process consists of the experience that language and knowledge building conversation are a medium for individuals to understand by collective understanding. It is the development of a language of understanding the difference that makes a difference for theorie and practice. To learn thinking in organic systemic connectedness in which ‘the’ difference is a source for the interdependency of what we are and what is. Understanding that nothing is an isolated, stand-alone object, a fact, a problem, a situation, a person as such, but all of this is what it is because of the organic ever changing connectedness. So not only the facts but the relationships are important to understand as well. A knowledge building conversation discourse is what Kegan indicates as an epistemic development in not only ‘what’ we know but also of ‘our way of knowing’ (Kegan, 2009). The restructuring of the frame of receiving an artefact of reality, making it possible to question facts, consider perspectives, biases and historical roots of thinking of who created the artefact. In the knowledge building conversation discourse you experience the cross boundary reconceptualization of object, motive and history of an activity of possible expansive transformations in an activity system by exploring the cognitive and emotional connectedness (Engeström, 2009; S. Paavola et al., 2004).

Conclusion and principles

The experience of a gap or boundaries like in many articles in this issue, is actually is the lack of responsive learning in education.  Bringing together research (e.g. an inquiry attitude and ability) practice and schools should be much stronger learning activities in supporting lstudents’ development. It is therefore important in developing learning environments in order to bridge imaginary gaps of crossing imaginary boundaries to be fully aware of what kind of learning is supported, and question yourself if responsive learning has space and is adequately covered and supported. Four guidelines can be taking in consideration in designing for responsive learning:

  1. Agency: more control for students of their mental activity (Bruner, 1996; De Jong, 1992) and improving students’ own ideas (epistemic agency; (Bereiter & Scardamalia, 2006a; De Jong, 2006; Scardamlia & Bereiter, 2014):
    Students have ownership of their learning and ideas
  1. Culture: ‘coming into language’ of how the way we live and think and construct thought are embedded in the knowledge we claim as ‘reality’ and how our mind set perceives and interprets signs in the ecology we are part of (Bateson, 1987; ’reflection; knowledge is justified belief’, Bruner, 1996; ’rethinking assumptions’, Sterling, 2009):
    Students question presumptions and ’realities’ of what they learn.
  1. Learning together: creating meaningful connections between individual and society by ‘coming into presence’ into an intersubjective space (Stroobants, & Wildemeersch, 2001; Wildemeersch & Stroobants, 2009). The sharing and negotiation of meanings to construct shared conceptions (Charmaz, 2014; Dillenbourg, 1999; Stahl et al., 2014); explanatory coherent practical knowledge, combining ‘know-how and know-why’ aiming at solving problems, guiding practice. Understanding through collaborative explanation (Bereiter, 2014; Scardamalia & Bereiter, 2014).
    Students build new meaning together for solutions. 
  1. Knowledge building: not simple ‘learning in the raw” (Bruner, 1996), ‘rote learning’, reproducing or solving a well-known problem, but a semiotic process of entering into a collective understanding, grounded in the consequences of the system of relations that makes a difference for life. (’community knowledge advancement’; conceptual understanding, enculturation in the world of creating knowledge; Scardamalia & Bereiter, 2014; Bereiter, 2002; De Jong, 2006; cultural artfacts, Stahl, 2006).
    Students learn together and go beyond what is known and done.

How do these crucial ideas enter language in teachers’ interests, their passion for teaching, their questions, their drive to improve their teaching and education? The research presented in this issue may give us some insight in the state of art and which steps are still needed.

Reading guide

The next three articles are more conceptually oriented studies based on practice based research. Meijer and Kuijpers approach the relationship of educational researchers and practitioners in mode 2 research as a gap to be bridged. They come up with design principles rooted in different learning and instructional paradigms. Van den Berg approached the collaboration between researchers and practitioners not as a gap to bridge but as a crossing boundaries activity that requires particular abilities from both professional sides to get into a mutual learning mode and developing a transdisciplinary ability as teacher-researcher, especially in in case the educational issue is of a complex and persisting nature. Kukkonen actually jumps into what kind of learning experience that could be especially from a perspective of students. He comes up with five specific elements of good student learning experience, which in our opinion are not limited to first year UAS students. These three articles are a good conceptual base to read and go into the other articles and make up your own ideas how UAS education and practice (and research) could become more of an effective activity system in which students develop their competence and abilities.

The next three articles actually concern practices in which gaps between education and practice within professional fields are experienced and activities are undertaken  to cross the boundaries. Heldal developed a process steering instrument to enhance systematic communication between stakeholders and students’ industrial doctoral research projects. Boehm et al. is an example in which the boundaries crossed between the disciplines of arts and social care with multi professional teamwork as a bridge. In the study of Cors and Robin a science education laboratory is the support to let students cross the boundaries of science in order to develop their ideas of the world of science. Like the other articles, also this study is interesting to read from the perspective of the collaboration and boundary crossing of researchers and educational practitioners.

The last five articles concern even more innovative UAS educational practices aiming  to bridge or to cross the boundaries with practice. Helminen takes a progressive position by stating models, the issue of mentoring and being credited for developing nursing competence by learning in and from daily (paid) work. Alvaikko brings students, teachers and institutional partners together in living lab in which real life problems, acting in a real ecosystem and active user-involvement contributes to the knowledge creation. An arena in which teachers mediate between wishes of partnering organizations and curriculum requirements. Karjalainen et al. also use the idea of LABs for bridging education and working life to develop students’ 21th century skills by providing students a learning experience of creating new solutions and innovations across disciplines for a more ecological and sustainable responsible economy. Laukkanen bridges the gap between education and practice by the approach of entrepreneurial coaching leading from ideas, intention to concrete business actions. Besides a good description of the educational model of entrepreneurial coaching the article also goes into the expectations and experiences of students. The last article from Koponen gives insight in the importance of good dialogical feedback, an educational instrument which is relevant for all educational settings.

This special issue by EAPRIL and UAS-journal gives voice toUAS-research practitioners who are engaged and passionate in their work to make UASs  an even better learning environment for students and professionals than they are already for developing relevant knowledge, skills, competence for their future work activities,  for their personal and societal lives. Our wish is that more international issues will follow to exchange and share the work that is done internationally and to enhance the responsivity of education to the developments and needs in working life and society.

We like to thank authors, reviewers, Editor-in-chief Ilkka Väänänen, and UAS Journal editorial staff.

[1] These paragraphs are based on De Jong 2015.

[2] (retrieved October 2015).

[3] “Die Verständigung über die Sache, die im Gespräch zustande kommen soll, bedeutet daher notwendigerweise, dab im Gespräch eine gemeinsame Sprache erst erarbeitet wird. Das ist nicht ein äuberer Vorgang der Adjustierung von Werkzeugen, ja es ist nicht einmal richtig zu sagen, Dab sich die Partner aneinander anpassen. Vielmehr geraten sie beide im gelingenden Gespräch unter die Wahrheit der Sache, die sich zu einer neuen Gemeinsamkeit verbindet. Verständigung im Gespräch ist nicht ein blobes Sich-ausspielen und Durchsetzen des eigenen Standpunktes, sondern eine Verwandlung ins Gemeinsame hin, in der man nicht bleibt, was man war. “

Photo (spiderweb): Minna Scheinin


Frank de Jong, Aeres UAS, Wageningen the Netherlands
Martijn Willemse, Windesheim UAS, Zwolle, the Netherlands
Mauri Kantola, Turku UAS, Finland
Mervi Friman, HÄME UAS, Finland
Margaux de Vos, EAPRIL, Leuven, Belgium

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Bridging the research-to-practice gap in education: the design principles of mode-2 research innovating teacher education


Current changes in society address new demands on professionals’ ability to respond to new and changing circumstances quickly and adequately (Coonen, 2006; Hargreaves & Fullan, 2012; 2002; OCW/EZ, 2009). This implies the necessity of continuous development to improve professional performance throughout the entire career. This general professional demand has consequences for teacher education (Darling-Hammond & Foundation, 2008; Scheerens, 2010). To support this lifelong professional learning, the development of an inquiry-based attitude (hereinafter: IA) is specifically recommended as a goal in teacher education (e.g. Cochran-Smith & Lytle, 2009). In Dutch teacher education at both initial and post-initial level, it is assumed that IA will allow teachers to create new knowledge of practice continuously with the aim to develop themselves as a professional and to improve their school context (Onderwijsraad, 2014). To be able to get more understanding about IA as a developable goal in teacher education, Meijer, Geijsel, Kuijpers, Boei and Vrieling (2016) conducted a multiannual empirical study and refined IA from an ill-defined global concept into a concept with reliable and valid characteristics. Their results indicated IA as a concept with two dimensions: an internal reflective dimension and an external knowledge-sourcing dimension. The internal dimension concerns intentional actions to acquire new professional modes of understanding and behaviour. The external dimension concerns intentional actions to gain new information and knowledge from relevant knowledge-sources. Our goal in this study was to create knowledge to support teacher educators’ in their pedagogical approaches to stimulate their students’ IA. However, the transfer of results from educational research into educational practice has proven to be complex (e.g.Broekkamp & van Hout-Wolters, 2007; OCW, 2011). To help bridge this gap, practice-based scientific mode-2 research design is presented as a research method that can help (Martens, Kessels, De Laat, & Ros, 2012). The assumption in this method is that partnership between researchers and practitioners will contribute to creating meaningful, generalisable knowledge and contribute to the transfer of this knowledge into practice. We therefore used this research design in our two-year follow-up study. In partnership with educators, we designed, tested and redesigned a professional development programme and we conducted a multiple case study. In this study (Meijer, Kuijpers, Boei, Vrieling, & Geijsel, in press) we gained insight into specific characteristics of professional development interventions that encourage teacher educators’ deep learning in stimulating IA-development of their students.

To our knowledge, there are few studies that provide specific insight into the design of practice-based scientific mode-2 research (hereinafter: mode-2 research) or into the actual impact of this methodology. To contribute to an understanding of how mode-2 research can help to bridge the gap between educational research and practice, this conceptual paper will reflect on how the partnership between the researcher and five educators resulted in creating practice-based scientific knowledge, professionalising teacher educators and simultaneously contributed to innovating teacher education practice. With this reflection, we aim to contribute to the development of mode-2 research as promoted in a research manifest on practice based scientific research (Martens et al., 2012). The study we are reflecting on is summarised in Table 1 and Table 2.

In what follows we first describe mode-2 research as a relatively new mode in social science and the general scientific requirements and usability criteria our research had to meet. Secondly, we report researchers role; recruiting practitioners and organising research meetings. Thirdly, we reflect from theoretical perspectives as to how and why our approach affected educators’ professional development and brought innovation to teaching practice. In conclusion, we present our working hypothesis on design principles in mode-2 research and discuss its complexity in design and the demands researchers must meet to monitor and facilitate simultaneously the quality of the research process and the learning of the practitioners.

Table 1. Process display of the mode-2 study we are reflecting on
Table 1. Process display of the mode-2 study we are reflecting on

1. Mode-2 research

Traditional methods of knowledge production and dissemination are the subject of debate in social science. Current scientific knowledge production does not transfer to practice adequately and opinions differ regarding the measures that should be taken to close the gap (Broekkamp & van Hout-Wolters, 2007). To bridge this gap, fundamental changes are suggested as a new research mode with regard to the interaction between science and society (Nowotny, Scott, & Gibbons, 2001). Social science production, in which socially robust knowledge is produced by social interventions in the context of application, was labelled by Gibbons et al. (1994) as Mode-2 research. Martens et al. (2012) promote this mode-2 research as an alternative to traditional educational research, in which randomised controlled trials still seem to be the golden standard. This, despite the fact that the complexity in educational research makes it impossible to control all variables (Cochran-Smith & Zeichner, 2010). Research based on randomised controlled trials aims to prove universal causal patterns in teaching and disparages the need for a stronger body of knowledge with practical, context-related relevance. The lack of knowledge with practical relevance is seen as one of the causes of the gap between science and practice. Hargreaves (1999) therefore even urged teachers to produce the knowledge they need by themselves. Martens et al. (2012) assume that research for which the questions are provided by practice – a partnership between researchers and practitioners – will contribute to creating meaningful, generalisable knowledge. From the perspective of learning, they argue that if practitioners participate in the knowledge creation process while participating in a practice-based scientific educational research in their own context, practical relevant knowledge will not only be created but it will also support the transfer of scientific knowledge into practice. Bronkhorst, Meijer, Koster, Akkerman and Vermunt (2013) found that collaboration with educators enabled the researcher to benefit from their expertise and that researchers’ position as a learner and researchers’ appreciation of the partnership impacts educators’ engagement ‘agency’ in the research . This means being an ‘agent’ and ‘owner’ instead being an ‘instrument’ or in other words ‘a tool for the researcher’ (p. 93). They found also that, compared to other research designs, collaboration supported the experience of research as an integrated part of everyday practice, which is also one of the goals in teacher education (Onderwijsraad, 2014). Researchers’ support of practitioner agency is thus seen as important because the more agency, the greater the chance that a solution will be found for the problem being researched (Bolhuis, Kools, Joosten-ten Brinke, Mathijsen, & Krol, 2012; Cochran-Smith & Lytle, 2009) and this will, as stated before, support the transfer of knowledge into practice.

1.1. Scientific requirements

Creating socially robust and practice-based educational scientific knowledge, under mode-2 conditions, has to meet the same generally accepted scientific standards as any other scientific research (Martens et al., 2012; Ros et al., 2012). However in mode-2 research, the relevance of the knowledge created is rooted in the (educational) context, in which the ‘problem’ occurred (Martens et al., 2012; Nowotny et al., 2001). A characteristic in this process of ‘local’ knowledge creation is to strive for external validity (i.e. generalisable insights) beyond the locus of knowledge production. Because practice-based research often works with small populations, it means that an attempt must be made, fitting within this type of search, to maximise generalisability without affecting the usability of the knowledge for the context in which the research took place (Ros et al., 2012; Verschuren, 2009). Furthermore, mode-2 research must be carried out in the wording of the scientific criteria that relate to the internal validity; controllability; cumulativeness and ethical aspects. The research must also meet the usability criteria with a view to the practice (Martens et al., 2012; Ros et al., 2012). The usability criteria define that the results must be accessible and understandable for the field of education; the results must be perceived as relevant and legitimate and the research must provide handles to improve educational practice.

1.2. Meeting scientific requirements in our study

In our two-year mode-2 research, we have secured internal validity by conducting it in the educational context in which the issue occurred. The study was executed in collaboration with an expert group of five teacher educators as co-researchers (Meijer et al., in press). The research process was characterised by iterative cycles of design, evaluation and redesign (McKenney & Reeves, 2013) and consisted of two phases: (1) a preparatory phase of designing, testing, evaluating and improving a theory-based professional development programme and (2) a main study phase in which the designed development programme was carried out. To build a strong partnership between the researcher and the participating practitioners, we followed Eri’s (2013) advice and involved them in constructing the design, and not only in testing the design, with the aim of supporting practitioners’ agency and ownership in the subject of the study.

To create generalisable knowledge we conducted the research as a parallel multiple case study (Swanborn, 2010) in four different teacher training courses. Four fairly homogeneous groups of teacher educators on four different teacher training courses at Bachelor and Master level at a professional university in the Netherlands were followed. The study resulted in clarification of the active ingredients of the designed interventions that supported the targeted development. We found that aligned ‘self-study’ interventions at personal, peer, and group level, guided by a trained facilitator, supported the aimed learning (Meijer et al., in press). To be able to reflect on this research from the perspective of partnership between researchers and teacher educators as co-researchers (hereinafter: expert group), we recorded and transcribed the research meetings (see table 2) with the expert group.

To meet the usability criteria we described our process of scientific knowledge construction and associated ethical aspects in a scientific publication and shared the results in the locus of the research. The way in which we further comply with the usability requirements is in fact seen in the focus of this reflective paper. In it, we look at how our collaboration with practitioners in the role of co-researcher resulted in socially robust scientific knowledge which contributed to professional development and is being implemented in practice. It should be noted that this implementation took place outside the scope of this research. This is because of the time that this implementation process took. In fact, the implementation process is still underway two years after the completion of this research.

2. Partnership between researcher and teacher educators in our study

The collaboration between practitioners and researchers is argued as a thriving force in developing new practices and educational change. To reflect on this assumption from our own research experience we will first successively report researchers role; recruiting practitioners and the research meetings between researcher and practitioners. Subsequently, in section 3, we will reflect on how our partnership between researcher and practitioners contributed to bridging the gap between science and practice. We reflect from theoretical perspectives on transfer of learning and development; practitioners’ knowledge creation and innovation and organisational learning.

2.1. Researcher

For mode-2 research it is important that the researcher(s) has coaching and consultancy skills in addition to research expertise and is able find balance between the relevance for the participating practitioners and the precision required by in scientific research (Martens et al., 2012). The researcher in this study (i.e. the first author) conducted research in her own professional context. She has an extensive experience as a teacher educator, trained supervisor/coach and is also responsible for the design of the professional Masters’ curriculum in the faculty where this research was conducted. This dialectic and simultaneous relationship between being a scholar and practitioner is an increasing phenomenon in educational research (Cochran-Smith, 2005). Before starting, and while conducting our research, the interwoven roles of the researcher were an explicit object of attention and reflection.

2.2. Recruiting the Practitioners

As pointed out above, besides creating practice-based scientific knowledge, the professional development of the collaborating practitioners is also one of the goals of mode-2 research. For this reason, we firstly based our research design on two preconditions in teacher-professionalisation, as reported by Van Veen, Zwart, Meirink and Verloop (2010): the subject of our study was in line with school policy and the participants were facilitated adequately by the management. Secondly, we decided to use the model of a professional learning community because this supports professional development (Lunenberg, Dengerink, & Korthagen, 2014; Van Veen et al., 2010), it supports innovation processes (Hargreaves & Fullan, 2012; Mourshed, Chijioke, & Barber, 2010) and it supports collaboration in designing, experimenting and re-designing (McKenney & Reeves, 2013; Van den Akker, Gravemeijer, McKenney, & Nieveen, 2006).

To recruit practitioners as co-designers and co-researchers in our research project, we organised a meeting with five experienced educators who were proposed by the management for practical reasons such as availability. We presented our research goal, basic design principles and the requirements that the participants had to meet. By being clear about our expectations of the participants’ qualities and commitment, we aimed to avoid drop-out on account of disappointment (e.g. Walk, Greenspan, Crossley, & Handy, 2015). First we presented our research goal as designing and redesigning a professional development programme based on theory and on practitioners’ knowledge and exploring which specific intervention characteristics support teacher educators’ professional development in stimulating students’ IA (Meijer et al., in press). We explained the importance of commitment in participating in a professional learning community during a two- year educational design-research within their own context. We also explained the importance of being an experienced teacher educator since we needed expert knowledge in designing a professional development programme. Experience was also important considering the plan that in the second phase of the study, the participants themselves would offer the designed programme to colleagues, and therefore we assumed that their credibility as a teacher educator should be beyond doubt. Furthermore, we highlighted the importance of being motivated to contribute to generalisable and reliable practice-based scientific knowledge by systematically, inimitably and accurately questioning their own practice. They also had to enjoy designing and redesigning interventions with the aim of improving them. Finally, we explained that they had to demonstrate commitment to participating in all the research meetings planned over the two years. Collaborating on this planning was presented as the first step in our partnership.

This meeting resulted in the voluntary participation of all five experienced (8-18 years) educators (hereinafter: expert group) aged between 43-58 and all female. They were facilitated with 90 hours of extra ‘professional development’ time over the two years, in addition to the standard annual time.

2.3. Research meetings

Before reflecting on ‘our’ partnership, we will give a short chronological overview of the research meetings between the researcher and the expert group (See Table 2, Overview of research meetings). All meetings can be characterised as ‘reflective dialogues’ (Mezirow & Taylor, 2009) between the researcher and the practitioners. Based on the practitioners’ wishes, we aligned our planning with the rhythm of our educational year. This meant no meetings during the busiest periods and not at the start and end of the year. The period between the meetings varied between two or three weeks.

Table 2. Overview of research meetings
Table 2. Overview of research meetings

3. Transfer of scientific knowledge into practice

To understand how collaboration with practitioners supported the transfer of scientific knowledge into practice, we firstly need to understand the underlying theories on the transfer of learning and professional development. Secondly, we need to comprehend the theories of practitioners’ knowledge creation and thirdly, we need to understand the theories of innovation and organisational learning. In these next sections, we will reflect – through the lenses of these theories – on our research journey, and illustrate our experiences with some vignettes.

3.1. Transfer of learning

The “changed and more experienced person is the major outcome of learning” (Jarvis, 2006, p. 132) is an important goal in mode-2 practice-based scientific educational research. In our research design, this learning concerned the development of teacher educators who participated as co-researchers. Since researchers in mode-2 research have to guide the participants’ learning and the transfer of this learning into educational practice, we built our research design on knowledge of learning theories in which the transfer of learning is a key concept.

Transfer of learning, and its underlying mechanisms, is still one of the most important educational research themes of the 21st century (e.g. Lobato, 2006). Thorndike (1906) introduced the concept of transfer and stated that the transfer of what is learned is dependent on the extent to which the new situations are the same as the original learning context. Thorndike conducted various empirical experiments and found that if an individual learns something in task A, it can be of benefit in task B if there are similarities between the two tasks. Although Thorndike’s view about transfer appeared to have been around for a century, later follow-up research showed that people can abstract things they have learned previously and subsequently apply this knowledge in contexts that are not obvious (e.g. Tomic & Kingma, 1988). However the transfer is stronger the more the contexts are alike. According to Piaget (1974), transfer occurs only if a measurement comes to the fore to show that what was learned had a demonstrable effect on the cognitive structure (knowing more) and that this knowledge can be operationalised in new situations. Piaget refers to this form of transfer as accomodating, by which he meant the capacity to adjust or transform familar strategies when a problem cannot (or can no longer) be resolved using the available tools and familiar methods. If this succeeds, previously acquired knowledge and insight is demonstrably transformed to a higher level.

The theory of the transfer of knowledge to other contexts was further illuminated by Branson and Schwarz (1999) in their AERA award winning review of research into transfer. They described Thorndike’s original view on transfer as the ‘Direct application theory of transfer’ which means that a person can apply previous learning directly to a new setting or problem. Based on their review, Branson and Schwarz proposed an alternative view of transfer that broadens this traditional concept by “including an emphasis on people’s ‘preparation for future learning’” (p. 68). They explicated the implications of this view for educational practices and elaborated Broudy’s (1977) instructional procedures with the aim of supporting the ability to adapt existing knowledge, assumptions and beliefs to new situations. Bransford and Schwartz highlight that people “actively interact” with their environment to adapt to new situations “if things don’t work, effective learners revise” (Bransford & Schwartz, p. 83) (See for example vignette 1). This so-called active transfer involves openness to others’ ideas and perspectives and seeking multiple viewpoints that are also important as a characteristic of critical reflection.

Vignette 1: Effective learners revise if things don’t work
Vignette 1: Effective learners revise if things don’t work

From the perspective of transfer, Illeris (2003, 2004, 2007; 2009) analyses leading theories of learning and differentiates four different learning types and looks at them in relation to their transfer capabilities. It is about mechanical learning, assimilating, accommodating and transforming. Each learning type is activated in different contexts, aims for different learning outcomes and varies according to the amount of energy learning requires. His learning theory rests on three different dimensions and two inseparable processes. He differentiates the cognitive (content), emotional (motivation) and social (interaction) dimension as well as the internal acquisition process in which new impulses are linked to earlier learning outcomes and the external interaction process that plays out between the learner, the teaching material and the social environment. According to Illeris (2014), professional learning already includes a change in practitioners’ work identity, the level of transformative learning. This happens only when the learner experiences a change in their own mental models with a perceivable impact on bringing about a change in attitude or behaviour. The individual then looks at the reality differently and also acts differently than previously (see for example vignette 2).

Vignette 2: Transformative learning
Vignette 2: Transformative learning
3.1.1. Supporting Practitioners’ Transformative Learning

To facilitate transformative learning Greeno (2006) calls for a learning environment in which stimulating and organising broad meaningful domain knowledge and automously founded actions are applied as two pro-transfer and inseparable factors. In this context, Kessels (2001) and Kessels and Keursten (2002) call for a knowledge-productive learning environment in which no educational material is prescribed, and instead research and reflection are the prime tools used to stimulate and facilitate meaningful learning. This is in line with the meta review by Taylor (2007) which indicates that accumulating personal learning experiences in a unique context about which there is critical reflection from various perspectives is one of the most powerful tools is promoting transformative learning. This is a process of communicative learning in which identifying and problematising ideas, convictions, values and feelings are critically analysed and given consideration. This requires a setting in which the participants dare to give themselves over to uncertainty and a certain degree of ‘discomfort’ so that they can learn personally. It is about daring mutual questioning of personal ‘truths’ and being prepared to modify existing paradigms on the basis of new insights. The shape transformative learning takes in education is in part dependent on the lecturer’s personal ideas about learning theories combined with the understanding of the reciprocal relationship between: (life) experience; critical reflection; dialogue; holistic orientation; context understanding and authentic relationships (Mezirow & Taylor, 2009). “Transformative learning is always a combination of unlearning and learning” (Bolhuis, 2009, p. 62). It is a radical process of falling down and getting back up again. According to Bolhuis, the unlearning element receives too little attention in research into and the forming of theories about learning. The helping hands that are offered with regard to ‘unlearning’ are implicit and are focused on reconstructing mental models and experimenting with new behaviour that can respond to behaviour and context through repetition and reflection.

In summary, this means that if mode-2 practice-based scientific educational research wants to contribute to the professionalisation of teachers, the research design must be based on ideas about learning theories with respect to the level of learning that is intended. In research into the professional beliefs and behaviour of the educator, a research setting in which transformative learning by the practitioners is facilitated is one of the design principles. This means that a research setting that is productive to knowledge is created, one which encourages and facilitates shared interactive research and the (re-)development of practical knowledge, beliefs and behaviour from different perspectives, with the aim of contributing to creating a ‘changed and more experienced person’ (see for example vignette 2).

Looking back over our research, we can typify our design of the learning environment in which the researcher and educators design and research together as a learning environment in which various levels can be learned. The accent in this was (1) having reflective dialogue which was dominated by: obtaining conceptual clarity about key concepts and the significance of this for practical actions and research into personal beliefs and the impact of these on actions; (2) the design of a theory-based analysis tool that, over a number of cycles, we ‘tested, reflected on, modified and again tested until we could work satisfactorily with it and were confident that the participants in the follow-up study could deal with effectively; (3) the design of interventions at ‘individual, peer and group level’ (Meijer et al., in press) via cycles of testing, reflecting on what worked, why it worked and how it could be improved; and (4) the design of a coherent professional development programme based on the interventions with the associated supporting materials and the basic premises of supporting learning from the participants. Because the practitioners researched with the researcher what interventions had an impact on their own development as well as how and when, they created new knowledge about professional development. They also integrated conceptual scientific knowledge about the subject of the research, ‘stimulating the inquiry-based attitude’, into their own educational repertoire.

3.2. Supporting Practitioners’ knowledge productivity

Following on from European and Americans examples (e.g. Cochran-Smith & Lytle, 2009; Loughran, 2007; Pickering et al., 2007), in the Dutch educational context and teacher training, we are increasingly seeing practitioner research used as a professional learning strategy to support individual and organisational learning. The teachers do their own research in their own context and the research itself as seen as an intervention (Bolhuis et al., 2012). According to Bolhuis et. al, practically-focused research by professionals contributes to more conscious consideration about the aims and effects of the work and promotes this approach where professionals create practical knowledge and use other people’s knowledge more in their work. The concept of practitioners’ knowledge productivity as a process in which new knowledge is created to contribute to innovation in the workplace was introduced by Kessels (1995; 2001). It refers to using relevant information to develop and improve products, processes and services. Supporting processes of practitioners’ knowledge creation requires expertise, such as “making tacit knowledge explicit, facilitating work and teambuilding, and supplying mentors and coaches with appropriate guidance abilities” (Kessels, 1998, p. 2). Knowledge productivity refers to ‘breakthrough’ learning’ which means that learners develop new approaches and are able to break with the past (Verdonschot, 2009). Both Kessels and Verdonschot believe that innovation processes are denoted as social communicative processes in which participants work in collaboration, whereby the quality of the interaction is important and should provide access to each other’s knowledge and connect these (see for example vignette 3). Paavola, Lipponen and Hakkarainen (2004) introduced the knowledge creation metaphor as a learning metaphor that concentrates on mediated processes of knowledge creation. A learning model based on knowledge-creation conceptualises “learning and knowledge advancement as collaborative processes for developing shared objects of activity […] toward developing […] knowledge” (p. 569)

Vignette 3: Social communicative knowledge creation.
Vignette 3: Social communicative knowledge creation.
3.2.1. Collaborative learning

In collaborative learning, the literature makes frequent reference to professional learning communities, group learning or learning from peers, and is seem as the most powerful driver for educational innovations (Hargreaves & Fullan, 2012; Mourshed et al., 2010). The concept of a professional community is multidimensional in nature and can be unpacked as practitioners’ peer learning with the goal of developing a shared vision that provides a framework for shared decision making on meaningful practice questions (see for example vignette 4). The aim is to improve practice from the perspective of collective responsibility, in which both group and individual learning are promoted. (Hord, 1997; Stoll, Bolam, McMahon, Wallace, & Thomas, 2006).

The positive impact of collaborative learning methods is convincingly present in research literature. The meta analysis by Pai, Sears and Maeda (2015) showed that compared to individualistic learning methods, learning in small groups ( 2-5 participants) promotes students’ acquisition of knowledge and has also positive effects on increasing the transfer of students’ learning experiences and outcomes into practice. From the perspective of cognitive load theory, that considers a collaborative learning group as an information processing system (Janssen, Kirschner, Erkens, Kirschner, & Paas, 2010), students working in a group outperform students working individually, because a group has more processing capacity than individual learners. Sharing the cognitive load increases the cognitive capacity to understand the learning objectives at a deeper level (Kirschner, Paas, & Kirschner, 2009).

Pai, Sears and Maeda (2015) found that the positive interdependence between the group members, interpersonal skills and carefully structured interaction contributed effectively to collaborative learning achievements. There is also general agreement that the reflective dialogue plays a key role in the interaction in collaborative learning (e.g. Fielding et al., 2005; Lomos, Hofman, & Bosker, 2011) and that critical friendship, with the emphasis on ‘friendship’, in the sense of equality, trust, openness and vulnerability (Schuck, Aubusson, & Buchanan, 2008) is a prerequisite for collaborative learning. Personal commitment, as in the sense of learner engagement (see for example vignette 5), is indicated as another precondition to resolve complex practice-based problems and find acceptable solutions. (Bolhuis et al., 2012; Fielding et al., 2005)

In their exploration of the relation between teacher learning and collaboration in innovative teams, Meirink, Imants, Meijer and Verloop (2010) found that collaboration in teams that focused on both “sharing of ideas and experiences” and “sharing identifying and solving problems” contributed to a higher level of interdependence. Collegial interaction that can be typified as ‘joint work’ is indicated as interaction with the highest level of interdependence. This is in line with other findings from research into factors that influence the transfer of good practice (e.g. Fielding et al., 2005). In this study, the transfer of good practise is seen as ‘joint practice development’ which depends on relationships, institutional and teacher identity, having time, and most important learner engagement. The importance of “the quality of relationships between those involved in the process” (p. 3) is highlighted because the transfer of practice is relatively intrusive and hard to achieve.

Vignette 4: Developing a shared vision


Vignette 5: Personal commitment and agency

In summary, this means that supporting practitioners’ knowledge productivity during mode-2 research requires a research design incorporates the theoretical ideas regarding collaborative workplace learning. Here, the practitioners use practice-focused as a professional learning strategy and not just as a tool to create knowledge.

Looking back on the knowledge productivity of the educators in our research design, we see strong correlations with, for example, the practitioner research self-study method (Loughran, 2007; Lunenberg, Zwart, & Korthagen, 2010). The aim of our research is very close to the central goal of the self-study methodology. This goal is to uncover deeper understandings of the relationship between teaching and learning about teaching, with the aim of improving the alignment between intentions and actions in the practitioners’ teaching practice. Like the self-study approach, our research design strongly appeals to individuals’ scholarly notions and qualities, where the systematic collation and analysis of personal data in a personal context supports a personal deeper professional understanding that can be shared with other colleagues. However, where we differ explicitly from the self-study approach is that our research design centred around ‘collective’ learning in multiple settings with the aim of creating a collective deeper understanding and generalizable scientific knowledge, and implementing this new knowledge into the practice of teacher educators. The importance of well-guided collaborative knowledge creation in small-peer groups is thereby emphasised by the expert group. The expert group highlighted the importance of flexible research guidance that is aligned with the ‘reality of the daily working context’ as a precondition to staying motivated to participate in this research project (see for example vignette 6).

Vignette 6: Flexible guidance
Vignette 6: Flexible guidance

3.3. Innovation in education

As well as professional teaching, mode-2 research also aims for innovation in the professional context. Therefore it is relevant to understand the relationship between individual and collective organisational learning (Argyris, 2002; Senge, Cambron-McCabe, Lucas, Smith, & Dutton, 2012). Innovation in education programmes is a complex, broad concept and concerns multiple relations and dimensions within multiple programme components. For a definition of what we can understand innovation in education, we use Waslander’s (2007) description in her review of scientific research on sustained innovation in secondary education. To her, an innovation is a set of activities which together comprise a concept or an idea which if implemented improves practice. An innovation is something ‘new’ that has added value for the future. Further, there is only an innovation of this ‘news’ manifests itself in people’s behaviour and is embedded in their day-to-day routine.

Innovations at the organisation level always relate to relationship between individual and collective learning and successfully triggering collective learning is a first step towards innovating. The research by Peck, Gallucci, Sloan and Lippincott (2009) into teacher education practices shows that the problems related to individual practice (raised by new policies) are often the trigger for faculty (collective) learning. Even though collective learning still delivers such well designed interventions and knowledge, it is no guarantee of successful implementation at the level of the organisation (Verdonschot, 2009). Based on her meta analysis of innovation practices, Verdonschot established that the skills and ambition of the individual implementing the intervention influence its success. In addition, the new knowledge that is to be integrated must be well-timed, relevant and appropriate (Eraut, 2004, 2007; Peck et al., 2009). If the knowledge was not acquired in a personal context, but through formal learning such as, for example, schooling, it often has to be transformed to the personal situation because the new knowledge doesn’t fit the actual situation in which it is required. To integrate the new knowledge requires practitioners’ meta cognitive skills in transforming knowledge and skills to the personal situation.

3.3.1. Supporting innovation in education

In supporting professional learning that is focused on innovating, it is essential to facilitate the generation of new reality constructions (Homan, 2005). Generating new reality constructs is central to the theory on organisational learning in the familiar work by Argyris and Schön (1978) and is aligned with the previously discussed theory on transfer of learning. Argyris (1992; 2002) differentiates between single-loop learning and double-loop learning. With single-loop learning, a lot is learned but nothing is learned about how to learn better. It is generally about solutions that are more of the same. Single-loop learning will therefore not contribute to innovations because it concerns only correcting errors without altering underlying governing values. To resolve complex problems for which new solutions are needed, double-loop learning is needed. This means calling on the ability to fundamentally think the problem through and learn from this through critical reflection. Argyris stated that to change organisational routines with success, organisational and individual double-loop learning processes should both be encouraged. In his opinion, it is impossible to change organisational routines without changing individual routines, and vice versa. Senge, Cambron-McCabe, Lucas, Smith and Dutton (2012) talk in this context about fundamental changes in mental models, systems and interactions which are a prerequisite to redesigning and changing the current situation. To support double loop-learning, Argyris calls for an increase in people’s capacity “to confront their ideas, to create a window into their minds, and to face their hidden assumptions, biases, and fears by acting in these ways toward other people” (2002, p. 217). He highlights the importance of encouraging self-reflection and advocating personal principles, values, and beliefs in a way that invites inquiry into them. This is in line with Eraut’s research (2004, 2007) in which he emphasises the critical importance of support and feedback in enhancing organisational learning, especially within a working context of good relationships and supporting managers. In addition, opportunities for working alongside others or in groups, where it is possible to learn from one another, are important.

In summary, this means that if mode-2 practice-based scientific educational research wants to help in innovating educational context, more is needed than stimulating double-loop learning by practitioners during joint design and research. Encouraging transfer between individual and collective learning and securing its implementation in the professional context requires a research design that is based on innovation theories that are leading in the monitoring of this complex form of learning.

Looking back over our research, we have experienced that the transfer of personal learning into organisational learning and innovation is highly complex and time-consuming. In our opinion, a well-designed implementation plan that is guided by principles from theories on organisational learning and innovation is needed prior to the start of the research. In our view, this plan must include management support and implementation facilities to ensure that the implementation doesn’t come to a halt when the researcher leaves.
In the study we are reflecting on, the researcher had a management position in two of the four participating educational settings and was able to influence the organisational policy concerning educating teachers and the demands the educators have to meet. In these two settings, our mode-2 research resulted in a successful transfer of scientific knowledge into our practice policy (see for example vignette 7).

Vignette 7: Transfer of scientific knowledge into organisational policy

In the other two settings, our research design was only successful from the perspectives of knowledge creation and professional development. Once the (co-) researcher had left, further implementation came to a halt. Our explanation is that having an implementation plan that is supported by the management (e.g. Eraut, 2004, 2007; Van Veen et al., 2010) is a prerequisite to implementing the innovation at the organisational level. We recommend that that if the researcher is not to execute the implementation plan personally, this should be done by an engaged practitioner who, in line with Verdonschot’s research (2009), has the courage, ambition and mandate to make the implementation a success. Looking back on our innovation we can see that, like many other innovations, it was triggered by new policy (Peck et al., 2009). This policy concerns the ambition of the Dutch Educational Council (2014) to promote the development of an inquiry-based attitude on the part of teachers.

4. Working hypothesis concerning design principles in mode-2 research

This conceptual paper is a reflection of our previous two-year mode-2 research journey (Meijer et al., in press) in which our partnership between researcher and practitioners successfully contributed to bridging the research-to practice-gap in education. That research concerned a multiple case study as part of which we worked with five experienced educators to design, test and explore a professional development programme. Our reflection shows that the partnership in our research helped to create socially robust scientific knowledge and that this collaboration contributed to the transfer of the knowledge created into the practice in which the research was conducted. The new knowledge was not just integrated into the practitioners’ actions, in two of the four settings where the research was conducted, it was also translated into internal policy documents. These policy documents are definitive in ensuring curriculum innovation and thus the required educational behaviour in the setting in which the researcher works.
Our contribution in shaping the theory regarding the design of mode-2 research comprises firstly the finding that partnership between the researcher and practitioners in creating practice-based scientific knowledge succeeds in closing the gap between theory and practice if the research design includes the objectives and a theoretically-based approach to both practitioners’ knowledge creation, practitioners’ development and the proposed organisational learning and innovation. Secondly our reflection resulted, from various theoretical perspectives of the partnership with practitioners, in concrete design principles, preconditions and recommendations for supporting and guiding practitioners during mode-2 research. We have set these out in the table below (see Table 3) and these can be seen as a working hypothesis for designing and guiding this kind of research. Allocation to the categories used is not a distinction because some of the recommendations apply within multiple categories.

Table 3: Design principles of mode-2 research
Table 3: Design principles of mode-2 research

To summarise: in this conceptual paper, we have reflected on the theoretical aspects of transfer of learning; professional development; practitioners’ knowledge creation; innovation and organisational learning on how partnership with practitioners can help in bridging the gap between theory and practice.

Our reflections have highlighted the importance of having three interwoven research designs in mode-2 research: (1) one design concerning the scientific knowledge creation process based on practitioners’ knowledge creation; (2) one design concerning the practitioners’ learning support in knowledge creation, professional learning and knowledge transfer and (3) and one design that guarantees implementation into practitioners’ practice at the organisational level. To gain a deeper scientific understanding in critical design variables in mode-2 research which at the same time help to create scientific practice-based knowledge, professionalise practitioners and ensure innovation, we recommend that mode-2 researchers write conceptual papers from the perspective of three interwoven designs to allow further meta analysis to be carried out in the future. We also advise further investigation into the qualities a mode-2 researcher must demonstrate as a facilitator of professional development and innovation. The researchers can use the design principles we have proposed as a working hypothesis for designing and guiding their own mode-2 research. Follow-up research into these design principles can support deeper understanding of how mode-2 research in education can bridge the gap between theory and practice.

Corresponding Author

Marie-Jeanne Meijer, PHD-student, Curriculum director at Windesheim University of Applied Sciences, Movement & Education, The Netherlands, mj.meijer(at)


Marinka Kuijpers, PHD, Professor at Welten Institute, Open University, The Netherlands, marinka.kuijpers(at)

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Boundary-crossing competences of educators and researchers in working on educational issues


About 25 years ago, I was conducting my doctoral research (Van den Berg 1992) with the aim of learning how basic education for adults had taken shape – after all of the relatively diverse precursors had merged – and how the environment, the organisation, and the supply of education were related. I spent a week each in 17 different institutions, during which time I conducted archival research, class observations and interviews. During the course of one academic year, I experienced the ins and outs of basic education, including the work pressure and commotion of the weeks preceding the summer holidays. One team that I observed called me a week after my visit because my interviews had created quite a stir. The underlying tensions between the precursors had suddenly become clearly visible, and the team did not want to leave for the summer holidays on that note. They had organised an extra team day in order to re-open a discussion, and they asked me to attend. In this way, they would have an independent observer and rapporteur, and I would gather supplemental material for my research. I had never before witnessed how the act of conducting research could have such a direct impact on practice, and how educators could immediately make use of this impact in a constructive manner.

Over the following years, the relationships between research, educational innovation, and teacher professionalisation remained of exceptional interest to me. How are knowledge from research and knowledge from practice interrelated? When and how do research inquiry and practitioner inquiry help educators achieve further professional development? How can research contribute to the improvement of the teaching profession with regard to learning and development? For example, Van den Berg and De Bruijn (2009) conducted a traditional literature review on competence-based education and reviewed documented practitioner knowledge on the subject. There appeared to be striking similaries between the two types of knowledge, the scienctific literature being more rigourous and the practitioner knowledge being more current. Van den Berg and De Bruyn (2009) suggested a research agenda that combined the two.

Another example is the reflection made by Van den Berg and Streumer (2011) on a Workplace Learning Breakthrough Project. They proposed that the relationship between research and practice has yet to be precisely determined in practice-based research. Both the willingness and competence of researchers and teaching professionals to collaborate on urgent issues appear to be particularly important factors for success. In retrospect on the Breakthrough Project, Van den Berg and Streumer (2011) determined that the process of conducting the study has rested primarily with the researchers, that the scientific quality of the research could nevertheless be questioned, and that the study had contributed less than had been hoped to changes in practice. Perhaps more patience is required, because the reality of workplaces is just too complex to grasp within the space of a three-year project (Van den Berg & Streumer 2011).

I am constantly searching for ways to collaborate with others to arrive at answers to the types of questions indicated above, as well as for ways to make these answers productive in research and educational practice. I am interested in educators and researchers ‘jumping in’ to apply these questions to real cases and working on them collaboratively. This article elaborates on this theme of ‘jumping in’. The discussion presented is based on a theoretical framework that is currently being developed (Van den Berg, 2016) for a research programme in the Netherlands, at Aeres Wageningen University of Applied Sciences. This programme aims at enhancing our understanding of the course of collaboration between educators and researchers on issues related to learning and development, as well as our understanding of how participants can improve their collaboration. The conceptual framework presented forms the basis for the empirical research agenda of the initiated programme.

This article will begin by introducing the theoretical background of this study. Second, the central question and methodology will be presented. Third, the resulting framework will be described in three parts, namely: a) the nature of problems, b) the concept of research competence and c) the concept of transdisciplinary competence. The article will end off by drawing conclusions and offering a sketch of the research programme initiated.

Theoretical background: Complex educator-researcher relationships

Knowledge and innovative competence are becoming increasingly important in society (OECD 2002; Onderwijsraad 2014; Rijksoverheid 2015). This is consequently changing the demands that are imposed on professionals. Routine skills are becoming less important, while non-routine skills and cross-disciplinary competences are playing an increasingly important role (OECD 2013). Analytical, investigative and reflective competences may serve as examples of this. For professionals, such qualities are important for optimal performance. For organisations, they are essential to improving responsiveness, innovation, and productivity (Volberda, Jansen, Tempelaar & Heij 2011; Onderwijsraad 2014, 9).

These changes call for increasing interaction of organisations on the one hand (enterprises, firms, non-commercial institutes), and research institutes on the other hand, and thereby of both practitioners and researchers. In narrowing the bandwidth of organisations to the domain of education and teacher education, the need for inquiry and research in educational institutes becomes explicit. And, addressing questions about learning and development by working in a systematic, inquiry-based manner (if possible in collaboration with external partners such as related organisations and researchers) appears to offer exceptional opportunities for realising sustainable improvements in our teaching practices (see, for example, Schenke 2015). At the same time, experience shows that persistence is also at play. Boundary crossing by practitioners and researchers has proven to be quite complicated, even when conditions appear favourable. Partners in innovation projects fail to complete their learning cycles, and research often fails to make the desired contribution to practice (Den Boer & Teurlings 2015; Schenke 2015; Van den Berg 2013).

The development of inquiry- and research-based education is subject to several inevitable challenges. For example, researchers still argue that their findings are not used to the extent that they should be, while educators argue that research is too often engaged in stating the obvious (‘bashing in open doors’), in addition to being reported in an inaccessible manner and containing no concrete guidelines for application (Broekkamp & Van Hout-Wolters 2006; Onderwijsraad 2006; Onderwijsraad 2011; Teurlings et al. 2011). Strengthening the usability and application of research requires more intervention than merely adding usability requirements to studies, imposing research duties on educators, expanding the research capacity in schools, and enhancing the findability and accessibility of research. Even if everyone endorses the importance of research and works to bridge ‘the gap’ between research and teaching practice, the practices of researchers and educators will not come together automatically.

The linear Research-Development-Diffusion (RDD) model of knowledge development followed by development work, diffusion, and application is being increasingly supplemented by alternative models, such as practice-based research in professional learning communities, knowledge-based workplaces, and academic workplaces. As advocated by Gibbons et al. (1994), this involves supplementing knowledge development by researchers in the traditional scientific method (Mode 1) with interactive researcher-practitioner knowledge development (Mode 2). Approaches like the Ecologically and Transdisciplinarily Inspired (ETI) research approach (De Jong, De Beus, Richardson & Ruijters 2013) further elaborate on this thinking. In this approach, researchers and practitioners engage in transdisciplinary collaboration in order to understand and resolve professional issues. Both practical and scientific knowledge have a voice in knowledge development, and all partners involved in the conversation learn from this (cf. De Jong 2015, 43-57). It is therefore a way of contributing to the general knowledge base (theory), as well as to practice.

Although interactive approaches such as Mode 2 and ETI are clearly on the rise, RDD thinking continues to hold a prominent place in our systems, including the associated processes of agenda-setting, funding, and accountability. This is not only the case in education, but also in other domains. Wehrens (2013) studied academic workplaces in healthcare. He proposes that we open a discussion concerning the practice of speaking in terms of ‘bridging the gap’. The image of a gap can reinforce the perception of research and practice as two separate worlds with completely different logics, motivations, and routines, thereby needlessly complicating the process of building bridges. The boundary traffic is actually more intense and fertile than could be expected, based on the image of two separate worlds. The perspective of mutual knowledge development entails looking at what does exist – the boundary practice, the bridge and, particularly, the traffic (active dialogue and negotiation on issues that belong on the agenda) – instead of looking at what does not exist (the void of the gap).

Crossing one’s ‘own’ boundaries and searching for cooperation is expected to result in more suitable and applicable answers to professional questions such as those in educational or healthcare practice (Akkerman & Bakker 2011; Akkerman & Bakker 2012). In particular, the interactive models of practice-based research (Mode 2, ETI) call for specific boundary-crossing competences of both researchers and practitioners. Exchanging information and using and reinforcing each other’s insights, instruments or other qualities requires attention to differences in culture and pace, mutual interests, and trust, as well as the relationship between factors at play both within and beyond the research-practice partnership. This attention should ensure the proper conditions for exchanging information and for using and reinforcing one another’s insights, instruments, or other qualities (Coburn, Penuel & Geil 2013; Ruijters 2016). Interactive research also calls for balancing the research role and the practice role, which demands both role stability and role development (De Bruijn & Westerhuis 2013). Andriessen (2014) introduced the concept of research competence as a specific quality needed for highly-educated professionals (in general, not only in the educational field). These individuals need to think and work from an inquiring stance, utilise existing research, and must be able to conduct small-scale research themselves. For practice-based researchers, Andriessen (2014) points to the scientific rigour and practical relevance of their work as necessary qualities. Further elaboration on these insights is required to more precisely define boundary-crossing competences.

Central question and methodology

As should be clear from this discussion, much work remains for practitioners and researchers in their joint efforts to clarify professional issues and contribute to solutions. To this end, we should also ask ourselves several questions and determine our position. For example, as educators, what views do we have on teacher-research and practice-based research? Do we ever discuss these views with researchers? How willing are we to acknowledge our prejudices and compare them with the opinions of others? Are we sufficiently open to findings from research? What do we need in order to convert information from research into guidelines for action in our own practice? As researchers, we should be asking ourselves questions too, for example, about our views on the contribution of research to educational practice. Would we be willing and able to make our research primarily dependent upon the issues with which schools are struggling?

In the interest of enhancing our understanding of the course of collaboration between educators and researchers on issues related to learning and development, as well as our understanding of how such collaboration can be improved, Aeres Wageningen University of Applied Sciences in the Netherlands initiated a research programme focused on the following central question: How can boundary practices between educators and researchers be reinforced? In this research programme, educators can be both teachers and teacher educators. Researchers in this field can be both (internal) teacher-researchers and (external) practice-based researchers.

The first step in the research programme is a conceptual study. During 2015, three intertwining processes took place: a) reading snowball-sampled literature, b) a (narrative) examination of, and reflection on, earlier publications by the author and c) a discussion of preliminary results of the study with both educators and researchers. These processes led to the gradual emergence of the conceptual framework as presented in the results. The conceptual study started from the key concept of research competence as formulated by Andriessen (2014). As Andriessen states, higher-educated professionals should be able to work with an inquiring stance, utilise existing research, and conduct research themselves. What concepts form the basis for this set of three subconcepts? What research on it is available? What specific features belong to research competence in the educational domain? Next, shifting the perspective: if practitioners need research competence, what do (practice-based) researchers need? They, too, need research competence, of course, but what more? Under this line of thinking, the concept of transdisciplinary competence emerged and was developed. Finally, now that we have these two competences, what kinds of professional issues will benefit from this? This third concept of professional issues is the first to be addressed in the next paragraph.

Three types of educational issues; three possible roles of research

The nature of professional issues concerning learning and development is important for the contribution that research can make to the resolution of such issues. The manner in which these issues can best be addressed depends primarily upon their relative simplicity or complexity, as well as upon the clarity of the solution. Three types of issues can be distinguished as follows:

Simple educational issues
Simple issues, in which both the actual issue and its solution are clear, demand substantive expertise in order to improve existing rules and support behavioural change. Schein (2005) refers to this as the ‘expert model’. These types of issues generally lend themselves well to informative learning (Kegan, 2009), as is the case with learning from a book and applying the knowledge gained.

In such cases, the role of research could consist of evaluating whether the solution is actually sufficient, or whether unexpected circumstances complicate the situation. In most cases, however, conscious reflection, discussion with colleagues and students, and possibly engaging in a mutual search for potential improvements should suffice (compare the concepts of ‘reflection-in-action’ and ‘reflection-on-action’ as defined by Schön 1987). How do I proceed in supervising my students today? What has the team meeting achieved?

Complicated educational issues
In general, when referring to complicated issues, the issue is clear, but the solution is not. Such situations require diagnoses and remedies, as outlined in Schein’s (2005) doctor-patient model. In educational contexts, this concerns issues such as: Does our curriculum offer students sufficient flexibility? How can we improve the correspondence between interim formative assessments and final assessments? In these situations, ‘the right solution’ is developed through behavioural prescriptions and tools. The learning is assimilative (Illeris 2010).

Research can help create an overview of existing solutions, as well as test these solutions. In many cases, however, it is enough for educators to adopt an inquiry-based approach. Commonly-used tools in this regard include the Plan-Do-Check-Act (PDCA) cycle (Deming 1996), Contexts-Interventions-Mechanisms-Outcomes (CIMO) logic (Denyer, Tranfield & Van Aken 2008), and Lesson Study (De Weert & Logtenberg 2011). Attention to teacher inquiry is also reflected in concepts centring on the use of available data, including result-oriented working methods, evidence-informed education, and Positive Behaviour Support (see for example Bruggink & Harinck 2012; Schildkamp 2012).

Complex and persistent educational issues
Complexity and persistency apply to situations in which the core of the problem is not particularly clear and/or in which no solution is immediately evident. For example, how can we optimise teaching and learning in hybrid configurations of school, the workplace, and virtual environments? Such contexts call for a path in which the issue can be dissected and possible solutions explored. It is conceivable that such situations demand fundamentally different ways of looking, thinking, and acting (so: transitions). Issues that require ‘only’ the replacement of old routines entail accommodative learning (Illeris 2010). If more extensive changes are necessary, transformative learning is needed: instead of calling for expanding our knowledge and competences, such situations require us to change the nature of our knowledge and competences across the entire scale (Kegan 2009; Illeris 2010).

Research can support the learning needed in a variety of ways: it can be used to describe and clarify the issue, to offer perspectives, to identify possible explanations, to mention and compare possible solutions, to conduct experiments and to monitor processes. In this way, research could fit well with efforts to build sustainable development in education and schools. Both processes proceed in an iterative manner, and both are characterised by a relatively slow pace. The interaction could be described as a continuous process in which research helps to improve our understanding of practice and to support school development, which in turn serves as a source of theory development (Schenke 2015, 80-81).

Research as careful ‘slow’ thinking on educational issues
So, in broad terms, different types of research are suited to educators’ professional problems of different levels of complexity. Particularly for complex and persistent issues, it may be helpful for educators and researchers to start working together. Nevertheless, people have a natural tendency to simplify issues to such an extent that existing routines will suffice to address them (Kahneman 2011). The urge to think from within existing patterns can cause us to opt for quick solutions. For example, to counteract student absence, we might be tempted to either introduce a mandatory attendance policy, create registration systems, or report to parents instead of adopting an inquiry approach that would require more time and transformation. One consequence of our preference for existing patterns could also be that we would opt for a traditional, linear research approach, whereas interactive research would presumably yield more sustainable benefits. However, if an issue concerning learning and development does call for the type of slow thinking that is known as research, the educators and researchers involved should be equipped to collaborate successfully. The following text addresses the next two primary concepts in this regard: the boundary-crossing qualities of research competence and transdisciplinary competence.

The research competence of educators

Research competence is the overarching term for various elements that serve as characteristics of professionals such as educators, i.e. a) possessing an inquiring stance and the competence to think and work from within this attitude, b) being able to apply knowledge from available research to one’s own professional practice and c) being able to independently design and conduct small-scale, practice-based research (Andriessen 2014). In addition to these three elements of research competence, there is another overarching element that applies specifically to educators. This special characteristic is that educators- even more than other professionals – support others in the process of learning, including in the development of research competence (Nijenhuis et al. 2015; OOB 2015).

Figure 1: Elements of educators’ research competence
Figure 1: Elements of educators’ research competence

Research competence is an integral part of our professionalism, and it should thus always be seen in relation to other qualities that make us who we are and what we do: our professional identity. The four elements of research competence represented in Figure 1 can be described as follows.

Inquiring stance
First, an inquiring stance can be defined as having an open attitude, being curious, being critical, and wanting to understand, support, justify, build, concede and innovate (Bruggink & Harinck 2012; Losse & Nahuis 2015; Van der Rijst 2009). Although competences in research and reflection do not necessarily constitute a component of an inquiring stance, these are important ‘tools’ for its application and thus its contribution to the assignment of meaning and the competence to improve action (Bruggink & Harinck 2012, 50-52). On the other hand, an inquiring stance can be seen as a prerequisite for conducting research (Van der Rijst 2009). We could argue that, without an inquiring stance, research would remain limited to a trick, a mechanical procedure that is not fuelled by any curiosity about answers to the issues being investigated.

For relatively simple issues, an inquiring stance is manifest in asking reflective questions, engaging in discussion with colleagues and students and possibly in collaborating to identify opportunities for improvement. In this case, the inquiring stance is thus the attitude of reflective practitioners, who build delays into their actions. For more complex issues, behaviour based on an inquiring stance is not merely reflective, but also more inquisitive. In studies by Bruggink and Harinck (2012) and by Greve, Munneke and Andriessen (2015), this is summarised through the terms ‘inquiry-based learning’ and ‘proper examination’. Finally, for issues that are complicated and persistent, an inquiring stance is evident in the methodical application of research competences. In this regard, we refer to practitioner research (by educators), practice-based research (by researchers), and everything in between.

Applying research
The second element of research competence, applying research in one’s own professional practice, contributes to keeping the vocational field up to date. It entails modernisation and innovation based on existing research rather than according to intuition and experience. Some research knowledge has been included in manuals, and some remains for current and aspiring educators to read on their own in scientific publications and to use in their actions.

As argued by the Netherlands Educational Council (Onderwijsraad 2006, 9), research can ‘yield a reliable judgement concerning the suitability of methods and approaches, thus preventing the protracted ideological discussions and “trial and error” in practice.’ The Council does not advocate the wholesale adoption of evidence-based education, but a phased and differentiated approach. Depending upon the state of knowledge in a given field, this is expected to generate a systematic process of exploratory research, development work, and practical experience that will ultimately produce an overview of what works, as well as why and how it works. Only then can hard experiments with control groups be justified (Onderwijsraad 2006). This approach could be compared to the model elaborated on by Van Yperen, Veerman and Bijl (2013), who distinguish four levels of evidential value (applied to the context of youth services): 1) descriptive evidential value, which demonstrates the potential of interventions; 2) theoretical support for promising interventions; 3) indicative evidential value, based on well-defined interventions that have proven effective and 4) causal evidential value, which demonstrates the efficacy of interventions. This model does justice to the notions of practice-based evidence and evidence-based practice, two movements in which the four-level model of evidentiary value can help realise the interaction between practice and evidence (Van Yperen et al. 2013).

The consideration of the possibilities of ‘applying research’ can be of relevance to any type of professional issue as described above. Nevertheless, building on available research as a foundation for individual actions is not commonplace. Negative connotations sometimes stick to evidence-based working methods. The concept is associated with hard evidence and a linear approach to research that would lead to prescriptions for action set in stone for educators, without allowing room for their own practical wisdom. This negative connotation threatens to allow ‘fast thinking’ to take precedence over the desire for innovation. One effect could be the absence of motivation on the part of educators to start working with research outcomes. It could potentially be beneficial to encourage them to develop an inquiring stance, thus making them curious about the outcomes of research. At the same time, they would also become more critical and less likely to accept research outcomes as irrefutable truths. Instead, they would be more likely to see such results as a supplement to their practical knowledge and as a potential foundation upon which to base their own actions (Enthoven & Oostdam 2014; Verbeek & Wassink 2014).

Conducting research
Conducting (small-scale, practice-based) research – the third element of research competence – refers to targeted, reproducible, and systematic data collection (Cochran-Smit & Lytle 2009; Ponte 2012; Zwart, Smit & Admiraal 2014). It entails a research cycle in which methodological rules are followed in order to clarify an issue; to map literature; to design a research approach; to collect, process, and analyse data; to describe results; to derive conclusions; to make recommendations, and to report on all of these actions. Conducting research can contribute to insight into their own actions, the process of building on insights from others, the development of knowledge of their own changing profession, the professional development of educators, and to the quality and development of their work practice (Admiraal, Smit & Zwart 2013; Bruggink & Harinck 2012; Ros et al. 2013; Van den Bergh & Ros 2015; Van Veen, Zwart, Meirink & Verloop 2010; Vanassche & Kelchterman 2014). Conducting research also lends itself to the reinforcement of an inquiring stance and to the acquisition of knowledge and skills with regard to conducting research (Van der Linden 2012). Conducting research is furthermore an effective learning strategy that contributes to self-directed learning. Research skills and study skills overlap to a large extent (Geerdink 2010).

In their international literature survey of peer-reviewed research published by teachers, Admiraal, Smit and Zwart (2013) distinguish four types of teacher research: action research, lesson study, self-study, and design-based research. The results of the studied teacher research appear to be increased teacher knowledge, greater use of research in practice, an increased capacity for critical thinking, and increased self-confidence as teachers. ‘Most importantly, however, participation in research appears to be a meaningful form of professional development for teachers’ (Admiraal, Smit & Zwart 2013, 25, translated). The authors observe that few of the studies they examined contributed to the generation of scientific knowledge concerning education, even though such results could be expected, given their selection criteria (that is: peer-reviewed and published research). The scope of teacher research thus apparently remains limited to the knowledge base within the field of educational practice. It could be discussed whether this ‘limitation’ really is a pity or if it is more than worth the trouble, in light of the often-painstaking effects of research conducted by outsiders in practice.

Supporting the development of research competence
Fourth and finally, the element of supporting others in the development of their research competence applies to both teacher educators and educators elsewhere in the domain of education. The most efficient manner of reinforcing the research competence of students is not yet clear (Bruggink & Harinck 2012). For several years, teacher-training programmes in the Netherlands have been active to gain insight into this matter and to build attention to research competence into the curriculum. In addition to this curriculum development, supporting the development of research competence implies demands on teacher trainers. They must possess research competence and serve as inspiring examples (Geerdink 2010, 73) and must be able to transfer research competence. This is more easily accomplished when the learning environment has a culture of research (Van der Linden 2012). An increasing number of teacher trainers have been developing themselves in this field. Many personnel advertisements currently call for teachers with research experience, and researchers are regularly invited to give guest lectures or to assess research. The greatest challenge is to assign teachers, teacher-researchers, research teachers, and researchers in such a way as to ensure balance at both the individual and team level in terms of subject content, teaching competences, and research competence. At the same time, integral attention to research competence is needed in both the curriculum and in vocational preparation.

Professional issues and research competence
Reflecting on the conceptual framework presented thus far, differences in the complexity of issues as described earlier can be related to the various elements of research competence. Consideration of the possibilities of ‘applying research’ can be relevant to any type of issue. The dimensions ‘working from within an inquiring stance’ and ‘conducting research’ nevertheless form a sliding scale that corresponds to the growing complexity of issues, in which explicit research knowledge and competences play an increasingly important role (see also Enthoven & Oostdam 2014).

Transdisciplinary competence

The second type of boundary-crossing qualities in working (together) as educators and researchers on professional issues is the competence to collaborate and engage in mutual learning across theoretical and practical boundaries. This transdisciplinary competence consists primarily of the three elements shown in Figure 2 and summarised in the following:

Figure 2: Elements of transdisciplinary competence
Figure 2: Elements of transdisciplinary competence

Good research?
With regard to educational research (and social sciences in general), a vast amount of methodological textbooks consider the different parts of research processes, such as problem definition, theorising, research planning, data collection, et cetera. All parts should contribute to rigorous research expressed in terms of validity and reliability. However, that which is considered as valid and reliable differs between methodological approaches and is related to epistemological beliefs. Anderson and Herr (1999) have formulated several alternatives for practitioner research and practice-based research in addition to, or in replacement of, existing interpretations of the concept of validity. They distinguish between result validity (the research contributes to the solution of the problem), process validity (the research approach corresponds to the manner of development within the organisation), democratic validity (the stakeholders are involved in the research), catalytic validity (the stakeholders feel that the research provides additional insight for improving practice) and dialogical validity (the research includes sufficient exchange between stakeholders) (Anderson & Herr 1999). These alternatives concern the mutual efforts of researchers and practitioners, as well as research conducted by practitioners. Directly related to this is the usability of the research in the development of professional practices.

In teacher research and practice-based research, both scientific rigour (see above) and interaction are significant and critical dimensions. So, the quality of teacher research and practice-based research is determined by 1) the degree of ‘simply good research‘ (valid and reliable) and 2) the degree of mutual knowledge development in interactive research (Akkerman, Bronkhorst & Zitter 2013; Andriessen 2014; Butter & Verhagen 2014; De Bruijn & Westerhuis 2013; De Jong et al. 2013; Den Boer et al. 2011; Ros & Vermeulen 2011; Ruijters 2016; Teurlings et al. 2011; Van de Ven 2007; Vanassche & Kelchterman 2014). The first aspect is addressed in the above; the second aspect is elaborated on in the following. The consideration and combination of both dimensions is involved in any research, and requires researchers and educators to explain the choices that they have made.

Interactive research
The engagement of researchers and educators in interactive collaboration on research (the second element of transdisciplinary competence) extends from addressing the professional issue up to and including valorisation, all with input in the form of both practical and theoretical knowledge (De Jong et al. 2013; De Jong 2015; Ellström 2008; Gibbons et al. 1994). Practical relevance thus takes on an integral form within this process of mutual knowledge development. This entails a specific responsibility for researchers. They must do more than ‘simply conducting good research’ for scientific relevance. They must also address the issue through dialogue with practitioners, with the goal of developing the practice. This is engaged research, which takes into account its potential effects on the surroundings. It is research whose positive influence on practice is regarded as being of equal importance to its implications for science. Involving educators and other stakeholders in all phases of the research process poses a challenge to the usual standards and criteria for success in scientific research (Edwards 2002; Rickinson, Sebba & Edwards 2011; Van de Ven 2007; Verbeek & Wassink 2014). Besides, as we have seen in the above, these standards are also discussed in such scientific research.

In order to allow interactive research to be useful and contribute to the actual development of practice, teacher-researchers and practice-based researchers should possess the following six qualities. First, they should possess a development-based stance. In other words, they should work from within the ambition and willingness to understand the complex field of practice and to contribute to the development of this practice. Contributing to change calls for researchers to broaden their perspectives beyond issues that are considered important in the field of science to include issues that are important to practice (Schenke 2015). It also implies that they must go beyond collecting information, making diagnoses and proposing remedies, adopting instead a primary focus on increasing the learning capacity of the parties who are raising the issue to be investigated. Schein (2005) refers to this as ‘the role of process consultant’, as distinguished from that of the substantive consultant (expert model or doctor-patient model).

A second quality regarding interactive researchers is that they should be able to clarify issues or topics systematically in collaboration with practitioners, in addition to sharpening them to reveal the core. In this iterative form of issue articulation, they should actively value practical knowledge, a third quality. This calls for researchers to do justice to the complexity of practice and to observe it in a holistic manner, taking various perspectives into account, as well as insights from the various disciplines (Fortuin 2015; Spelt 2015). Researchers should be able to guide practitioners in their efforts to consider the past, present, and future of an issue, as well as its context. They should also help practitioners recognise any ‘problems behind the problem’. For example, what is at hand if a new educational tool does not bring about the expected outcomes? Is the design of the tool inadequate? Is the tool only suited for specific types of students? Is the tool adequate but not being implemented because teachers do not know how to use it or do not actually support the tool? The path of clarification and sharpening to reveal the core (the definition of the professional issue) is an art unto itself. It has characteristics of short-term and long-term research, based on explorations in and with the field of practice, with a short-cyclical character and a continuously-shifting perspective (Butter 2015; Butter & Verhagen 2014; Heikkinen 2014; Schein 2005). As researchers, we possess certain substantive expertise (which is often the reason we are asked), and this acts as a filter on our lens (the theoretical framework). Discoveries in the documentation concerning the issue and in conversations with stakeholders concerning their practical knowledge help us arrive at ideas for delving into certain research literature, probing more deeply into these aspects in subsequent conversations. Such issue-articulating conversations should also include discussion about the extent to which the resolution of the issue that has been defined will actually require research (or follow-up research), or whether other activities might be preferable. In other words, the analyses in the initial phase could lead to the conclusion that something other than research is needed in order to continue the process, thus possibly concluding the collaboration. If it becomes clear that research would be desirable in order to support the development of educational practice, however, the professional issue should be developed into a research question, based on insights from previous research.

Interactive research also imposes demands on the design of the study (De Jong et al. 2013; Gibbons et al. 1994; Rickinson, Sebba & Edwards 2011). For this reason, researchers should have a fourth interactive quality: the quality of designing and conducting studies with practitioners, with an appropriate role for these practitioners that ranges from respondent to sounding board to co-researcher, and from outsider to active participant. Views concerning the distribution of roles between researchers and practitioners will need to be discussed and adjusted repeatedly, against the background of the interaction demanded by the professional issue. Based on the results of his study on collaboration between school managers, teachers, and researchers in research and development projects in secondary schools, Schenke (2015) advocates collaboration from the start (the original professional issue) up to and including the consideration of the implications of the research results for the field of educational practice. Schenke concludes that, in a collaborative project, the boundary practice that emerges and the learning mechanisms that occur are determined by the mutual reasons for collaborating, the division of tasks amongst those involved and the manner of communication. More boundary traffic (e.g. an active data-collection role for educators or the involvement of researchers in considering school development) increases the presence of transformative learning mechanisms. It also increases the likelihood that new routines will emerge in the school (e.g. more teacher inquiry with regard to school development) and amongst the researchers (e.g. more transdisciplinary working methods).

The fifth quality researchers need in interactive research is the ability to provide explicit clarification of research activities, outcomes and returns, both during and after the study. This entails 1) statements concerning the usability of the research for the educational field. Usable research is perceived as relevant, understandable, acceptable, ethical, plausible, legitimate, inspiring, insightful, and applicable. 2) Resolutions for professional issues in the form of guidelines for action and instruments.

Sixth and finally, interactive research involves implementation, innovation and valorisation competence. This concerns the competence of researchers in providing proper guidance to the educational field throughout and following the research, in addition to inspiring educators in the development of new behaviour and the use of new instruments in their professional practices.

Teaching about research
Returning to the three elements of transdisciplinary competence, the third element teaching about research will now be addressed. This element of integrating research and development into education includes supervising the development of research competence, transdisciplinary competence, and the role development of both practitioners and researchers. Teaching can help researchers level with the field of educational practice. It can make them more likely to be accepted, and it can be seen as enhancing the legitimacy of their roles as practitioner-researchers and practice-based researchers. At the same time, researchers who teach could contribute to the development of practice through the process of their teaching. Conducting research with students, giving lectures (or guest lectures), supervising or assessing student research – all of these activities are examples of boundary practices in which research can enhance teaching. According to Visser-Wijnveen (2013), this can occur through 1) the reinforcement of the inquiring stance of students, 2) imparting knowledge to students with regard to a subject area or discipline, 3) helping students become familiar with the phenomenon of research and 4) contributing to the recruitment of research competences in students. Conversely, teaching can enhance research: through input from students, through reflection by researchers on their teaching roles, and through the broadening of the research focus as a result of the specific approach demanded by teaching (Visser-Wijnveen 2013).

Research competence of both researchers and and educators
Reflecting on the concept of research competence in collaborative work on educational issues, everything that applies to researchers in this regard also applies to educators. Learning how to cope with professional issues (including the issue of developing research and transdisciplinary competence) in current practice within the system of higher professional education is one type of ‘jumping in’ for researchers, educators, and students. It is accompanied by a certain amount of interdisciplinary role development for all parties involved, not in a temporary boundary practice between professionals, but as a new interpretation of the role of professionals. Schenke (2015) observes that the development of transdisciplinary competence emerges through active participation in an inquiry-based, transdisciplinary project. The deliberate design of the intensive interaction between researchers and educators can support both the role and process of professional development. In the same vein, the deliberate design of limited boundary traffic can support professional role stability. Fortuin (2015) reaches a similar conclusion in the context of teaching and learning boundary-crossing skills in environmental science education.


This article has presented a developing conceptual framework for a research programme aimed at enhancing our understanding of the course of collaboration between educators and researchers on issues related to learning and development, as well as our understanding of how participants can improve their collaboration. This framework builds on a) snowball-sampled literature, b) the author’s earlier publications and c) discussions with both educators and researchers. The resulting conceptual framework for studying the boundary crossing of educators and researchers working on educational issues forms the basis for the empirical research agenda of the programme initiated.

Three concepts have been discussed. First, the nature of educational issues is relevant to determine the role research can have in clarifying and solving the issue. Relatively simple issues primarily call for professional reflection. Complicated issues mainly need more thorough practitioner inquiry. In complex and persistent issues, explicit research knowledge and competences play an increasingly important role. Collaboration between educators and researchers can help clarify the issue and find solutions. This collaboration calls for specific competences of partipants. In that regard, the second concept of research competence has been further discussed. Educators (and researchers) with research competence 1) think and work from an inquiring stance, 2) utilise existing research 3) conduct research themselves and 4) supervise the development of the research competence of students. The third and final concept is transdisciplinary competence. Researchers (and educators) with this competence 1) conduct good research, 2) engage in interactive collaboration on research, and 3) teach about research.

Discussion and topics for further research

It is argued that both researchers and educators need research competence and transdisciplinary competence for crossing their ‘own’ boundaries in a new culture of collaboration on educational issues. These two concepts enhance our understanding of the course of collaboration between practitioners and researchers on professional issues. They also enhance our understanding of balancing the roles of both practitioner and researcher, for example as a teacher-researcher. The framework suggests that collaboration and high boundary-crossing competences result in better understanding and solving educational issues. However, empirical research is required to validate these concepts, their interplay and revenues. It may be argued that preferred contexts to proceed in investigating boundary-crossing collaboration on educational issues should be the ones in which research, educational degree programmes and the vocational field converge, as well as those in which Mode 2 and the ETI perspective are (or can be) addressed. How do participants interact? What roles do they take? What do they learn? However, other contexts are equally important to address when testing the framework. For example, if research competence and transdisciplinary competence are low, it could be stated that sufficient ground for interactive research is lacking and that it would be more appropriate to choose a more traditional RDD-configuration. Different kinds of dialogical activities in boundary crossing (e.g. Akkerman & Bakker 2011, 2012 bring up identification, coordination, reflection, and transformation as learning mechanisms) could demand different types of competences. Thinking about this, one could say that developing research and transdisciplinary competence enlarges the range of dialogical activities and learning mechanisms that are possible in interaction.

In constructing an empirical research agenda, several other options can also be mentioned. Building on the elaboration of the concept of research competence with the aim of envisioning challenges in working on educational issues, questions for empirical research include the following: How do practitioners, researchers, and students view the components of research competence? How are these components interrelated? How does research competence relate to other qualities of practitioners? What does working in the field of education (student learning, team functioning) demand with regard to the research competence of teachers? What does their research competence contribute, and to whom or to what (for example, students, themselves, their teams, further education, the vocational field, society), and what exactly does this contribution entail? What are the conditions for developing and using research competence?

Building on the elaboration of transdisciplinary competence, questions for empirical research include the following: What views do researchers have concerning practitioner research and practice-based research? What do practitioners think of this? How do practitioner-researchers and practice-based researchers realise their roles; what conditions are addressed, and what benefits do they realise? To what extent, on what points, and in what way do researchers want to develop themselves in their roles? What do practitioners perceive that researchers need with regard to role development?

Another research topic is the role of teacher leaders (educators who supervise teams in the inquiry-based and systematic improvement of educational quality) and what is needed to equip them for this role. Studies on innovation projects in the field of education have indicated that inquiry-based learning and practitioner inquiry are currently not being addressed to any great extent (Den Boer & Teurlings 2014; Van den Berg 2013). There is evidence of a positive relationship between the research competence of educators and the quality of education, although the available research on this point remains relatively sketchy and fragmented (for example, see Imants 2010; Ros et al. 2013; Snoek 2014; Van den Berg et al. 2011). Teachers who are involved in practitioner inquiry could serve as inquiring, transdisciplinary educator-leaders in their teams, largely by contributing to the process of mutual working and learning for the purpose of quality improvement (see, for example, Castelijns, Koster & Vermeulen 2009; Verbiest 2012; Verbiest 2014). Results from a study by Van den Bergh and Ros (2015) in Dutch training schools for the university for teacher education reveal that not every school manager is aware that research constitutes an important part of any Master’s programme. The positioning of Master’s-level teachers (and teachers-in-training) at both the school and supra-school levels could be improved through actions such as having them lead research groups (with supervision by an experienced researcher or teacher-researcher). In addition to research competence, teacher leaders should possess team and leadership qualities, including a belief in their own competences, as well as those of the team. Formal and informal recognition for teacher leaders, the willingness to engage in mutual practitioner inquiry within teams, a clear vision on the management of practitioner inquiry, and a culture of inquiry within schools are indispensable to the successful introduction of practitioner inquiry, as directed towards the quality of education (Krüger 2010; Snoek 2014; Van den Bergh & Ros 2015; Van der Zwaard 2014).

Whatever the choices made in further research on research and transdisciplinary competence, it would be counterproductive to make these without addressing professional issues and taking the ownership of practitioners and other stakeholders into account.

This article is adapted from Van den Berg (2016).


Dr Niek van den Berg, Professor of Applied Sciences, Aeres Wageningen University of Applied Sciences (Netherlands), n.van.den.berg(at)

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Imagined future – elements of a good first-year student experience


Perceptions of the goals, objectives and tools of work have changed. It has been estimated that the transformation of working life which is going on today will equal in magnitude the changes brought about by the industrial revolution. This means that we should assume a completely new approach to work and education on all levels. The efficiency of work and work performance used to be largely dependent on the traditional structures of industrial work; the workplace, colleagues, supervisors, clients and their needs, working hours, organizations, products and services were all stable and predictable. These days, however, the transformation of work and the pressures for organizational change mean it is no longer possible to rely on these structures. Increasing unpredictability and complexity in the operating environment have become the norm. (Järvensivu, Kokkinen, Kasvio & Viluksela 2014.)

This trend is also having an impact on higher education.  Our traditional views of efficient operating models, good practices and guidelines for the delivery of higher education are all being challenged. There have been calls for closer linkages between higher education and the world of work, in order to increase the relevance of the curriculum to working life (Singh & Little 2011, 38). So, the resources of higher education institutions have come under intense pressure; they should provide quality learning and teaching, making effective use of technology, while being responsive to the increased expectations and conflicting demands of a student body with ever more diverse needs (Morgan 2012, 10).

The increasing costs of delivering higher education, reductions in state funding and constraints on resources mean that delivering high quality student experience is challenging. Staff at all levels and across all areas within an institution affect the student experience. In order to be effective, services, advice, guidance and support for students must be organized holistically rather than provided only by dedicated central services (e.g. student services departments, students’ unions).  Providing guidance and support only to specific groups (e.g. dyslexic, mature, or disabled students, or those with weak entry qualifications) should be avoided.  It is also unrealistic to expect students to seek out support themselves. (Morgan 2012, 11.)

Student experience has been studied extensively mainly from the point of view of the students. This is natural, of course, but it is important to find out the viewpoints of other groups, too, such as teachers and other staff members. Teachers are key figures regarding student experience as they create the framework for action in the context of the curriculum. Williams (2011, 46.) points out that other categories of staff, such as those responsible for delivering student support services, are often the invisible support function within higher education institutions. Yet they are of vital importance to the student experience. They are also important to the teaching function.

This research examines the premises for a good student experience for people in their first year of studies. The research was conducted in one university of applied sciences and the key aim was to provide insight into and understanding of the factors affecting student experience. The research question is: What elements are important for a good first year experience in a university of applied sciences, according to students, teachers and other staff members?

The concept of student experience

Higher education is at a crossroads. The development of competencies required both for studying and in working life has become the personal project of each individual student. (Stelter 2014.) Students expect and demand support, advice and guidance which meet their individual needs. This cannot be provided with a “one size fits all” approach to education. (Morgan 2012).

The idea of student experience as an issue to be managed institutionally is a relatively recent one and the term has multiple meanings.  First, it is important to emphasise that each student’s set of experiences will be unique to him or herself. Thus any uniform “student experience” does not exist in practice. (Temple, Callender, Grove, Kersh 2014; Morgan 2012.)  As Forbes (2009) explains, student experience can be defined narrowly or broadly.  In a narrow definition the focus is on students’ formal learning experiences and their overall experience of university life. A wider definition covers their entire engagement with the university from initial contact, through recruitment, arrival, learning and university experience, graduation, employment, and their experiences as alumni. In addition, there are matters that the institutions are not directly responsible for, but generally have some involvement in. These include students’ living arrangements, accommodation, safety and security, part-time work, and social inclusion.

According to Benckendorff, Ruhanen & Scott (2009), the factors identified in the literature as influencing the student experience can be grouped broadly into four dimensions: Institutional dimensions (how universities and staff can better manage the learning experience), student dimensions (individual student characteristics), sector-wide dimensions (broader systems of institutions and trends that emerge as a result of competition or collaboration) and external dimensions (factors such as government policies, technological innovations, and economic pressures).

Harvey, Burrows and Green (1992, 1) argue that student experience is the most important factor in assessing quality in higher education. They use the expression “total student experience”, indicating that significant experiences are not restricted to the classroom. Internationally, the term “student experience” is used to refer not only to the teaching, learning and curriculum aspects of student life, but also encompasses extracurricular activities, academic advice, support and mentoring, as well as work experiences and student lifestyle (Purdue University 2004).

The recent interest in students’ experiences may also be associated with changing conceptions of learning and curricula. Emphasizing students’ agency, activity and participation means that experiences have to be taken into account when designing the curriculum (Barnett & Coate 2010). Thomas (2012) argues that students’ experience of the curriculum has a profound influence on their persistence and success in studies. Curricula can be designed and delivered in a way that promotes students’ engagement and sense of belonging, and reduces drop-out rates.

The term “student experience” has come to be used so widely that it is important to consider critical viewpoints, too.  Student experience is sometimes treated as analogous to customer experience – as a marketing term.  As students are seen as ”customers” or “clients”, their ”experience” becomes a factor that must be managed and optimized, as for any other “target group”.  However, Staddon and Standish (2012) have challenged the idea of “student-as-customer”. In their view, seeing students’ choices as determinants of quality is an abrogation of responsibility on the part of higher education providers. Furthermore, Gibbs (2012,14) argues that evidence is lacking as to whether there is any causal relationship between good student satisfaction scores – suggesting satisfied ‘customers’– and educational quality as assessed by measures such as student performance and learning gain.

The student experience arises not only from the engagement of students with learning and teaching, but also include other aspects that impinge on learning and studying. Since students’ experiences are shaped through interaction with the whole institution, it is important to know what elements are significant in creating a good experience. Therefore, in this study an interaction- and institution-based definition of student experience is used. Student experience can be defined as the totality of a student’s interaction with the institution (Temple, Callender, Grove & Kersh 2014).

Students’ engagement and expectations

Students’ engagement has become the focus of a great deal of research. Students’ expectations and their experience during their first year of studies have a tangible influence on student engagement and persistence – that is, the probability that they will complete their studies (Longden 2006). Singh and Little (2011, 36) argue that within discourses concerning pressures on higher education, the economic point of view tends to dominate; less emphasis is placed on the implications that various changes have for teaching and learning and for non-economic dimensions of social engagement. Instead of assessing students’ engagement in their studies from an economic point of view, the benefits of engagement should be seen in terms of better learning outcomes (Millard, Bartholomew, Brand & Nygaard 2013).

Definitions of student engagement vary somewhat depending on the theoretical framework used. An individual-constructive perspective focuses on the time and quality of effort that students devote to educationally purposeful activities (e.g. Astin 1993; Pascarella & Terenzini 1991). For instance, their level of motivation and willingness (Ainley 2006; Purnell, McCarthy & McLeod 2010). The interactional perspective emphasizes that personal investment, by both students and university staff, is the key to engagement (Kuh 2009). In this view, it is important for institutions to adapt their organizational structures and cultures to enable students to be part of learning communities (Zhao & Kuh 2004). Sociocultural engagement theory (Haworth & Conrad 1997) underlines that students and staff ought to engage in a mutually-supportive academic community, building a participatory and dialogical educational environment. Engagement is enhanced by a participatory culture, interactive teaching and learning, connected programme requirements, and adequate resources. (Annala, Mäkinen, Svärd, Silius & Miilumäki 2012.)

Coates (2007) has described four different engagement styles: intense, passive, collaborative and independent.   Intense and passive come at opposite ends of a continuum covering engagement styles from engaged to disengaged.  The collaborative style favors social aspects of university work, while the independent style is characterized by a more academically and less socially oriented approach. These two latter styles point out the multidimensionality of engagement: a student may emphasize social aspects and turn the focus from studies to social life or vice versa, he or she may be very engaged in studies but neither socially active nor interested in communality with peers. (Annala & al. 2012.)

Turning to the question of student expectations, research suggests that the standard practices of higher education institutions do not necessarily align with what students want and expect.  Teachers and providers of student services may make erroneous assumptions about students’ needs and expectations because higher education institutions tend to provide information to students based on the institutions’ expectations, not those of the student (Pithers & Holland 2006). Thus, there may be a significant gap between the students’ expectations and their actual experiences during the first year of their studies. According to Telford and Masson (2005), the perceived quality of the educational service depends on students’ expectations and values. If teachers and other staff know what their students expect, they may be able to adapt their behavior and services accordingly, which should have a positive impact on students’ levels of satisfaction. (Voss, Gruber & Szmigin 2007.)

Today’s student body is highly diverse, comprising members of the “Baby-boomer” generation (born mid-1940s to mid-1960s), “Generation X” (born mid-1960s to early 1980s) and the “Millennial” generation (born early 1980s to 2000). These generations tend to have different expectations and life experiences, and different skills in using and understanding technology.  This diversity creates challenges for higher education institutions. Morgan (2012, 9) gives examples of how tensions can arise between students and also between students and lecturers and other staff members. A Generation X student may feel that Millennial students are not as engaged in group project work or as committed to their studies as they should be.  A Baby Boomer student who has worked in business for many years may feel that he or she is much more qualified to teach than a lecturer who has little – if any – experience in running a company.

With the increase in student diversity, the probability of drop-out, i.e. failure to complete the study programme, rises.  When a student drops out, there are usually a number of causal factors behind it.  Each student’s personality, life experience, study experience and future plans will all affect his or her level of engagement. (Morgan 2012, 9-10.) Thomas and May (2011) argue that if students are able to engage with their peers, teaching staff, other staff at the institution, and with the institution per se, then they are more likely to experience a sense of belonging to and identity with the institution.

Identity work – the process of becoming

New interpretations of student engagement in studies emphasize the importance of identity construction and communities of practice (Krause & Coates 2008; Millard, Bartholomew, Brand & Nygaard 2013; Wenger 1998). Thus learning to become a professional involves not only what we know and do, but also who we are, and who we are becoming (Dall’Alba, 2009). Cognitive elements and acquiring of new skills are only part of the process of becoming a professional – albeit an important part. Emotive issues are of crucial importance in identity construction. Learning is both affective and cognitive, and involves identity shifts which can entail troublesome, unsafe journeys (Cousin 2006).

Beijaard, Verloop and Vermunt (2000, 750) define identity as who or what someone is, the various meanings people attach to themselves, or the meanings attributed to them by others. An essential point is that each individual has not just one identity but many; these multiple identities are changing over time and are revealed in interaction.  Identity is formed and constructed by narratives (Rodgers & Scott 2008). Thus, professional identity is not a fixed state which can be achieved during one’s studies, but is rather a continuing dynamic process of intersubjective discourses, experiences, and emotions. Beijaard, Meijer and Verloop (2004, 108) consider identity to be an ongoing process of interpreting one’s self as a certain kind of person and being recognized as such in a given context. Identity can be seen as an answer to the recurrent question, “Who am I at this moment?”

Identity construction requires a conception of where one is coming from and going to (Taylor 1989). It is thus essential that students have some vision of their future in order to engage in their studies. Having a clear image of what might lie ahead is important for decreasing uncertainty. Markus and Nurius (1986) use the expression “possible selves” to describe individuals’ ideas of what they believe they can become. These possible selves form the basis for evaluating one’s current selves and motivating action. “Possible future” is a term used in socio-dynamic counselling. It suggests that the future is not a predetermined state, just lying in wait around the corner, but is created and constructed through human action. What we think about our future affects what we do today. (Peavy 2006.) Thus students who can imagine their future as professionals in a particular field are likely to be more highly motivated and to have a clearer idea of what they still need to learn.

Gadamer’s (1979) conception of two kinds of experiences can be used to illustrate the connections between students’ experience, engagement and identity work. There are experiences which strengthen personal conceptions, and there are new, hermeneutic experiences. People need experiences that strengthen their conceptions but they do not learn anything new from experiences of this kind.  Hermeneutic experiences, on the other hand, include something new and unexpected, something we have not thought about before. Hermeneutic experiences are uncomfortable, as they disrupt our typical way of seeing and understanding matters. These experiences feel unpleasant and painful, as they challenge our conception of ourselves and of our personal competence and knowledge. These negative experiences, however, make identity work productive by enabling us to see and understand matters in a different way. It is therefore crucial to present students with hermeneutic experiences, as through these experiences they gain new insight into the demands of working life, and start to see themselves in a new light – as “becoming professionals”.

 Two important pedagogical concepts are particularly relevant to this discussion of promoting identity work, namely, the zone of proximal development, and scaffolding. The zone of proximal development is defined as the range of tasks that a person can perform with the help and guidance of others, but cannot yet perform independently. It is the area where the most sensitive instruction or guidance should occur. (Vygotsky 1986.) Scaffolding is directly related to the zone of proximal development in that it is the support mechanism that helps a learner successfully perform a task within his or her zone of proximal development. Typically, this process is completed by a more competent individual as a way of supporting the learning of a less competent individual. Scaffolding is a key strategy in cognitive apprenticeship, in which students can learn by taking increasing responsibility and ownership for their role in complex problem solving. (Collins, Brown, & Newman 1989). So, for example, there could be a teacher assisting a student, or a higher-level or more competent student assisting a peer. By using scaffolding, the teacher becomes more of a facilitator of knowledge acquisition on the part of the learner rather than the dominant source of knowledge and expertise.

Identity is not a fixed state which can be attained during one’s studies. Constantly changing environments and new competence criteria in working life require flexibility to construct one’s own identity over and over again. Enabling contacts with working life during the studies is vital, because it allows students to adopt role models and to participate in professional discussions; it exposes them to influences from professionals in their own field of practice, and provides them with material for reflection on their own professional identity (Adams, Hean, Sturgis & Macleod Clark 2006; Kärnä 2015, 84). Identity functions as a basis for the interpretations the student makes of him- or herself – as a learner, as a member of different groups, and as a prospective professional. Thus identity is the basis for all one’s possible selves (Markus & Nurius 1986) and images of the possible future (Peavy 2006), too. According to Tsang (2010), having the opportunity to conduct identity work during the studies enhances learning experiences and leads to a positive and more clearly defined professional identity.

Method – imagining the future

Organizations evolve in whatever direction their members ask questions about. The basic assumptions for the methodology of this study arise from Cooperrider’s (1995) argument that we need forms of inquiry that are generative: which help us to discover what could be, rather than try to fix what is. Human systems project ahead of themselves a “horizon of expectation” that brings the future into the present. What we believe to be true determines what we do, and what we do today is guided by our image of the future. (Cooperrider & Whitney 2005; Peavy 2006.) Organizational life is expressed in the stories people tell each other every day, so the story of the organization is constantly being co-authored. The purpose of inquiry is to stimulate new ideas, stories and images that generate new possibilities for action. By inquiring into human systems we can change them. (Cooperrider & Whitney 2005; Kessler 2013.)

In this research, instead of only asking students about their experiences retrospectively, a more comprehensive and future-oriented perspective on first-year experience was used. It can be called imagining or envisioning the future. It can be loosely connected to one stage in the so-called “cycle of appreciative inquiry”. In the “dreaming” or “envisioning” stage of appreciative inquiry, the participants are asked to imagine their group, organization or community at its best in relation to the affirmative topic. The purpose is to identify the common aspirations of system members. (Kessler 2013.) Taking this for a starting point, a group of second-year students (n = 121) and a group of personnel (teachers and other staff, n = 523) were asked to imagine the desirable future by reflecting on the question: What would the students tell about their first-year experience if everything had been ideal in our university of applied sciences? The data was produced in small group discussions in order to share existing stories and create new ones about matters associated with good first-year experience. The discussions were documented by each group, either in a discussion area in the intranet of the university of applied sciences, or on flip charts. In total the data comprised 25 pages (font Times New Roman 12).

The data was analyzed in a three-stage process based on content analytical approach. The methods of qualitative content analysis should not simply be techniques to be employed anywhere but the methods must be adapted to suit the individual study (Mayring 2014, 40). Therefore, a three stage process was created for the analysis. Firstly, the data was read many times, in order to identify different expressions, sentences and key words relating to a desirable future state i.e. what the students would tell if everything had been ideal. Figuratively speaking, the data was asked what kind of things belong to an ideal university of applied sciences. Gradually, three categories were identified: the psycho-social point of view, the material point of view, and the pedagogical point of view into a good university of applied sciences. Secondly, the expressions belonging to these three categories were moulded into the form of short narratives in order to create a meaningful, explicit and coherent whole from partly short and fragmental utterances.

During these two stages of analysis the student data and the personnel data were analyzed separately. Therefore, after the second stage, there were two collections of narratives: those constructed from the students’ descriptions and those constructed from the descriptions provided by the teachers and other staff. However, the purpose of the study was not to search for differences in students’ and personnel’s conceptions, but to find common prospects.  Therefore, the analysis was proceeded and in the last stage of the analysis common elements for a good first-year experience were identified from both sets of narratives. This was done by identifying similarities in the three categories – psycho-social point of view, material point of view, and pedagogical point of view – relating to students’ identity construction, professional growth, participation, sense of belonging and engagement. On the grounds of this comparison five elements for a good first-year experience was identified.

Findings – Basic elements for a good first-year experience

In a university of applied sciences, a good student experience is associated with practices, situations and events which affect students’ learning and well-being. In the data-production discussions, the students, teachers and other staff brought out themes related to the psycho-social environment, the material environment and the pedagogical environment. On the basis of the research material, five elements for a good first-year experience were identified: personalization, mentoring-guidance, authenticity, collaboration and adaptability. These elements can be understood as a basis for promoting students’ agency, participation, sense of belonging, and engagement in their studies, and thus for supporting students’ identity construction and professional growth. It is important to point out that the five elements of a good first-year experience are not distinct from each other but overlap; changes in one element resonate throughout the others. However, this kind of theoretical separation helps when it comes to applying them for the purposes of assessing and developing the prevailing practices and systems.  In the following description of each element there is a short example from the narratives to illustrate the features of the element concerned. The question the participants were asked to reflect on was: What would the students tell about their first-year experience if everything had been ideal in our university of applied sciences?

a) Personalization

Studying has changed my life – my aims are more ambitious than before. I have grown as a human being and have got new perspectives. I have found my own strengths and possibilities and I know what I want from the future. I already have enough professional pride to take responsibility for my own choices and also for the choices we make in team-work. In our school, students can follow their own interests and develop their ideas further. You can choose what you study, make your own timetable and even choose the teachers you want to work with. There are lots of study modules to select from, and each student’s timetable is tailored on the basis of individual choices and plans.

Personalization included many kinds of action which allows individual decisions. Studying was seen as a personal project and during the process the student start to recognize his or her own capacity. Learning to become a professional involves not only new knowledge and new skills, but also personal growth and new perspectives to oneself. Students can make choices and influence their own study paths Learning is tailored to the individual needs of each learner. This kind of personalization of studies can take many forms, including accreditation of prior learning and “studification of work”. Studification of work is a new, alternative way to study at universities of applied sciences.  It is a model of studying where learning is brought from the classroom to the workplace and formal studies are combined with work.

Prahalad & Ramaswamy (2000) make a distinction between personalization and customization. Customization assumes that the manufacturer will design a product to suit a customer’s needs. Personalization, on the other hand, is about customers, i.e. students in this case, becoming co-creators of the content of their experiences. Personalization includes tailoring of content and action to the individual student’s frame of reference, and enables students to have personal learning paths that encourage them to set and manage their individual goals. This does not mean that individual students are separated from each other (see the fourth element: collaboration).

The main thing in personalization is that it strengthens the student’s engagement by increasing psychological ownership (Pierce, Kostova, & Dirks, 2003, 86) Psychological ownership is a cognitive-affective state in which students feel a sense of ownership in the process of studying. They have a positive attitude towards studying, a realistic self-concept, and a sense of responsibility for the results and outcomes. This sense of possession (the feeling that the learning objectives or assignments are ‘mine’ or ‘ours’) promotes engagement in the processes of studying and learning, and facilitates identity work. The emergence and development of ownership is supported by letting students have a greater say in their own learning activities, and in how they deal with assignments which require complex action, thinking and planning.

In working life, work is supervised to an increasing extent by employees themselves, involving negotiations in various communities. Supervisory and managerial responsibilities are also in motion, and are not permanently associated with specific people. (Järvensivu & al. 2014.) In complicated assignments, employees have to exercise autonomy and use their own discretion; the choices they make are heavily influenced by their work-identity or professional identity (Pierce, Jussila & Cummings 2009.) Similarly, learning assignments which are too carefully preplanned by the teacher do not necessarily support the development and maintenance of ownership. Putting the onus on students to formulate their own goals and assignments is the basis for the use of scaffolding.

b) Mentoring-guidance

I have the feeling that studying here is meaningful for my life. My own field of study seems worthwhile and my perspectives and goals have become more explicit and clear. Even my professional identity has strengthened. I feel that the staff are really there for you. The teachers and other staff are kind, human and approachable – not like robots. Individual guidance is much more available than ever before; I have never felt lonely or abandoned at any time during my studies.

The atmosphere is really good, democratic and tolerant. The students are treated as adults and the teachers appreciate the students. I feel secure, knowing that I can get help whenever I need it.

Successful mentoring-guidance requires mutual respect, listening, encouragement, dialogue and emotional sensitivity. Teachers, other staff members and representatives of working life can encourage students’ engagement in their own learning and performance improvement by guiding students in planning their own learning and studying. Personal meaning-making will be emphasized in constructing positive future scenarios. The goal in mentoring-guidance is that, within a dialogical environment and participatory culture, students become aware of themselves and their own potential.

What does it mean to you to become a professional in your own field? That is a question every student should have time and opportunity to consider and discuss. The role transition from student to employee in working life may happen quickly, but identity work needs time and support. Identity construction, i.e. the person’s conception of who he or she is and where he or she belongs, requires a conception of where he or she is coming from and going to (Taylor 1989). Students must have a future vision in order to engage in their studies and form their own professional identity.

Meaning-making is at the core of mentoring-guidance. Meaning is formed on the basis of experience, reflection, speech and action.  It is based on previous experiences and expectations of the future, and is a holistic way of integrating past and present experiences, together with ideas about what the future holds (Stelter 2014). Mentoring-guidance helps to regulate the development of competencies and supports the learner’s ability to apply skills, knowledge and experience to new situations and processes (Michael 2008). It is a form of dialogue where participants focus on creating space for reflection through collaborative practices. The target is to encourage students’ goal-orientation, and engagement in their own learning and performance improvement. Parsloe (1992) argues that the function of mentoring is to help and support people to manage their own learning in order to maximize their potential, develop their skills, improve their performance, and become the person they want to be. This applies to mentoring-guidance too.

c) Authenticity

Individuality and diversity as well as differences between students are respected. I have been treated with respect – as myself. People here are truly interested in your learning and your future.  The goals of every study module are directed towards working life. Already during the first year you can participate in development projects together with students from other fields of study and representatives of working life. We carry out activities in which you can learn and practice work-life skills in real situations with real customers and professionals.

Authenticity was connected both to learning environments and to the quality of interaction.  Working in real projects with representatives of working life was seen as essential part of learning.  One important aspect in authenticity was that students are not only defined by their institutional role as students, but their personal and individual needs, situations and goals are also taken into account.

Authenticity is a complex and multidimensional phenomenon.  No single unanimous definition of authenticity exists, but core elements of its meaning are being “real” or “genuine”.  For the purposes of this study, three definitions by Kreber are worth mentioning.  First, authenticity as being true to oneself means not being defined by others but using self-knowledge to establish one’s own identity. Another view of authenticity – acting in the interests of learners – means that teachers and other members of staff care about their students and want them to succeed. The third definition refers to transformation, or the process of becoming. In this view, authenticity develops via a process that involves ongoing critical reflection. Transformative learning goes beyond changing what students know – it can change who they are. (Kreber 2010.)

In higher education, the terms “authenticity” and “authentic” are usually associated with real-life situations, environments and tasks which are exploited in some way for learning purposes.  However, authenticity occurs not in the learner, the task, or the environment, but in the dynamic interactions among all of these. It is cognitive authenticity rather than physical authenticity that is of prime importance in the design of authentic learning environments. (Barab, Squire & Dueber 2000; Herrington, Oliver & Reeves 2003). Authenticity enables learners to engage in activities which present the same type of cognitive challenges as those in the real world (Honebein, Duffy & Fishman, 1993). Working with tasks and problems which replicate the particular activity structures of a context enhances transferability and application of theoretical knowledge to the “real world”. Along with technical procedures, students should be learning the schema through which professionals recognize and solve problems. Expert thinking involves the ability to identify and solve problems for which there is no routine solution. According to employers, the most important skills in new hires include teamwork, critical thinking/reasoning, assembling/organizing information, and innovative thinking/creativity. (Hart 2006.)

Authenticity can also simply mean that something is personally relevant or interesting to the learner (Jonassen 1999). Authentic problems engage learners because they represent a meaningful challenge to them. Thus authenticity goes hand in hand with the drive for student engagement and partnership. Authenticity can be enhanced by helping the students to recognize their own starting points, thinking, action and prior knowledge, supporting them to formulate their own learning objectives, and encouraging them to reflect on issues concerning theory and practice.

d) Collaboration

The students work in small groups or teams (not too big) – both within the institution and together with representatives of work life. There is a lot of project-based learning in co-operation with work life. Student counselling functions very well.  The students’ union is active and constantly develops new kinds of ways to influence the practices within the organization. Students, teachers and other staff know each other, which is a good basis for co-operation. ICT is widely used in teaching and teamwork and communication with regional, national and international partners.

The principle of collaboration includes any kind of action that is done with the student or for the student. Thus, one-on-one encounters, group or team discussions, co-operation between different fields of study, services and departments are all encompassed within this concept. In addition, collaboration included networking with representatives of working life and regional policy-makers, and web-based participation in nationwide and global discussions.  Digitalization, social media and mobile technology was seen as essential tools of communication which are opening up new opportunities for agile interaction. Furthermore, these tools enable technical scaffolding, such as web links, online tutorials, or help pages, for the guidance of students (Yelland & Masters, 2007).

Collaboration entails working together toward a common goal. Students invest in their own learning and take responsibility as team members (see also psychological ownership). Learners use a variety of research tools (digital and mobile) as they actively participate in different projects, working not only with internal partners but also with representatives of working life.

Collaboration is a process in which individuals negotiate and share meanings relevant to the problem-solving task at hand. (Roschelle & Teasley 1995). In working life, employees are increasingly organizing their work flexibly among themselves. Work is flexibly reorganized, rescheduled and replanned in response to changing situations and needs. (Järvensivu & al. 2014.) These flexible working skills can be practiced during the studies. Collaboration is a coordinated activity that is the result of a sustained attempt to construct and maintain a shared conception of a problem. This enables, for example, role-switching, where teachers/practitioners become learners at times, and learners sometimes teach. Collaboration can be seen both as a way of studying together and a way of creating knowledge.

The use of new devices for communication are an essential element in collaboration. However, students’ ability to exploit mobile devices and other emergent technologies as effective study tools cannot be assumed; this issue requires deliberate attention. Furthermore, personal factors such as students’ prior knowledge and their metacognitive and collaborative skills, as well as contextual cues such as cultural compatibility and instructional methods, influence student engagement. (Laru 2012.)

e) Adaptability

Accreditation of prior learning and work experience enable students to make individual study plans and study paths. I didn’t have to study the same things I had already studied before. It is possible to study and learn new, interesting and useful skills or shorten the studying time and move earlier into work life. This kind of possibility increases motivation. It is possible to affect your learning environment, teaching, the spaces you work in and the equipment you use. Bureaucracy is very low and even administrative matters work well. Unexpected changes in a student’s life situation are understood and accepted. Plans are flexible and they can be reorganized.

 Adaptability was understood as a multilevel phenomenon. On a personal level and group level, adaptability refers to the ability to take on new challenges at short notice, and to deal with changing priorities and workloads. On an organizational level – both in educational and work-life settings – adaptability means the capacity to modify plans, curricula and organizational structures to meet changing demands in different situations.  An essential feature of adaptability is the creation of learning spaces that are flexible and plastic while supporting the teaching and learning processes. Adaptability – like personalization – includes tailoring of content and study processes to the individual student’s frame of reference.

Adaptability can be defined as the capacity to deal with new, changing, and/or uncertain situations (Martin 2010). Thus, adaptability can be understood as a mindset, a way of thinking or a habitual attitude. This kind of flexibility is one of the key competencies in working life. Järvensivu & al. (2014) argue that when today’s students enter the workforce, they will need to cope with complex environments, production networks and online work communities.  They will face chaotic situations, demanding high-level management – and self-management – skills.  This will require a capacity for continuous shared learning in response to the changes in the work environment.   From the educational and vocational viewpoint, the changes in working life present enormous challenges, particularly for the improvement and up-dating of competencies.

Discussion and conclusions

The focus of this study was on inquiring into first-year student experience; the research question was: What elements are important for a good first year experience in a university of applied sciences, according to students, teachers and other staff members?  Higher education ought to equip students to enhance their capacity to adapt and manage an unknown future. The five elements of a good first-year experience identified from the data – personalization, mentoring-guidance, authenticity, collaboration and adaptability – can be seen as guidelines for supporting students’ identity work and professional growth, and for promoting their acquisition of the competencies needed in working life. These guidelines could serve as an example of how curricula can be linked to world of work (c.f. Singh & Little 2011, 38). Beijaard & al (2004) emphasize that identity is an ongoing process. Thus identity work continues even if the student has finished his/her studies.

The results of this study are significant in that they give voice both to the students and to the personnel by allowing them to specify the elements of good student experience. The results highlight the importance of student agency, responsibility, and participation in decision-making. Students, teachers and other staff should have opportunities to engage in mutually-supportive communities, and contribute to building a participatory and dialogical learning, teaching and working environment. The five basic elements help us to understand how to enhance engagement in the processes of studying, what is important in interaction, and what should be taken into account in executing plans and processes. These elements can be applied in any discipline or field of study, at any stage of the student journey, and in the whole range of student services.  By providing opportunities for every party – students, teachers and other categories of staff – to articulate their opinions, constructive dialogue becomes possible, enabling progress towards a more positive alignment between student expectations and their actual experience (c.f. Morgan 2012, 10).  This in turn will raise levels of student satisfaction.   According to Williams (2011, 46) for example the experience and knowledge of people working in student support services is usually not utilized enough. A future-oriented and positive approach is needed in order to identify, acknowledge and reflect on daily practices, and ultimately determine what action should be taken if some of the basic elements are being neglected.

The findings of this study provide strong justification for practices which enable students’ agency and participation, and give students responsibility. Further research is needed in order to work out how these five basic elements can be implemented in practice, and to analyze what impact they have on students’ experiences. Answers to these questions should be sought in collaboration with students, teachers, other categories of staff, and representatives of working life.  As times, places and tools for work are all in flux, so the times, places and tools for learning, teaching and education have also been reconsidered. It is important to consult the people working with the students during their practical training periods and in projects, and to involve them in investigating what the broader conditions are that maintain particular ways of thinking, acting and relating, in the context of supporting professional growth. Collaboration between employees in universities of applied sciences and workplaces should be enhanced in order to create a common understanding of the ways to support students in their identity work, and to facilitate their acquisition of the competencies needed to meet the demands of working life in its current state of change. The implementation of these elements could help students to endure uncertainty and hermeneutic experiences (c.f. Gadamer 1979) and their orientation to their own zones of proximal development (c.f. Vygotsky 1986).

This study was carried out in a university of applied sciences. As the five basic elements of a good first-year experience are not related to any particular subject or field of study, they can be applied in many kinds of institutions and in all manner of situations where learning, professional development and identity construction are a high priority. They can be applied even in work-life organizations for assessing current practices and organizational culture. In educational institutions, teachers and other categories of staff can use them in planning, assessing and developing their work.  Work communities can use them for assessing learning environments and making the working culture more collaborative in nature.  Students can use them when planning their studies, and representatives of working life can use them for developing new ways of supporting students’ learning in project work and in practical training settings.

It is important that the five basic elements identified in this study should be applied not only during the time spent in the institution, but also during the practical training periods in work-places, and in other situations involving cooperation with companies and representatives of working life.  The five elements give a good basis for building a participatory culture where students, teachers, other staff members and representatives of working life engage mutually in creating dialogical learning environments (c.f. Haworth & Conrad 1997; Annala & al. 2012). This would provide a good basis for enabling students to become competent partners for research and development projects, and valued employees who are capable of developing their organizations and work communities.


Harri Kukkonen, PhD, MSocSc, Principal lecturer, Tampere University of Applied Sciences, harri.kukkonen(at)

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Supporting Communication between Stakeholders Involved in Industrial Doctoral Projects by a Process Steering Instrument


Industrial doctoral projects are defined as projects that promote knowledge transfer between universities and commercial organisations and nurture innovation. These projects are founded on needs identified within business organisations and researchers from related research areas. The projects last approximately five years in Sweden[1]. A typical project involves a doctoral student and stakeholders from academia and industry who have different priorities and areas of expertise. The project is usually co-financed by research funding agencies, often within the framework of larger research projects, research environments or schools. Unfortunately, many projects of this nature are interrupted, take an unnecessarily long time to reach their objectives or do not meet all the stakeholders’ requirements.

The characteristics of an industrial doctoral projects are seldom taken into account in the assessments, rules and regulations for doctoral projects. The traditional goal of the doctoral programme and thesis is to demonstrate the candidate’s ability to conduct independent research on a novel concept and to communicate the results in an accessible way (Gould, 2016: p 27). In terms of knowledge, skills and competences, this overall aim can be formulated somewhat differently depending on the university and the programme, and does not include applicability to a specific context. While research applicability is requested for all doctoral theses (see e.g. Norell Bergendahl et al., 2004; Nature Editorial, 2016), the value of a doctoral project to non-academic stakeholders is seldom known and assessed in formal evaluations, i.e. goals and regulations do not necessarily take into consideration whether a project is an industrial doctoral project or not.

The hypothesis behind this study is that systematic communication increases the possibility of succeeding with industrial doctoral projects. The success of a project means continuously demonstrating relevant values throughout the whole project and concluding it by successfully defending a PhD thesis that is beneficial to all the parties involved. Systematic communication should include business values and use terminology that is understandable to all the stakeholders.

The overall aim of this paper is to contribute to a better understanding of industrial doctoral projects in modern educational environments where the stakeholders come from both academia and industry. It discusses the role of the doctoral students and the evolving process around their projects in environments at the interface between academic culture and industrial traditions. This is done by presenting the construction and use of a supporting instrument at an industrial research school specialising in applied informatics and the evaluation of the instrument. The following questions are examined:

  1. How can industrial doctoral projects take into account process steering instruments?
  2. How can a process steering instrument be used at a research school?

Based on the rules and regulations and stakeholder requirements, with a focus on the value creation, and coupled with a short presentation of the development of the process steering model presented in part earlier (Heldal et al., 2014), this paper includes new data from meetings and interviews with stakeholders after three years of use. The data is discussed in view of documents and literature ensuring successful completion of industrial doctoral projects.

The structure of the paper is as follows: Section 2 presents previous research results dealing with issues that support or impede knowledge transfer between academia and industry and the requirements for running academic projects that are relevant in practice. Section 3 describes the Methodology, Section 4 the basic components in the design of a process steering instrument that is called Thesis Steering Model (TSM). Section 5 presents experiences from the introduction of TSM and during the three first years of use. Section 6 discusses the findings, with the literature as a background and Section 7 concludes the paper.

While the overall aims of a doctoral project – producing new academic values and demonstrating the capacity to perform independent research – are not questioned, the paper focuses in the first instance on the interests of industrial stakeholders and the support they can provide for industrial doctoral projects. Moreover, the role of management in involving all stakeholders interested in industrial doctoral projects is also discussed. The current limitation can be the relatively short time, acquiring a better understanding of the influence of process steering methods may require further investigation in a longer time perspective. Three years may be quite a short period of time to carry out a more rigorous evaluation of the effectiveness of such instruments.

2. Background

Good industrial doctoral projects need to deal with cultural differences between the environments in question and the roles and responsibilities of the stakeholders, including uneasy decision-making situations. In order to identify possible areas of support, this section focuses on the identified problems and benefits outlined in the literature and in current steering documents in Sweden.

2.1. Two different cultures: University and Business

The different countries in Europe and in the European Union invest huge resources in industrial doctoral projects (Schiermeier, 2012; Borrell-Damian, 2009). While the importance of university-industry collaboration via different projects is recognised, the innovations achieved are often considered to be ‘smaller’ in contrast to real breakthroughs. As regards doctoral projects, stakeholders from academia respect that in the first instance it should be the goals set by universities and at national level that regulate projects. Stakeholders in industrial contexts recognize this; however, they would like to understand and follow their ‘own’ doctoral projects. While, they are familiar with the use of process steering instruments as a means of aligning important partial goals to the overall goals in long-term projects, they are not necessarily as familiar with long-term academic projects where the partial goals are, e.g. research proposal seminar, paper x, licentiate thesis etc. The academic doctoral projects do not have business values, deliverables aligning to overall progress, potential commercialization plans, clear process owners etc. Not understanding the major goals and the plan, could jeopardise the progress of the doctoral project since knowledge does not per se flow between the academic and industrial sphere (Hermans and Castiaux, 2007), coordination takes time, and requires careful planning.

An extensive investigation of problems experienced by four different industrial research schools within engineering fields was carried out by Wallgren (2007). She clearly identified a vast gap in understanding between industry and academia; a gap that can cause serious problems for industrial doctoral projects. This can be experienced by the students in the form of inadequate information transfer between the two environments, poor understanding of the business values, a lack of understanding of the economic conditions behind the projects, inadequate control by the companies, problems with supervisors, and the feeling that they are alone when building a bridge between academia and industry.

According to an extensive background examination in the doctoral thesis by Julie Hermans (2011), successful collaborative research and development projects run by academia and industry need to recognise (1) the two-way relationship between the different environments, (2) focus on knowledge co-creation as a process, and (3) have active and supportive social milieus around the projects. She argues in favour of considering a longitudinal and situated approach to nurture good applied projects. Following established approaches for applied and interdisciplinary research could be questionable. This is particularly the case for highly interdisciplinary fields within informatics, as understanding knowledge creation in applied research is often insufficient. Cross-disciplinary boundaries need to be considered for several activities – in order to follow interdisciplinary courses for example (Bergeå et al., 2006). It is highly debatable how one and the same study can follow existing institutional research traditions (Evans and Marvin, 2006) or cross certain disciplinary boundaries (Lowe and Phillipson, 2009) in order to produce new scientific knowledge.

If the most important aspects of successful industrial doctoral projects require awareness of each other’s environment and culture (e.g. Wallgren and Dahlgren, 2005) and project completion in time (Manathunga, 2005) the varying role of the supervisor is probably the most important (e.g. Grant, 2005; Lee, 2008) that directly influences awareness and completion. The relation between the supervisor and doctoral student is highly debated (McCallin and Nayar, 2012; Deuchar, 2008), especially considering the involvement of industrial supervisors with currently unspecified roles (Salminen-Karlsson and Wallgren, 2008). However, industrial supervisors are undoubtedly influence the flow and results. If the academic and industrial stakeholders are not coordinated a doctoral project can meet conflicting requirements (Morris et al., 2012). In order to solve problems such as these, both the different supervisors and the student should assume the role of negotiator and translator (Strengers, 2014). Success is more likely can be achieved if there is good communication and a joint decision-making involving both university and industrial partners (Salimi et al., 2016). This position is only possible with a high degree of involvement which, apart from having the right professional expertise, also needs personal skills (Malfroy, 2011) and longitudinal planning (Thune, 2009).

To plan industrial doctoral projects are subject to debate at different levels. The definitions of values certainly can and need to be discussed when studies argue in favour of using entrepreneurial methods for value creation (Lackéus and Williams Middleton, 2015). While the aim of this paper is not to promote industrial development directly but to do so via new scientific knowledge, consideration must be given to the environment in long-term projects if values are to be of interest. Methods and terminology from industry must be taken into account when projects include business stakeholders and when the aim is to achieve employability at business companies (Harman, 2004).

2.2 Influences of industrial stakeholders

For complex industrial projects where no individual stakeholder has the competence to understand and control the entire activity, it is common to work with processes. Processes help to handle and bring order to activity flows that include tasks, players, resources and peripheral players. This is the case for large companies in Sweden, including ABB (Gustavsen et al., 1996), Volvo (Eneroth et al., 2009) and Ericsson (Ericsson, 2012), companies highly involved in industrial doctoral projects.

As an example, the IS-GDP (Information Systems Global Development Process) is one such process, developed at Volvo IT and intended for use in complex IT projects and a refinement of the more general Global Development Process (GDP) at the Volvo Group (Eneroth et al., 2009). The process is defined as a procedure for a repeated activity, such as a production line, a computer algorithm or a code. Given standardised input of the right quality, the process delivers standardised output of the desired quality. Central to the process concept is what should be agreed on in the different process steps, not how or by whom. While the structure for doctoral processes can be the same, the progress and the content toward achieving the main goals are usually different (Newbury, 2003).

Since doctoral students need to be aware of the different ways in which academia and industry gather and handle knowledge (Ivček and Galinac, 2008) and possible differences in terminology during a long-term industrial doctoral project, it is important to clarify whether main values are understood in the same way during the key steps that have been identified. To overcome any misunderstanding of complex industrial contexts, where no individual stakeholder has the competence to understand and control the entire activity, processes can be used to manage projects. Ankrah and Tabbaa use a process approach to summarise a systematic review of university-industry collaboration (2015). Their process approach begins with establishing collaboration, moves on to defining organisational forms and operationalising activities, and ends with investigating outcomes. This study is focusing on developing a model to define forms of collaboration and support communication around activities and partial goals.

2.3 The Swedish doctoral process

Previously, a full-time doctoral programme took an average of four years’ full-time study. That has now risen to a longer time due to other duties and interruptions, such as teaching, project work, parental leave, sickness etc. Certain requirements need to be fulfilled during each doctoral period (see Figure 1).

Figure 1. The PhD process in Sweden (picture by courtesy of Wallgren and Dahlgren, 2007, p. 434). Illustrated is a four-year, full-time PhD project from commencement (A) through individual study plans (IS[2], one per year), Intr (Introductory seminar), thesis proposal (TP) and a mid-term, i.e. licentiate (Lic) seminar and the thesis (Ph.D.) seminar. Figure 1. The PhD process in Sweden (picture by courtesy of Wallgren and
Dahlgren, 2007, p. 434). Illustrated is a four-year, full-time PhD project from
commencement (A) through individual study plans (IS[2], one per year), Intr
(Introductory seminar), thesis proposal (TP) and a mid-term, i.e. licentiate
(Lic) seminar and the thesis (Ph.D.) seminar. 

When a doctoral project commences, many doctoral students and their supervisor(s) from industry are not aware of the academic doctoral process and the requirements that emerge during this process. The students and their supervisors do not necessarily have full knowledge of the business value of their concrete research ideas. Careful guidance through the process is essential, particularly at the beginning when research problems are formulated. This problem formulation is a key area that can set the tone, expectations and conditions for the doctoral student and her/his progress for years to come. It is important for all stakeholders (doctoral students, supervisors and mentors) to realise that problems cannot be identified in isolation by one or two parties. Instead, they must be identified through collaboration in order to ensure value and benefit for all concerned and that the doctoral project is supported by everyone (Wallgren and Hägglund, 2004). ‘

3. Methodology

Handling multiple targets and acquiring a mutual understanding that creation of added values are key issues to ensure the best possible synergy effects. The results describe the development and use of a process steering instrument, which was used for doctoral projects at an industrial research school specialising in informatics – ApplyIT. The instrument is named Thesis Steering Model (TSM). Section 4 presents TSM, developed to plan structured up meetings for all stakeholders based on academic and industrial requirements. Section 5 presents the evaluation. This is done via participatory observations from the responsible management group for TSM. The management groups incorporated three persons belonging to the management group of the school. This study contains data from 19 gate meetings (about the gate meetings, see Section 4.2), examining documents from TSM, and informal conversations with the stakeholders during the first three years of usage. To answer the research questions results from 12 semi-structured interviews were used, with 6 doctoral students, 3 industrial stakeholders and 3 academic stakeholders performed 2015 and 2016.

4. Development of a process steering instrument for industrial doctoral projects

Previous sections have shown that a number of challenges can arise in a doctoral project and collaboration, handling multiple values and acquiring a mutual understanding of those values are key issues to ensure the best possible synergy effects. This section argues in favour of and describes the development and use of a process steering instrument, which was used for projects at an industrial research school specialising in informatics ApplyIT[3].

4.1 Incorporating knowledge from different cultures

Having identified underlying problems in industrial doctoral projects, as well as the potential usefulness of the process concept from industry and the requirements for successful completion of doctoral projects, the management group from the industrial research school decided to couple this with their own experiences and develop a formal instrument to support doctoral projects. The instrument, called Thesis Steering Model (TSM), was developed alongside the task of defining the basics, starting up the research school and identifying the needs of the first PhD students.

TSM is an abstract structure for predefined meetings where each step aligns the main educational requirements to the main activities deriving from existing industrial process steering instruments. The content depends on finding the right doctoral project and focuses on values, aims, progress, activities, risks, resources and basic terminology. TSM is a methodology driven by scientific requirements and business needs. The activities are enhanced and intense, especially during the start-up phase, and are intended to support systematic encounters between stakeholders throughout the entire doctoral project.

The main steps during a doctoral process that are known to the university stakeholders are not necessarily known to the industrial stakeholders. Likewise, the main steps in industrial processes are not necessarily known in an academic environment. Following examination of a wide range of industrial process steering instruments, the study focused on a simplified and more generalised instrument. This generalised instrument was based in the first instance on instruments from the industrial stakeholders from the research school. The steps in TSM are meetings that are important to the academic process but which also take into account the industrial process (see Figure 2). While TSM focuses on the mandatory aspects, in the first instance the academic process, characteristics from the industrial process are also in focus.

Figure 2. The TSM considers the academic process for a doctoral project and important steps taken from project steering instruments used in industry.
Figure 2. The TSM considers the academic process for a doctoral project and important steps taken from project steering instruments used in industry.

Beginning and successfully ending a doctoral project via requirements from academia is important. Conveying the terminology related to duties and progress via the generalised process steering instrument known to the industrial stakeholders clarifies eventual misunderstanding and promotes discussion about current values and goals.

In order to identify important steps for TSM, local university and national requirements for doctoral projects in Sweden are considered together with experience gained from industrial process steering instruments. Most doctoral projects at Swedish universities comprise five important steps: admission, suggesting a research proposal, obtaining a licentiate (mid-term seminar), a concluding[4] seminar, and a public defence. In addition, annual continuous progress plans, known as Individual Study Plans (ISP), must be set out at the doctoral student’s research location. This plan shows the current status of the doctoral project but seldom the progress made in relation to previous plans (Thune, 2009; Vesterlund, 2015). To show progress processes steering instrument can be used to emphasise negotiations for key steps for the different stakeholders. These negotiations are particularly important during the early stages of a project (Strengers, 2014). Examples of values that need common agreement include partial goals, associated resources, managing changes, participation levels and issues related to the roles and responsibilities of the parties involved.

TSM was developed by the management group of ApplyIT to provide evidence of progress, ensuring that

  • a project group that aims to start and support a doctoral project is formed
  • innovation techniques are used to generate and identify research ideas more quickly
  • time and other resources are allocated already from the idea generation phase
  • important milestones and stages in a doctoral project are identified and facilitated through scheduled communication and collaboration meetings
  • academic values in terms of scientific significance and business value are discussed at each meeting
  • the terminology is widely understood and the process is transparent
  • progress reports are produced based on common agreements between all key stakeholders after each meeting
  • a focus is maintained on overall goals as well as awareness of any deviations that may arise at a meeting and within each identified step
  • the progress goals are revised and aligned to the overall goals

Therefore, a project group consisting of the PhD student, the supervisor, the assistant supervisor(s) and the industrial mentor(s)[5] was formed for each PhD project. They were obliged to participate in a number of meetings, as described in Section (3.2) below. In order to allocate responsibility as close as possible to the work that was being conducted, the PhD student was appointed to act as project leader and the person responsible for the content of the meetings. This naturally meant that she or he would initially need a great deal of support from all the parties involved.

The progress of every doctoral project needs to be monitored by a project steering group consisting of the project group members and at least one person from the industrial research school management group. The involvement of external individuals from the school in longitudinal plans for doctoral projects alongside the members of the project group, coupled with the use of TSM, is new and unique in Sweden for the industrial doctoral project administration.

4.2 TSM: an instrument that supports systematic collaboration in doctoral projects

The TSM is an instrument for longitudinal support based on seven or so gates (see Figure 3). Each gate involves an associated gate meeting with systematic and thematic questions that are set out in templates (15 active slides for each meeting), and which need to be answered prior to each gate meeting. The answers to these questions require a great deal of teamwork on the part of the project group. The TSM is thus not a quick fix guide to pass the gates but more a process tool to get communication flowing in the project group and to harmonise the members’ expectations by identifying and discussing scientific requirements and possible associated business values.

Depending on the project and the familiarity of the project group with process steering tools, the preparation before each gate meeting takes a few days. As the templates for the different meetings are related to each other, the work involved in understanding the structure of a meeting decreases after each gate meeting. The presentation of the templates at the gate meetings usually leads to further discussion.

The TSM aims to achieve the following:

  • Describe what needs to be done (generate ideas and plan activities) and when they should be done (by identifying important phases and elements as ‘gates’), but leave the how question to the project group.
  • Provide guidance, support and quality assurance for the research projects by going through a series of gates, where each gate represents a key phase with associated templates.
  • Support communication between the academic and industrial partners and follow this up at systematically planned meetings. The partners need to come up with a mutual agreement and understanding of the goals behind the doctoral project at each gate a) by formalising concrete goals and decisions regarding time, resources, quality and content and b) by ensuring that key issues have been covered and the right resources of the expected quality and content are available.
  • Provide a skeleton to ensure appropriate areas are documented sufficiently with regard to important decisions and individual project requirements.
  • Be easily understood by all the parties, regardless of their background.
  • Bring transparency and control into project monitoring by focusing on the importance of commitment, common sense, cooperation and active involvement and by highlighting potential risks before they become a problem.
  • If possible, generate synergy effects between the doctoral projects.

 TSM have the following gates:

At the Start Gate the project group is formed and the project vision and expectations are formulated in general terms and are agreed on in order to commence the pre-study. Initial scanning of related work is carried out with a focus on novelty assessment. The pre-study ends with the Vision Gate, which is where multiple project visions are generated. Several possible ideas have been investigated and possible goals and research problems have been formulated. Related research from other parties and potential external cooperation environments have been considered. The vision of the project has become clearer.

At the Concept Gate, the main feasible research goals are discussed and ways of reaching these are examined. The research background needed is discussed together with possible external cooperation environments and experts and the potential for collaboration. At the Development Gate clear targets, plans and methods to achieve the research aims are formulated. The resources needed to do so are planned and secured from all stakeholders. These four early gates are the most important gates and correspond to the convergence in the funnel model used in innovation theory.

The Follow-up Gate aims to discuss the mid-term seminar and future plans. Several Follow-up gate meetings can be requested, depending on the doctoral project. The formal concluding gates are the Thesis Gate, which involves preparing for a formal pre-defence and defence, and the End Gate, which involves concluding current collaboration and preparing for future collaboration, and ends the series of TSM meetings. The correspondence between scientific magnitude and business value is considered at all gates.


Figure 3. A general overview of the doctoral project from the point of view of the TSM.
Figure 3. A general overview of the doctoral project from the point of view of the TSM.

The four most important values – research quality, progress towards examination, associated business values and overall project control – as streamlines are shown in Figure 3. These are discussed at each gate. As an example, the increased number of ideas and visions and the width of the Vision Gate will converge towards the concrete aims at the Development Gate.

3.3 Gate meetings

Seven gate meetings are intended to take place at well-defined stages in the project, depending on the progress and the degree of activity of the doctoral student. A student usually spends 80% of her/his time working on the project and the remaining time is taken up with working in industry or teaching. As a result, her/his PhD project may take five years.

The first three gates occur relatively early on in the doctoral project. A formal progress sign-off meeting (i.e. a workshop) is planned at each gate. At each gate-opening meeting a discussion takes place within the project steering group, based on the preliminary work carried out within the project group. The aim is to ensure the discussions remain constructive and to keep the plans transparent and approved by everyone. If the discussion goes well, the gate is formally opened.

Opening a gate at the gate meeting is a symbolic action that means that the progress made is acknowledged and that the PhD student can continue her/his work. If the gate is not opened, clear indications are given about how to continue with the thesis. Formal minutes from each gate meeting are written with a focus on the four main questions (research values, examination management, business values and project control), including important decisions or unanswered questions or risks.  Figure 4 is taken from a Concept gate presentation dealing with identification of the research problem and the benefits of a project. As this is a template, the headings are the same throughout the whole process although the content the doctoral students add at each meeting changes over time.

Figure 4. An example of a template presented at a Vision gate meeting by a PhD student. The template shows the identified strengths, weaknesses, opportunities and threats within a project dealing with automated improvement analysis of a production system.
Figure 4. An example of a template presented at a Vision gate meeting by a PhD student. The template shows the identified strengths, weaknesses, opportunities and threats within a project dealing with automated improvement analysis of a production system.

 4.4 Influences on development

The management group at the industrial research school included members from the university and from industry who have previous experience of managing pure academic and industrial doctoral projects and from using process steering instruments, especially ISGDP (presented in Section 2), which is a familiar feature at Volvo. As the majority of the doctoral projects in question were initiated by Volvo and people from the management group already had industrial experience of ISGDP from several Volvo companies, the management group decided to develop a process steering instrument based on several other process steering instruments. ISGDP was the one that had affected TSM most.

Picture 1. Stakeholders at the research school kick-off listening to a presentation of TSM.
Picture 1. Stakeholders at the research school kick-off listening to a presentation of TSM.

In order to use TSM, the university management and supervisors were informed and they had to give their approval. During development, two former industrial doctoral students from the university were interviewed and their experiences were taken into consideration. It was ready to use when the Applied Informatics research school[6], complete with eight doctoral projects, commenced in January 2013. An initial overview of the development from a two-year perspective has been presented earlier (Heldal et al., 2014). In 2013 and 2014, the TSM was improved based on early comments. The changes included the introduction of the Follow-up Gate (requested by the project group) and improving the accuracy of the templates. The TSM was used initially in eight doctoral projects and it is currently (2016) being used in twelve projects[7].

For the introduction, one-hour seminars were arranged on a number of occasions for the stakeholders to explain the project methodology. It was explained again at a separate seminar held during the two-day ‘kick-off’ meeting for the research school, which took place in January 2013 (see Picture 1) and which was discussed at a workshop by different combinations of participating stakeholders in June 2013.

5. Using a process steering instrument for industrial doctoral projects

Breaking down the process into smaller parts makes it easier for the doctoral students to report their progress while still maintaining coherence between scientific and industrial needs and requirements. TSM enables them to keep values – both academic and industrial – in focus, and to ensure that both supervisors and industrial mentors have a common understanding of their problems. One of the main lessons to be learned from this study could be to acknowledge that focusing on the introduction of a doctoral project needs better communication. This is also confirmed in other studies (Wallgren and Hägglund, 2004; Wallin et al., 2014). It is not very easy to understand each other’s needs at the beginning.

1.) How can industrial doctoral projects take into account process steering instruments?

 Based on the literature for managing good university-industry projects, both industrial processes and documents regarding compliance with the academic requirements for a doctoral thesis influenced the development of TSM, as described in Section 3. Even at the construction phase a large number of associated questions needed to be addressed; questions about the content and how to use it and about roles and responsibilities associated with use. In order to accept the instrument, several meetings needed to be initiated and coordinated, and the instrument needed to be adjusted according to observations and requirements laid down by the university management and the parties involved in funding the research school.

One of the main observations is the substantial difference between the users’ background and their familiarity with process steering instruments. In three of the seven projects there was no previous experience of project management and process steering instruments, which made TSM difficult, especially at the beginning.

Positive comments were also received from the other eight research schools that were partly financed by the same national research funding institution as ApplyIT. While several schools requested the documentation necessary to run TSM, no one has to our knowledge applied the tool in their environments. In the light of the required coordination time, it could be considered beneficial to develop the instrument in parallel with development of the research school, which demands additional time on the part of developers and managers. To begin using it, the school may require resources to change the content and a number of strategic decisions may need to be made regarding how to use it in current doctoral projects.

2.) How can a process steering instrument be used at a research school?

This part is based on an initial overview of 19 meetings (SG, VG and CG) for seven doctoral projects. The following parts discuss separately the perspectives from a) the doctoral students, b) academic stakeholders and c) industrial stakeholders.

a) The doctoral students’ perspective

At almost all the SG meetings (for 6 out of 7 students) there were misunderstandings in relation to the research questions. For one student, who had supervisors from two universities and mentors from two companies, this was very obvious. Even if the aim of providing better decision-making support was stated before commencement, it became clear at the meeting that stakeholders were interested in at least three major research areas when approaching this aim and they had different opinions regarding the underlying research. Only two out of the seven project groups held at least one additional meeting with the whole project group between the beginning of the doctoral project and the SG meeting. A positive consequence of having slightly difficult templates was the increased discussion between the doctoral students regarding the meaning, for example, of research aims, business values and internal and external cooperation potential. One student, who was doing an industrial doctorate at Volvo, stated: “It was great to contact X and see her templates. Even if our projects differ a lot and even if she is working at GKN, I see we have a number of common issues regarding our research.”

While the SG meeting was considered to be more frustrating due to a lack of familiarity within the groups and with the templates, the VG meeting that was held approximately six months after commencement was considered by many projects to be positive. Idea generation with some constraints had already been discussed before the start-up and proved useful. Again, there was only one project where all the associated supervisors in the project group met between the SG and the VG meetings. According to one student: “Having all my supervisors in one place and being able to discuss with all of them the possible external environments and where important research or development projects are and what needs to be considered, proved to be extremely useful.” A student who held his SG and VG meetings together (after failing at the first SG meeting) commented: “I still think your templates are difficult, but this was really a great day for me. I feel that I have a better understanding of what I need to do in my research.”

It was hoped that all CG meetings would be held approximately one year after the start, but the meetings were only held during the second study year. Unfortunately, in most of the doctoral projects the project groups did not hold any additional meeting between VG and SG.

One of the aims of TSM, i.e. to follow the doctoral process and empower doctoral students to gain a better grasp of their projects, was considered to have been reached, but further investigation is needed to discuss how this can be made more seamless. For two of the doctoral students, assuming responsibility was a major problem and planning the first gate meeting took an unnecessarily long time. In general, some experience of project management and process steering would be beneficial to all students before starting their industrial doctoral studies, i.e. from the second information meeting dealing with TSM one year after the start. Here we can see that it is not the well-run projects that are in most need of steering. The main benefit for the student is that she/he is presented with a valid problem early on and which is of interest to both the university and industry. Another important aspect is that training in project culture would be a considerable advantage when entering the professional world. Direct contact with industry during the study period would also be enhanced.

b) The academic supervisors’ perspective

 Those academic supervisors who had previous experience of industrial collaboration, and those who had collaborative projects involving different universities, were more positive about TSM. For the last two studies the industrial perspective and business value were only dealt with on a hypothetical level. In these two cases, the management group and the academic supervisors discussed the relevance of process steering to the projects. Although before the first TSM meeting (SG) the use of TSM was called into question, the supervisors agreed to continue using it due to the fact that TSM made it easier to follow the same project from different research areas and different places.

Initially, the academic supervisors were somewhat sceptical but they became significantly more positive after a number of meetings during which TSM was explained and discussed and after realising that TSM would help them in their collaboration with the mentors from industry. There were also differences of opinion between the supervisors depending on their level of activity in the doctoral projects. The younger supervisors in particular adopted a more protective view of their students’ time and involvement in activities that were not vitally important to an accurate study.

c) The industrial mentors’ perspective

Most of the mentors found it interesting to work with TSM except those from smaller consulting companies and in the case of a doctoral project where the supporting company changes during the project. A mentor from GKN stated: “In order to follow X’s [the doctoral student’s] work we participated in the regular status meetings where the TSM model was presented as support in the process and X presented her work. Accordingly, X […] is on the right path and we now understand her thesis proposal and a recently published paper at a scientific conference. From the company’s perspective, X’s efforts have resulted in improved maintenance expertise, which is valuable to us.”

There are differences between mentors who are already used to doctoral programmes and those who are not. Discussing terminology, e.g. what is a research proposal, when and how can a paper be published and what participation at conferences means for doctoral students, is important not only for managing and funding resources but also for attracting interest from the company.

In the short term the company will have a competence influx via those persons from the company who are participating in the project and via discussions with university participants on different occasions. Regulations and legal systems mean that concept content differs from one organisation to another. An example was that different regulations stipulated that organisations were required to maintain control of information security and privacy. These issues arose on several occasions at the gate meetings.

In the long run, however, it emerged that the TSM ideas are more difficult to understand in practice than the school management group first anticipated. We have met with different reactions and been somewhat surprised by them. One industrial mentor stated: “We are not experienced in identifying the research problem that needs to be addressed, and a problem almost never gets an industrial research project up and running”. This opinion needs to be discussed further. According to the aim of TSM and the discussions during the gate meetings, the industrial mentors should be empowered to express their thoughts and to attempt to deal with problems, needs and ideas within the project group. Industrial supervisors who are not used with supervising doctoral projects are not aware on their own role. At the end of the second year, a course for teaching mentors was requires. Maybe this course is not necessarily needed for everyone. For another project, another mentor, used with supervising doctoral projects r commented at a VG meeting: “I am not interested in this […] since it is only producing a small improvement for us, an improvement that I can order and test much cheaper from […]”. While the scientific relevance of the research depends more on the supervisor from academia, securing industry approval for the study is extremely important.

The mentors realised there was a willingness to focus on industrial challenges founded in business needs and they were positive, even if they were not sure about the results and even if they found it difficult to find the time to provide input for the doctoral students or find a time slot for collaborative gate meetings.

6. Discussion

Doctoral projects that aim to create new knowledge are difficult to evaluate, especially by introducing new routines or management instruments. What can be attributed to individual abilities and what can be attributed to artificial support is always a subject for debate. The general positive attitude, despite difficult templates, allocating time for meetings and solving coordination problems, is, as one student put it, a result of getting more attention. As one of the students stated: “On the whole, ApplyIT works very well, especially with regard to the additional aids it gives us when we compare an ApplyIT doctoral student to a ‘regular’ doctoral student.” According to the same student, being the first also means embarking on a new path: “I belong to the first group of doctoral students at the research school and I came across certain things that could be improved. These have also been raised with the management and steps have been taken. TSM works well and clearer instructions (with examples from past students) for the gate material are now in place. I believe this will provide a good example for future doctoral students.”

The role of support on the road to becoming an independent researcher could also be discussed. A member of the management group, who was an experienced mentor for several industrial doctoral projects, said: “In the case of my own doctoral studies, approximately fifty years ago, my supervisor told me to go to the library and find my research problem and research questions”. While this strategy may promote a willingness to learn and make new inroads through one’s own efforts, it is difficult to follow this principle today with the limited timeframes available. Finding a smaller research area by yourself and defining research questions may contribute to learning experiences but it can scarcely be followed by many stakeholders. According to one manager and mentor from another research school: “I don’t have time for Start Gate and Vision Gate. I have to define twelve important research questions prioritised at my company, choose twelve good students, and start with the Concept Gate”. Consequently, one can discuss the role and the number of gates and how these can be defined to support and not delimit research at the very beginning of doctoral projects. Here there is a related question regarding the quality of the project and how steering and supporting that can help truly revolutionary innovations (e.g. National Academies of Sciences, 2016) and not marginalise the research contributions (Blumenthal  et al., 1996) can be possible with predefined research questions. Establishing research questions in interesting research areas and defining research contributions are clearly different from development or consulting needs. Behind these questions there may only be a subtle border, and it should therefore be discussed further. Having pre-defined gates, templates and research questions may encourage investigation of roles and aims behind industrial doctoral projects in order to sort out possible concerns about exploitation of students and ’over-industrialisation’ of higher education. (Schiermeier, 2012: p. 559)

According to this study, exploring the diversity between academia and industry can produce values if the differences are acknowledged, identified and handled from the very outset. The gain for the company is understanding state-of-the-art technologies and associated research efforts at national and international level. The meetings for discussing and steering research projects are expected to provide a good example for future projects. There can be resulting spin-off effects in terms, for example, of good master’s dissertations and other research work initiation. The dominating positive effect for industry is if they employ the successful doctoral student and bring her/him into their organisation. There she/he will make a substantial contribution in terms of time, especially by analysing problems systematically. The ‘absorptive’ effect of the research school in general can be seen in the study by Bienkowska and Wallgren, in which 19 PhD graduates were interviewed 5-10 years after being awarded their PhD (Bienkowska and Wallgren, 2012). While many companies, especially the larger ones, have an interest in supporting genuine research, they are also interested in the higher levels of competence that can be accessed via new PhD graduates (Schiermeier, 2012)

7. Conclusions

This study presented a process steering instrument, TSM constructed and used at a research school in applied informatics and provided examples for its use. The main challenge was to getting the industrial research school to prioritize time and resources to start to use TSM. Our evaluation show that meetings would not be scheduled and, as Section 3 exemplified, issues would not be discussed without TSM. One of the main lessons from this study is illustrating the needs for carefully planned introductory activities. Industry mentors are not usually trained in research procedures. Their role should be better clarified. Since the backgrounds of the stakeholders are different, it would be beneficial to know more about their view of values, handling intellectual property, patents, publications and dependence on co-funding companies already during the development supporting instruments.

This study acknowledges the result from Hermans (2011), on the importance of having active and supportive social environment around the projects and the benefits of developing the instrument alongside with developing the research school. To adjust routines and procedures for TSM according to comments and suggestions from the different stakeholders during the development phase was useful.

TSM was served as a way for the doctoral student to take the leadership for their own projects and report partial advancements to all stakeholders, as the templates were well suited to such presentations. However, only some students could master project leading and instruments for process steering at the very beginning of their graduate careers.

During this study there were a number of changes at different levels at the research school and in the surrounding research environment, including changes in the institutional structure at the local university. More than half of the doctoral projects replaced some of the academic supervisors, and a number of them replaced mentors. Even the form in which the school was co-funded by the different stakeholders changed. Handling change needs to be investigated more thoroughly for such long-term projects. Our evaluation also show that small companies need more help and therefore it would be beneficial to further investigate the need for additional support to them.


I would like to thank Lars Bråthe for much help with this paper, Robert Murby and Eva Söderström for their collaboration for building TSM, the members of ApplyIT for their fruitful comments, and Patrick O’Malley for reviewing the paper.

[1] According to the Swedish Council for Higher Education, the average time taken for doctoral projects completed in 2014 was 5.5 years (11 terms). (See: )

[2] IS (or ISP) stands for Individual Study Plan, a yearly plan for the doctoral student that must be signed by the doctoral student and the academic supervisors.

[3] The industrial research school in Aplyied Informatics (ApplyIT) later changed its name to IPSI.

[4] The concluding seminar is often called a pre-defence seminar.

[5] In certain contexts, the industrial mentor is called an industrial supervisor.

[6] The name of the research school changed from ApplyIT to IPSI in 2015.

[6] The name of the research school changed from ApplyIT to IPSI in 2015.

[7] After changing the management group at the industrial research school, the Follow-up Gates and the End Gate were removed. See (July 22, 2016)


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Contexts and Approaches to Multiprofessional Working in Arts and Social Care

I. Introduction

In this article, we identify the basic concepts informing multiprofessional competencies in arts and social work/care, focusing on their specific cultural contextualisation,  as framed within the currently running project MOMU (Moving towards Multiprofessional Work in Art and Social Work) funded by the Erasmus+ Programme.[1]  In short, the project aims to define competencies in teamwork and enhance educational/teacher knowledge and skills in arts and social work/care (MPW) by developing learning materials and handbooks in this area and embedding this in undergraduate HE provision. It builds on the work carried out in the project MIMO – Moving In, Moving On!  which established and embedded the initial methods for MPW into professional practice in Finland and Estonia[2]. (TUAS, 2013)

The emphasis of this kind of MPW work lies in combining the strengths of different arts and social work/care professionals to work effectively together with individuals or communities to address the identified needs. It is a multiprofessional practice stemming from a multidisciplinary approach to working with communities and individuals.

This article will thus aim to a) articulate the cultural and critical contexts of relevant concepts and b) propose overarching criteria for learning frameworks which inform future training modules in the area of MPW.

II. Scope and context

As the initial project documentation suggests, there are ‘artists who are willing to work in new kinds of environments. In the field of social work there is a growing willingness to apply art, but it is not always easy when different professional cultures confront’. (Tonteri, 2013) Artists and arts professionals might feel that they cannot get inside the community of social work professionals or might perceive that by doing so, they leave their artistic integrity behind or open themselves to risks. Social Work/Care professionals, on the other hand, often feel that collaboration may make their work more complicated, and there is often a lack of confidence in applying artistically informed approaches. More often than not, although there is real enthusiasm and willingness, they do not perceive themselves as artists, and do not feel they have the credibility or confidence to use artistic methods. Art is perceived to be associated with a deeply informed, embodied and/or studied practice and thus represents a barrier towards a wider, or deeper application of arts-based approaches in social work/care contexts.

There are plenty of case studies and projects demonstrating on the one hand the positive impacts of art-based working with youth and ethnic minorities (and other communities), and on the other the effectiveness of multiprofessional approaches in health and social care (Glasby, 2007). This project builds on these and various premises that have been widely explored in other publications and embedded into policies and professional practices but focuses on joining these two specific areas of professional practice. For sake of clarity, the basic premises that underpin this work are listed below, provided with a few key recent publications supporting their assertions:

  • Arts and culture engagement maximises social well-being and a nation’s productivity
    (Carnwath & Brown, 2014; Daykin & Joss, 2016; Sacco, 2011; The National Youth Agency UK, 2009; The Finnish Ministry of Education and Culture‘s Child and Youth Policy Programme 2012–2015; The (Finnish) Art and Culture for Well-being 2010-2014;  The Spanish National Strategy ‘Culture for all’; etc)
  • Multiprofessional working environments are a key component of modern healthcare/social care and policies dealing with children, young people and adults have already accepted/embedded the need to work with multiprofessional approaches as an effective means to achieve impact
    (Barr, 1996; Lewitt, Cross, Sheward, & Beirne, 2015; The Scottish Government, 2012a, 2012b; Zwarenstein, Goldman, & Reeves, 2009; EU Youth Report 2012; The Spanish National Strategy on Disability 2012-2020;  Government Green Paper entitled ‘Every Child Matters’; Children Act in the UK; etc)
  • Integrating both arts-based approaches and multiprofessional working methods within young people benefits growth, well-being and participation of young people (Krappe & Leino, 2013; Krappe, Parkkinen, & Tonteri, 2012; Leino, 2012; Tonteri et al., 2013; TUAS, 2013)

These underpinnings need to be inherent in any learning frameworks training young professionals in MPW in social care/work and art, allowing professionals not to lose sight of the need to be effective advocators of the connections between arts and society. The given basis that arts and culture engagement maximises social well-being and a nation’s productivity already appears in various policies, but what is often missing are more formal learning frameworks that help afford professionals to gain the skills, knowledge and competencies needed for effective MPW work to address the challenges of young people in our societies today. Additionally, learning frameworks will need to be able to address the cultural and national contexts of communities, welfare and political institutions as well as learning organisations.

This is where multiprofessional approaches can provide solutions by using the full depth of artistic engagement, while maintaining the community focused support specific to the needs and requirements of the social context. Examples of multiprofessional teamwork by arts and social work/care professionals already exist extensively, but there is a lack of learning frameworks that allow MPW teams to be supported by a structured process of negotiating roles and understanding their own responsibility in this collaborative process.

III. Linking arts-based methods and multiprofessional work

The concepts informing multiprofessional collaboration are widely used, but not often specifically defined in the context of arts and social work/care. Either they cover MPW education (or IPE – Interprofessional Education) (Davis & Smith, 2012; Lewitt et al., 2015), or they consider arts-based approaches in social work without the MPW element.

Within the context of multiprofessional work in arts and social care/work, we define MPW as a collaborative practice stemming from an inherently multidisciplinary approach to working with communities and individuals. Its strength lies in combining the knowledges and skills of arts and social work/care professionals to work effectively together to address the identified needs.

Reappearing themes from prior projects, as well as the general literature, point towards the need to consider integrating supportive measures to address these. These recurrent themes include:

a) From practical, conceptual to organisational dimensions

MPW education does not stand in isolation, and like any multidisciplinary or newly emerging practice, the various dimensions in which it exists tend to become important when advocating for its efficacy. When considering degree level training and knowledge acquisition within universities, multi- and interdisciplinary practices are always influenced by various dimensions, including:

  • the academic – multidisciplinary curricula and degree structures
  • the organisational – institutional infrastructure for multiprofessional practice
  • the social – disciplines underpinning professional practices are elementally social constructs (Boehm, 2007)

Parna referring to specifically MPW work (in Krappe & Leino, 2013) has similar divisions, from organisational, conceptual to practical. These different spheres continuously interact and need to be constantly negotiated in order to ensure that MPW can be embedded both in educational curricula, experiential learning or placement activities, as well as professional practice.

Thus as with any innovative learning practice, it will be of interest to academics and practitioners working in this field to ensure that we have the evidence to prove its efficacy in order to devise learning components that fit into existing organisational structures. Persuasive cases need to be made for the various organisational structures in order to allow effective MPW learning to happen, such as supporting multiprofessional team teaching; co-teaching of multidisciplinary students cohorts.

Outcome measurement thus becomes a necessity in order to afford the organisational dimensions to meet the needs at the theoretical and practical level. In a similar manner, how to measure the individual/pair impact of embedding MPW in professional practice interventions is a subject matter that needs to be integrated into educational provision. And as Carpenter (2005) identifies, outcomes can be at a number of different levels; about learner’s reactions, modification in attitudes and perceptions, acquisition of knowledge, changes in behaviour, changes in organizational practice and benefits to service users and carers.

b) MPW caught in the vocational vs academic debate

To understand and advocate effectively the facilitation of university-based learning environments for multiprofessional practice, it also helps to understand the question of multi-, inter-, and transdisciplinary knowledge creation in universities including their historical evolution that have widely influenced organisational structures.

Depth of knowledge has not always been prioritized over breadth, and the organisational challenges to mind the gaps between what is considered academic and what vocational; intellectual vs professional learning experiences; all these still stem from a 19th century model of intelligence. Certain subjects have come to be perceived as academic only since the 18th century and were reinforced as being ‘academic’ by the rise of the Humboldtian model of a university, which was accepted by most European and American universities. That the English and Scottish (and Irish) ancient universities have more recognisable remnants of their medieval origins may in some way also explain the wider acceptance of the ‘practice-based’ in British university contexts, as exemplified by music composition, drama, dance or creative writing. Whereas in the UK composition is taught in research-intensive universities, in Germany it is predominantly taught in conservatories and music colleges. Similarly, the Finnish HE system still displays a binary divide with universities on the one hand, and universities of applied science on the other, the latter usually not providing study to PhD level. Spanish universities are more and more adopting practice-based methods, however there are still clear differences between University degrees and ‘upper degree professional studies’ (‘formacion professional de grado superior’) which are the equivalent of Universities of Applied Sciences in Finland. Arts Schools in Spain also fall into this category[3]. Even in the UK, where the Further and Higher Education Act of 1992 placed the former polytechnics – with their more vocational and practice-based cultures – into the same framework as the old universities with their perceived predominantly academic provisions, the binary divide is still apparent and its value system perniciously remains, for example in the form of perceived research intensity.

As many of our modern European and US universities are built upon just this Humboldtian ideal of knowledge and intellect, some have argued (Boehm, 2007; Robinson, 2010) that this poses a challenge to our education systems, as well as to our means for knowledge production. The perceived difference between the ‘vocational’ and the ‘academic’ is based on this very specific intellectual model of the mind: that our perception of what academic study entails was formed at a time where the concept of intelligence was limited to the ability to reason deductively. Robinson (2010) sees this divide as being detrimentally influential in the secondary educational sector, but also suggests in his keynote speech to the RSA in 2010 that we need to scrap the perceived dichotomy between the ‘academic’ and the ‘non-academic’, the ‘theoretical’ and the ‘practical’. ‘We should see it as what it is: a Myth’.

The scale and quality of adoption by universities of innovative professional practices, such as MPW in arts and social care, is affected and influenced by these contexts, and in turn affects the creation of the skills and competencies needed for multiprofessional work, and this has been repeatedly identified in the general MPW literature reaching back at least 40 years (see Lewitt 2015). For MPW work to be widely accepted in the HE sector, these national and international Higher Education policy drivers will need to be understood to devise convincing cases for adoption.

c) Multidisciplinary knowledge and multiprofessional practice

As multiprofessional work is based on multidisciplinary learning, research and practice, as indicated above, how we facilitate interdisciplinary and multidisciplinary learning in Higher Education becomes an important framework consideration. As part of this, knowledge institutions need to understand the nuances in relation to interdisciplinary knowledge.  Thus apart from above structural dimensions, it also helps to see disciplinarity as an umbrella concept with individual terms referring to various nuances. According to Stember (Stember in Seipel, 2005) we can differentiate between knowledge formation in the following categories:

Intradisciplinary enquiries, which involve mainly one single discipline, such as a musician harmonically analysing a piece of music, or a social scientist using thematic analysis of structured interviews to consider important aspects of self-expressions of particular communities,

Cross-disciplinary enquiries tend to view one discipline from the perspective of another, such as understanding the history and social dynamic of British Pop Bands through Tajfels (1982) social identity models,

Transdisciplinary enquiries, in Stember’s words, are ‘concerned with the unity of intellectual frameworks beyond the disciplinary perspectives’. Seipel goes on to suggest that they may deal with philosophical questions about the nature of reality or the nature of knowledge systems that transcend disciplines.

Multidisciplinary enquiries draw on the knowledge domains of several disciplines, providing different perspectives on one enquiry in an additive fashion. ‘In multidisciplinary analysis, each discipline makes a contribution to the overall understanding of the issue.’ In this, a study of music performance can include insights derived from psychology as well as historical performance practice.

Interdisciplinary enquiries require ‘integration of knowledge from the disciplines being brought to bear on an issue. Disciplinary knowledge, concepts, tools, and rules of investigation are considered, contrasted, and combined in such a way that the resulting understanding is greater than simply the sum of its disciplinary parts. However, the focus on integration should not imply that the outcome of interdisciplinary analysis will always be a neat, tidy solution in which all contradictions between the alternative disciplines are resolved. Interdisciplinary study may indeed be ‘messy’. However, contradictory conclusions and accompanying tensions between disciplines may not only provide a fuller understanding, but could be seen as a healthy symptom of interdisciplinarity. Analysis which works through these tensions and contradictions between disciplinary systems of knowledge with the goal of synthesis—the creation of new knowledge—often characterises the richest interdisciplinary work.’ (Seipel in Boehm 2014)

Multiprofessional practices can thus be seen as the professional application of a knowledge domain that derives from multidisciplinary and interdisciplinary methods of enquiry. These multidisciplinary approaches will be facilitated by the educational frameworks developed by the current MOMU project. What will undoubtedly emerge is also genuine interdisciplinary knowledge and practice, where the result becomes more than merely the sum of the parts. This ‘interdisciplinary’ stage, represented by the synergy of different knowledge domains can conceptually be seen as the evolutionary development of disciplines and their associated professional practices (C. Boehm, 2007). However, it should be noted that multidisciplinary and interdisciplinary practices often exist simultaneously in a field, providing in the extreme both the opportunities of synergy of something new on the one hand, and an addition of existing deep knowledge on the other. This represents a rich environment in which new knowledge and its associated practices are formed for real-world challenges that our contemporary society is facing. MPW work thus adds a new knowledge and professional practice that will hopefully allow us to meet some of the challenges of today’s world.

d) Sharing competencies and capturing change: communication and documentation

Whether choosing a multiprofessional practice, or an interdisciplinary one, the process of formation of collectively shared competencies needs an intentional effort to communicate from one knowledge/practice domain to the other, from one expert/practitioner to the other. Structured communication channels are thus a key element in the toolset of any MPW practitioner.

Leino (2012), writing on the experiences of working in MPW teams as part of the MIMO project, emphasises the shift towards having to manage a collaborative owned knowledge: ‘The traditional concept of expertise is based on emphasizing the individual’s professional skill, which was seen to arise from the individual’s experience of working in the field in question.(…) Collective expertise means a shared kind of competence.’(Leino, 2012)

To facilitate this process of managing a shared collection of competencies, the MIMO project put forward the model below, which acted as a tool for learning, development and MPW work supervision (see Figure 1) and encompasses a concept of collective expertise through teamwork, thus facilitating the sharing of competencies between professionals from different fields (Leino 2012).

Figure 1 - MIMO’s MPW teamwork model, based on problem-based learning, in Leino's (2012)
Figure 1 – MIMO’s MPW teamwork model, based on problem-based learning, in Leino’s (2012)

Thus central to the notion of collectively shared competencies and collective expertise development is the need to have structured communication channels available that support the sharing and combining of different knowledge and values. Communication becomes a vital part, specifically as different professional cultures will not have the same terminologies and concepts or have similar terms and concepts which mean different things whilst also having differing working methods and processes.

Besides the need to maintain structured communication channels to facilitate a process of experienced change, there is also the need to document just this process. Art and social work/care is known to allow and support transformational change, be it of perspective, personal boundaries, self-knowledge and reflection, personal or community identity, empathy or empowerment. However when working in MPW it is useful to ensure that teams are aware that the focus is often predominantly on the process rather than the product. So although artistic integrity and ‘depth’ is needed and even desired, the social contexts requires an artistic experience to provide some form of transformation or change through a process of engaging artistically or creatively. ‘Rather than the artistic end product, the most important aspect of the work was the process by which the opportunities (were) awarded by art’.(Leino 2012)

It might be worthwhile noting, that this emphasis on the creative process, rather than the creative artefact (or end product), as an inherent element of an artistic practice, differs from country to country. Music, as one of the most ‘ancient’ academic subjects has had the least resistance in being accepted as an academic study to PhD level in Universities in UK. But specifically those countries that were at the forefront of artistic subjects being accepted in academic contexts, e.g. those countries in which it has been possible to study Dance, Drama, Theatre and Creative Writing to PhD level, pushed forward the idea of practice-as-research, or PaR. ‘PaR acknowledges the significance of a direct engagement from within the practical activity as an integral part. What is often called a dialogical relationship between the practice on the one hand, and the conceptual and critical frameworks on the other, is integral to PaR. In this, it does have resemblances to methodologies such as action research.’ (Boehm, 2014) With the need for an ongoing dialogue as part of a rigorous, research informed practice, in short ‘praxis’, documentation becomes an integral part of that practice. And this in turn reflects similar good practices identified in the social work/care context. Here, McLaughlin (McLaughlin, 2012) has argued that practitioners should view their practice as research in action whereby they should evaluate their interventions and where practice should inform research and research should inform practice. But the national differences in this area of artistic ‘praxis’ does have ramifications for MPW in that documentation as part of a professional practice might be common knowledge for social work/care professionals, but might not be as inherently understood by all arts professionals.  With a focus on the – by its nature – ephemeral process, it follows that documenting practice also becomes a vital part of MPW work and needs to be considered as part of the competency frameworks.

e) MPW learning improves adoption of MPW methods

Most literature about MPW in healthcare reflects the MOMU philosophy of the experiential value of learning with multiprofessional cohorts of students, and being facilitated to learn by multiprofessional teams of educators. Whether these learning experiences are labelled as interdisciplinary or interprofessional, intra-professional or interdisciplinary-interprofessional (Wiezorek, Sawyer, Serafini, Scott, Finochio in (Wiezorek, Sawyer, Serafini, Scott, Finochio in Lewitt et al., 2015), the underlying plausible assertion is that learning together will lead to an embodied understanding of how to better work together. Part of this is the premise that collaboration is itself a skill-based social process, and thus early experiences of MPW as part of skills and knowledge acquisition is vital. (Clark, 2006; Oandasan & Reeves, 2005a, 2005b)

It is noteworthy that MPW in healthcare is usually with people who are employed by the same employer, work in the same structures and share a common language. This is different from social work/social care and arts professional who are usually employed by different employers who may irregularly come together and have to develop a common language.

To support individual learners develop the team-working skills and competencies, mentoring (Lewitt et al., 2015), peer-led reviewing, peer-mentoring, experiential learning and placement shadowing (Lewitt et al., 2015) all have been identified as effective. Although no empirical study of the efficacy have been carried out, considering the very individualised and specifically contextualised needs of arts and social care/work projects, using a leadership-related-coaching approach with real experiential learning in real-life projects can be expected to become one best practice that supports teams on their own experiential journeys.

IV. Terminological quagmires, or building sandcastles with a shovel

The formation of a new knowledge domain and its professional practice arrives often with the formation of new concepts, words and associations. This terminological quagmire is made more complex when considering it across cultural and country boundaries, with their own cultural heritages and associations. Thus the words ‘multiprofessional’, ‘interprofessional’, ‘competency’, ‘applied arts’ might all seem harmless on their own, but when considered in different cultural contexts, the expert trained and practiced in one country faces the helplessness of being caught in a differently flowing maelstrom of concepts and meanings.

These interdependencies do not exist in isolation but are part of a wider political, cultural and social contexts of nations, both helping to shape and be shaped by these concepts. Language and culture thus often not only enlighten us, but make us humble in the acceptance that words are simply crude tools in our sandbox of quite sophisticated concepts, meanings and truths. Thus the communication of this knowledge, our knowledge exchange of which this article is one attempt, necessarily is like building the most intricate of sandcastles with a large shovel.

Thus it might be worthwhile to explore the complexities of certain terms in relation to different critical and cultural frameworks.

In the English language, ‘multiprofessional work’ is one term of many that is increasingly used to define a concept to describe a way of working with different professional sectors or services. Other terms often found relating to this are ‘interprofessional work’ or ‘interagency work’.

Figure 2 Number of papers using the terms interprofessional, multiprofessional, interdisciplinary or multidisciplinary in the title.( Lewitt and alii (2015), p7)
Figure 2 Number of papers using the terms interprofessional, multiprofessional, interdisciplinary or multidisciplinary in the title.( Lewitt and alii (2015), p7)

Although in MOMU we would normally consider the term to denote a model that necessitates collaborative team-work processes at every stage, in health and social care practices this is not always the case. A ‘consecutive’ working process with case handovers, joint case management, but not necessarily simultaneous collaborative multiprofessional team work, is also often considered to conform to this term, such as is described in various examples in Davis’ pedagogical handbook about multiprofessional work within child services (Davis & Smith, 2012). This might be considered to conform more to the UK-used term of ‘interagency work’, but the fluid and responsive nature of this kind of work and how it moves seamlessly from more linear case handovers to non-linear, simultaneous multi-sector involvement makes it difficult to find one term fitting all specific scenarios and contexts.

Historically, in 1997 the Centre for the Advancement of Interprofessional Education (CAIPE) put forward the definition  that  ‘interprofessional education occurs when two or more professions learn with, from and about each other to improve collaboration and the quality of care’(CAIPE, 1997).

Lewitt (2015) points out that there is a renewed interest in MPW/IPW and they put forward an exponential rise in publications using these terms in key works (See Figure 2). Interestingly they point out that  ‘publications using the terms multi–‐ or interdisciplinary tended to be practice–‐oriented, while approximately 50% of papers using the term interprofessional related to undergraduate or postgraduate education.’(Lewitt et al., 2015) The interdisciplinary underpinning stands out for Lewitt, who wrote: ‘There is lack of consensus and clarity around the use of the terms multiprofessional and multidisciplinary, both in the literature and in practice, and they are often used interchangeably.’

The discussion around the concept of ’multiprofessionality’ and ’multiprofessional work’ is highly topical in Finland where the arts sector has not had a long tradition of cross-sectoral cooperation or even ‘community arts’. This can be seen in public and media debates, in the most of extreme of these the concept of a multiprofessional practice was questioned in terms of disciplinary depth, e.g. from an artistic perspective the doubters put forward the danger of risking artistic integrity. The fear is often expressed in these debates that overwhelming demands on arts professionals would be made, being obliged to be multiply skilled persons or multi-taskers; artists who are at the same time therapists, teachers, counsellors, business managers, salespersons, project experts and so on.

The term multiprofessional seems to have gone out of fashion in the UK as Banks (2010,  p.281) notes: ‘The idea of “multi-professional working” (different professionals working alongside each other) is being replaced by “interprofessional working” (different professionals working closely together, with shared goals and perhaps with interchangeability of roles).’(Banks, 2010)

Of interest to us are the notions of ‘working closely together’, ‘shared goals’ and ‘interchangeability’ The working closely could involve two or more workers jointly sharing a case or a project and doing everything together to the situation of a key worker coordinating the contributions of other workers to achieve an agreed aim. Shared goals whereby the workers would have jointly assessed a need and agreed a plan building on the strengths of both, or more, workers identifying who would do what. Interchangeability is interesting as it suggests the final destination of interprofessional working for workforce analysts might be to question whether the two workers are always needed or whether we need a new type of professional an interprofessional worker or even a non-professional interprofessional worker.

‘Multiprofessional working’, ‘interprofessional practice’, ‘multi-disciplinary working’ or collaborative practice are often used interchangeably but all contain a notion that by working together their will be a pooling of resources, and where the ‘whole is believed to be greater than the sum of the parts’.

In the UK some social work programmes have had dual professional qualification programmes e.g. learning disability nurse and a social worker. However, even though qualified workers were qualified in both disciplines they found it difficult to obtain jobs which used both their skill sets and instead were forced into joining one profession or the other McLaughlin (McLaughlin, 2012b). This also reminds us that professions are not neutral entities and that professions like social work/social care and the arts are involved in an exercise of occupational boundaries claiming control of their own area of practice. Thus change in one profession’s claims may have knock on effects in others (Abbott, 1988).

In England there are 72 approved social work qualifying programmes in social work who enrol approximately 4,500 students per year  (Skills for Care, 2016). As part of the heavily prescriptive curriculum social work students are expected to develop skills in interprofessional practice especially as the failure of the caring professions and the police to work together has been highlighted in all UK child death inquiries since Maria Colwell (1974) to Peter Connolly (Baby P 2007). The Health and Care Professions Council ((HCPC) who currently regulate social work require qualifying and registered social workers as part of their Standards of Proficiency to be able to:

  • be able to work in partnership with others, including those working in other agencies and roles (9.6)
  • be able to contribute effectively to work undertaken as part of a multi-disciplinary team (9.7) (HCPC, 2012:11)

These standards have to be achieved by all qualifying social workers, but are generally seen in relation to working with education, health services and the police rather than with artists. This is not to say that the arts have not been used in social work, for example in the development of ‘life story books’ for children moving to alternative permanent families or the use of art, poetry, drama or music with people suffering from mental illness or dementia. It is just that artistic approaches have never been mainstreamed within social work education or practice. Hafford-Letchfied, Leaonard and Couchman (2012) in their editorial to a special edition of Social Work Education: The International Journal on the use of arts in social work note that although artistic methods are becoming more common they remain underused, connected to the lack of critical mass of evidence for their effectiveness.

The concepts around the term of MPW have thus various dimensions and contexts in which different sets of meanings and associations, and specifically for this project the professional connotations and the national contexts are relevant in order for consistent, but possibly not conform, methods of MPW education to be established.

V. Conclusion

In this first article as part of the three year EU funded MOMU project, we have explored some of the basic critical and cultural contexts in which multiprofessional work in arts and social care resides. As an inherently multidisciplinary practice, emerging from the more interdisciplinary challenges that our complex societies throw at us, it provides challenges to educational providers that derive their historical and cultural understanding from a modernity point of view of prioritising depth of disciplines. We felt that it was necessary to understand this underpinning before moving on to exploring multi- and interdisciplinary learning frameworks that will train the next generation of professionals working in this area.

Our specific learning frameworks will be the subject of a separate article, but from these explorations it becomes already clear that any learning frameworks put forward will need to cover the following aspects, whose critical and conceptual frameworks have been explored in this article:

a) Art as a basic human right (see section II);
b) Creativity and its connection to health and well-being;
c) Learning components that fit into existing organisational structures, as well as make a persuasive case for multiprofessional teaching teams and co-teaching (see section IIIa);
d) Importance of measuring outcomes of MPW work and MPW learning for demonstrating impact (see section IIIa);
e) Ability to address various national and international policy related drivers (see section IIIb);
f) Understand the academic-vocational divide as a myth, and allow experiential learning (see section IIIb);
g) Appreciation of MPW as the professional application of a knowledge domain that derives from multidisciplinary and interdisciplinary methods of enquiry (see section IIIc);
h) Skills related to communication and documentation are part of the professional practice (see section IIId);
i) MPW learning Is most effective as an MPW practice (see section IIIe);
j) Sensitivity to terminological quagmires and respect the interdisciplinary, interprofessional and intercultural interdependencies of terms and concepts (see section IV).

This is an exciting time for multiprofessional learning, and we expect that there will be many possible approaches taken across Europe to explore how best we can train future professionals. We would hope that the MOMU approach will be one of the models that will meet the challenges. Thus, we have covered in this article the specific cultural and critical contexts and propose frame criteria for learning frameworks which inform and develop future training modules in the area of MPW.

VI. Acknowledgements

We would like to thank the ERASMUS+ programme for funding this project, and everyone within the project team as well as all other individuals that have already been involved in, or contributed to the project in various ways, including interview participants, survey participants, workshop attendees or simply people we meet and talk to. The list goes on. We believe this project, which is interfaced between arts, health and wellbeing, is important, and we are thankful to be working in an area where we meet people on a daily basis that are as passionate about arts and well-being as we are. Thank you.

[1]  The idea of the project was developed in cooperation with four European Universities involved intensively in arts and social work provision: Turku University of Applied Sciences (Finland), Manchester Metropolitan University (UK), University of Tartu Viljandi Culture Academy (Estonia) and University of Castilla-La Mancha (Spain).

[2] MIMO was a research and development project running from 2010–2013 funded from the Central Baltic INTERREG IV A 2007–2013 programme, the project developed multiprofessional teamwork models and applied art-based methods for participatory youth work and embedded the approach within its own educational provision and many external youth organisations.

[3] See and (Last accessed 2016/07/23)


Carola Boehm, Manchester Metropolitan University, UK; Associate Dean; MA; C.Boehm(at)
Liisa-Maria Lilja-Viherlampi, TUAS, Finland; Principal lecturer I Culture and Well-being; PhD; Liisa-maria.lilja-viherlampi(at)
Outi Linnossuo, TUAS, Finland; Senior teacher/Social Worker; PhD; Outi.M.Linnossuo(at)
Hugh McLaughlin, Manchester Metropolitan University, UK; Professor; H.McLaughlin(at)
Emilio Jose Gomez Ciriano, Universidad de Castilla-La Mancha, Spain; Professor; EmilioJose.Gomez(at)
Oscar Martinez Martin, Universidad de Castilla-La Mancha; Señor Lecturer; oscar.martinez(at)
Esther Mercado García, Universidad de Castilla-La Mancha; Associate Professor; esther.mercado(at)
Suvi Kivelä, TUAS, Finland; Project manager; suvi.kivela(at)
Ivar Männamaa, TÜ Viljandi Kultuuriakadeemia, Estonia; ivarman(at)
Jodie Gibson, Manchester Metropolitan University, UK; Director Axis Arts Centre, MSc; J.Gibson(at)

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Strategies for evaluating informal science education: Identifying and measuring meaningful indicators of program effectiveness for a mobile laboratory program


The mobiLLab science education program was developed by faculty at the University of Teacher Education in St.Gallen (Pädagogische Hochschule St. Gallen (PHSG)) to spark young people’s interest in science and technology (S&T). During the last 30 years, science centers and mobile laboratories have been developed in response to a decreasing interest in S&T careers among young people (Huber, 2014), something critical to our Digital Age society and workforce (Sjøberg & Schreiner, 2010). Since its inception in 2008, the mobiLLab program has provided secondary school pupils and their teachers in Eastern Switzerland with hands-on training in science experimentation using industry and laboratory equipments. The program also serves as on-the-job training for pre-service science and math teachers at the PHSG, who participate in several school visits as pupil coaches. For the first four years of operation, mobiLLab program staff had regularly received positive verbal feedback from participating teachers and pupils and had more requests from schools than they could visit. Even so, before making changes to the program, mobiLLab leaders wanted to elicit more specific, candid feedback from program participants that could inform program development.

Starting in 2012, mobiLLab team members worked with researchers to better understand the effectiveness of their program. This paper begins with a description of the mobiLLab program and provides detail about a typical visit. The next section describes how, through an exploratory background investigation, program priorities and indicators of effectiveness were identified (Cors, 2013). We then explain how, through a mixed-methods pilot study (Cors et al., 2015), researchers examined these indicators. We further describe findings about pupil and teacher satisfaction with the program; teacher ratings of classroom preparation materials offered on the mobiLLab website; pupil educational outcomes related to S&T interest; and which factors affect these educational outcomes. A final section discusses the advantages and limitations of the methods used, and offers recommendations for future research.

Background: A Program for Inspiring Tomorrow’s Science and Industry Workers

The mobiLLab program was developed to support the PHSG strategy to promote interest in S&T topics and careers among Switzerland’s youth. School visits are designed for pupils aged 14 to 16 who attend secondary school level 1 (German: Oberstufenschule). These pupils generally either pursue further vocational training or transfer into the university preparatory secondary school level II (German: Gymnasium).

A typical visit

A mobiLLab school visit begins at the PHSG building, where the deployment team loads the experimental equipment into a van, shown in Figure 1, and drives to the school. Typically, a class visit with mobiLLab lasts a half a day. The mobiLLab usually stays at a school for one or several days, during which it holds two class visits per day.


Figure 1: The mobiLLab van
Figure 1: The mobiLLab van

MobiLLab brings with it 12 experimental posts, listed in Table 1. During classroom prepration, teachers work with pupils to choose four experimental posts at which they will work and to prepare for the visit by reviewing the corresponding E-Learning tutorial for each post. The E-Learning tutorials are 10- to 13-minute video sequences that introduce the theory, equipment and sometimes applications for each experimental post. The last part of each E-Learning tutorial is a quiz consisting of about 10 questions. Most teachers print out worksheets (Journalblätter) from the mobiLLab website for pupil use. The worksheets include blank spaces for pupils to write down their own hypotheses and questions about the experiments before the visit as well as blank spaces for them to record the results of their experimentation.

Table 1: MobiLLab offers twelve experimental posts.
Table 1: MobiLLab offers twelve experimental posts.

A day for tinkering

The mobiLLab offers pupils an opportunity to work independently and in an evaluation-free environment, something thought to promote engagement in activities and interest development (Boekaerts & Minnaert, 1999; Ryan & Deci, 2000). In contrast to most classroom experiences, where pupils regularly encounter goals, deadlines, tests and other directives, teachers and the mobiLLab team present the mobiLLab visit as a day for trying things out and working in a self-directed manner. Pupils work in pairs, as shown in Figure 2 and, in addition to following step-by-step directions at each post, are encouraged to play around and ‘tinker’ with the equipment. Pupils are asked to try to deal with unexpected results on their own before turning to a mobiLLab coach. This independent problem-solving is supported by inquiry-based responses from mobiLLab coaches, who offer comments and questions (and no direct answers) to support pupils in exploring their own explanations for their observations. Pupils are also encouraged to bring items from home to test. At the Food Analysis Post, for example, pupils test the sugar content of soft drinks and homemade jam. Sometimes pupils bring tap or pond water to analyze via ion chromatography or metal objects to analyze with x-ray fluorescence.

Figure 2.1: Pupils at mobiLLab experimental posts: Exhaust Gas Measurement
Figure 2.2: Pupils at mobiLLab experimental posts: Microwave Synthesis
Figure 2.3: Pupils at mobiLLab experimental posts: Spiro-ergometer

A desire to move forward strategically

In 2011, the mobiLLab operations team made some changes in response to teacher comments. Specifically, the mobiLLab team developed two new items for each post: the E-Learning tutorials that pupils review online before the visit and the laminated step-by-step procedural guides (Kurzanleitung) for each post. Before making other changes to the program, the mobiLLab team wanted to evaluate the effectiveness of the program and to identify factors that promote this effectiveness. What did it mean to be effective? What factors influence mobiLLab’s effectiveness?

Phase I: A Background Investigation

A first step in the evaluation was to identify exactly what it meant for the mobiLLab program to be effective. Researchers worked with mobiLLab faculty and staff to organize a background investigation to explore the program’s priorities and identify measures of effectiveness.


The background investigation took place between October 2012 and April 2013. This discovery work took place in part during mobiLLab visits through observations of and informal conversational interviews with teachers and pupils. In addition, informal interviews conducted using an interview guide, were held in person or over the telephone with mobiLLab team members and representatives from similar programs worldwide. Interview guides were developed based on guidelines from Patton (2002) to conduct informal (not taped), non-structured, open-ended discussions. Interviewees received a list of questions before the interview, in order to encourage reflection and well-thought-out responses. Both informal conversational interviews and script-guided interviews were conducted in German or English, depending upon the preference of the in¬terviewee. Activities also included reviewing mobiLLab program materials, relevant economic trend reports for Switzerland and Europe, and relevant research studies. Figure 3 shows the scope of investigation activities.

Figure 3: Background investigation activities.
Figure 3: Background investigation activities.

This exploratory inquiry provided information that the mobiLLab team used to sketch a ‘logic model,’ or map, showing the logical relationships among the resources invested in the program, the activities that take place, and the benefits or changes that result from them. The mobiLLab team developed the logic model according to a process designed for educational program planning that was developed at the University of Wisconsin-Madison (Taylor-Powell et al., 2003). The logic model expresses the mobiLLab team’s theory of change, which illustrates how the program is supposed to work. Taylor-Powell described how the logic model helps groups use evaluation resources effectively by explicitly describing how program resources and activities are meant to be linked to desired outcomes:

”A logic model is the first step in evaluation. It helps determine when and what to evaluate so that evaluation resources are used effectively and efficiently. Through evaluation, we test and verify the reality of the program theory – how we believe the program will work. A logic model helps us focus on appropriate process and outcome measures” (p. 3).

Results: Articulating their situation

A first step in creating the logic model was for the mobiLLab team to define the situation, or the environment in which the program exists, which is a complex of sociopolitical, environmental, and economic conditions. An accurate understanding of the situation is a foundational part of logic model development in that it identifies forces driving the need for strategic planning and describes the people, resources, and activities related to program challenges. The mobiLLab team formulated the following situation statement:

“In spite of good science and math scores in secondary school (Eichenberger, 2010), young people in Switzer¬land, as in many other developed countries, show low interest in these subjects (Sjøberg & Schreiner, 2010). Moreover, too few young Swiss who show talent in science and math are completing univer¬sity degrees in these disci¬plines and they are choosing non-tech professions or professions outside of industry (MINT-Meter, 2012; Vogel-Misicka, 2012). This trend comes at a time when demand for science and technology graduates is growing, making it necessary for Switzerland to import high-tech and industry workers to remain competitive (High Level Group on Increasing Human Resources for Science and Technology in Europe, 2004; PresenceSwitzerland, 2012). To address the lack of “home-grown” industry and technology workers, mobile laboratory programs have started operating in countries including Germany and Switzerland.

By bringing laboratory experiments, scientists and science coaches into secondary school class-rooms in the German-speaking part of Switzerland, mobiLLab gives pupils an opportunity to expe¬rience inquiry-based science experimentation. Studies conducted in Europe and the US show that visits with mobile laboratories and science centers sometimes result in the development of pupils’ science interest attitude and knowledge immediately after a visit and that any changes tend to fade over a matter of one or two months (Barmby et al., 2005; Brandt et al., 2008; Dowell, 2011; Gassmann, 2012; Jarvis & Pell, 2005; Pawek, 2009).

Now in its fourth year of operation, the mobiLLab team would like to evaluate the program’s effec¬tiveness to inform further development. Specifically, we want to better understand how mobiLLab affects pupils’ science and technology interest, attitudes and knowledge development, and how positive changes can be sustained” (Cors, 2013, p. 4).

Results: The core program aim is to awaken youth interest in S&T

In the logic model, or theory of change shown in Figure 4, outcomes and assumptions that the mobiLLab team believed to be most influential to program success are shown in bold. The logic model shows, for example, how classroom preparation, shown as an Action Outcome, is important for helping the pupils know what to expect, reducing anxiety and promoting curiosity about the mobiLLab visit, a Learning Outcome. This enables pupils to better engage in activities at experimental posts, which causes them to ‘become more technophillic,’ a Condition Outcome. Becoming more technophillic is an important step towards maintaining interest in S&T, which the mobiLLab team believes makes it more likely that pupils will later choose related careers, another Condition Outcome.

Through this logic modeling process, mobiLLab team members confirmed that awakening pupils’ interest in doing science with technology, or pupils becoming more technophillic, is the core goal of the program. During background investigation interviews, stakeholders including teachers, industry representatives who visited classes during mobiLLab events, and mobiLLab team members, explained that awakening pupils’ interest involves promoting multiple views of the relevance of S&T in their lives. They spoke about fostering development of pupils’ basic interest in S&T; their awareness of it in the world around them; how it is useful in society; and their comfort level with it. Similarly, studies often couple measures of science interest with measures of attitude and self-concept of ability related to S&T (Denissen et al., 2007; Dowell, 2011; Dresel & Lämmle, 2011; Potvin & Abdelkrim, 2014). Even though some elements of the logic model were somewhat roughly expressed, it provided a centerpiece for discussion among mobiLLab staff and researchers that informed identification of program effectiveness measures.

Figure 4: The logic model illustrates the mobiLLab program Theory of Change (Cors, 2013).
Figure 4: The logic model illustrates the mobiLLab program Theory of Change (Cors, 2013).

Results: Indicators of program effectiveness

Based on several logic model elements, the mobiLLab team identified a list of indicators of program effectiveness, which would be practical to measure during a research investigation. One indicator, participant satisfaction, is reflected in several logic model outcomes, such as ‘pupils feel engaged…’ and ‘teachers continue to request mobiLLab.’ A second indicator, usefulness of classroom preparation materials, comes from the logic model assumption that the level of the E-Learning tutorials is appropriate for pupil learning and from the Learning Outcome that ‘teachers learn how to prepare for the mobiLLab visit.’ A final indicator was change in pupils’ affective educational outcomes, to be measured as S&T interest, attitude and self-concept of ability. The literature review conducted in conjunction with the background investigation helped researchers identify existing instruments that could be adapted for use in the mobiLLab pilot study to measure these aspects of program effectiveness. The specific instruments that were used to measure each indicator, along with the source for each, are listed in Table 2.

Table 2: Measures of effectiveness for some mobiLLab program outputs and outcomes.
Table 2: Measures of effectiveness for some mobiLLab program outputs and outcomes.

Results: Factors thought to affect pupils S&T interest development

Drawing on results from the logic model and the literature review, the mobiLLab research-faculty team identified factors they thought had the greatest influence on pupils’ affective educational outcomes. These factors included pre-visit classroom preparation activities; pupils’ feelings of novelty, or unfamiliarity; and teachers’ attitudes about learning approaches. The process for identifying these factors is shown in Figure 5 and each factor is described below.

Figure 5: Process for identifying factors that affect pupils' development of S&T interest.
Figure 5: Process for identifying factors that affect pupils’ development of S&T interest.

Classroom preparation. Classroom preparation was seen as critical to program effectiveness. The mobiLLab team’s hypothesis, shown in the logic model, was that a more complete classroom preparation would better help pupils know what to expect at the visit and therefore support their engagement in visit activities, which would, in turn, improve their S&T interest. Similarly, several studies of informal science learning programs provide evidence for a link between a more complete classroom preparation and development of educational outcomes, which sometimes related to pupils’ exploratory behavior at the program visit (Anderson & Lucas, 1997; Cotton & Cotton, 2009; Jarvis & Pell, 2005; Kubota & Olstad, 1991; Orion & Hofstein, 1994).

Novelty. The mobiLLab theory of change emphasizes classroom preparation because it increases pupils’ familiarity with the schedule and objects they will encounter at the visit, which should lower their anxiety and heighten their curiosity about the visit. This improved familiarity should, in turn, enable pupils to better engage in at-visit activities, which should promote development of more positive interest in S&T. Evidence for such a link between increased familiarity, or reduced novelty, and the effectiveness of informal science education program has been produced by several studies. These studies indicate that pupils’ individual novelty factors, such as relevant content knowledge or familiarity with the informal learning setting, related significantly to more on-task behavior at the visit and to the development of more positive educational outcomes (Anderson & Lucas, 1997; Falk & Balling, 1982; Falk et al., 1978; Jarvis & Pell, 2005). Based on this, mobiLLab investigators identified three novelty impact factors thought to most influence how novel pupils found the mobiLLab experience: 1) a cognitive factor, measured as pupils’ grades, 2) a setting orientation factor, measured as frequency of pupils visits to informal learning venues, such as museums and science centers; and 3) a technological capability factor that reflects whether pupils’ explore and tinker, or to seek direction and support, when interacting with technology. As already mentioned, the first two factors have been examined in previous studies of informal science learning. The capabilities impact factor became part of the research design in response to interviews and conversations with mobiLLab program faculty and staff during and after the background investigation. They explained that they wanted to have a better understand how pupils feel about working with technology. The technological capability construct was chosen because it is an indicator of how capable people feel interacting with technology. It was developed as part of the Technological Profile Inventory (TPI), which supports a South African university admissions process that sought to admit engineering students with the best chance of success (Luckay & Collier-Reed, 2011).

Teacher Attitude. As an assumption in the mobiLLab logic model shows, mobiLLab team members also thought that teacher attitude influenced pupils’ interest. The great influence of teacher attitude on what pupils gain from an informal learning experience was also emphasized in interview responses from leaders of similar programs worldwide (Cors, 2013). Teacher attitude and teaching approach as a key to improving educational outcomes is not a new idea and, as early as the 1960s, the United National Educational, Scientific, and Cultural Organization recognized the “essential role of teachers in educational advancement and the importance of their contribution to the development of man and modern society” (ILO & UNESCO, 1966, p. 20). Based on a previous study of how teacher attitudes are linked to how pupils learn physics, investigators selected two factors to examine: teachers’ attitude to situational learning and to constructivist learning (Kuhn, 2010).

Phase II – Pilot Study

A mixed-methods pilot research investigation was developed to examine how classroom preparation, pupil novelty factors, and teacher attitude related to pupils’ affective educational outcomes. Affective educational outcomes, called ‘core S&T outcomes,’ were measured as interest in, attitude to, and self-concept to S&T. The investigation was designed to explore the questions, ‘How do differences in classroom preparation and in pupils’ novelty factors relate to changes pupils’ core S&T educational outcomes from before to after a mobiLLab visit?’ and ‘What moderating role do teachers’ attitudes play?’ The study also presented an opportunity to examine measures of program effectiveness.


The mobiLLab pilot study took place in Spring 2014. Data collection involved 9 teachers and 15 of their class groups who experienced a mobiLLab visit. All 9 teachers and 208 pupils completed pre- and post-visit surveys, which occurred in January and one week after their mobiLLab visit, which occurred from February to May, respectively. Teachers also participated in post-visit interviews.

Pupil survey. Pupils responded to survey items about their core S&T outcomes, their individual novelty factors, and opinions about the mobiLLab program. They rated these items using a 4-point Likert scale: “1”=completely untrue (“stimmt gar nicht”), “2” = somewhat true (“stimmt wenig”), “3” = very/quite true (“stimmt sehr”), “4” completely true (“stimmt völlig”). Examples of survey items are shown in Table 3. All of these items were borrowed from other pupil surveys and were adapted to the mobiLLab pilot surveys through a review process that involved mobiLLab program leaders, to ensure that the language would be appropriate for participating pupils. A group of eight testers, including four teens who attended school in the same provincial areas as mobiLLab pupils, completed a draft of the survey and provided feedback to improve understandability.

Table 3: Example items from the pupil survey of the mobiLLab pilot study.
Table 3: Example items from the pupil survey of the mobiLLab pilot study.

Paired t-tests were employed to assess whether pupils’ interest, attitude and self-concept regarding both science and technology changed significantly between pre- and post- visit surveys (when p<0.05). For significant changes, Cohen’s d was calculated to indicate the magnitude of the change, called effect size, which can be interpreted based on guidelines from Cohen (1998): small d=0.2, medium d=0.5, large d=0.8. Relations between impact factors, such as technological capability, and educational outcomes were explored through multivariate analysis of regression (MANOVA). Results are reported as F values, a comparison of group means for tinkers and direction seekers. For significant relations, an effect size is given as partial eta squared, Ƞp2, which can be interpreted from guidelines from Cohen (1988): small Ƞp2=0.01, medium Ƞp2=0.06, large Ƞp2=0.14.

Teacher interviews and survey. Teacher interviews took place at schools where teachers worked and lasted 30 to 40 minutes. The aims were to characterize classroom preparation and better understand teachers’ experiences with the mobiLLab program. Interviews were developed and conducted according to guidelines from Patton (2002) in a semi-structured manner. This involved following a scripted list of questions and sometimes diverging from the script when opportunities arose to talk with teachers about suggestions for program improvement. It was clear beforehand that there would not be enough time during the interviews for teachers to comment on each of the classroom preparation resources available on the mobiLLab website. In anticipation of the limited time, the interviewer (first author) asked teachers about the four resources thought to be most used by teachers: the introduction to mobiLLab PowerPoint presentation (Einführung ins mobiLLab), E-Learning, the worksheets (Journalblätter), and the step-by-step instructions for working at each post (Kurzanleitung). If other resources were discussed, these conversations were generally initiated by the teacher.

Through an online survey, teachers responded to questions about their preparation and rated four of the materials thought to be most frequently downloaded from the mobiLLab website and used for classroom preparation. These materials were the introduction to mobiLLab PowerPoint presentation (Einführung ins mobiLLab), E-Learning, the worksheets (Journalblätter), and the step-by-step instructions for working at each post (Kurzanleitung). Teachers rated these website materials based on four criteria: appropriate level and language for pupils; clarity and understandability for pupils; whether the material was edited by the teacher prior to use in class; and appeal to pupils. They rated the materials using a four-point Likert scale to indicate for example, how clear and understandable each item was: 1= not at all (stimmt gar nicht), 2 = somewhat (stimmt wenig), 3= quite (stimmt ziemlich), 4= completely (stimmt völlig).

Teacher sample and intervention

It was expected that survey responses from teachers about classroom preparation would differ between treatment teachers, who received additional preparation materials, and control teachers, who received no additional preparation materials. However, teachers’ accounts of their preparation did not vary significantly for most factors, such as which mobiLLab website materials they used during classroom preparation and their attitudes toward situated learning. In fact, classroom preparation time was the only aspect from which a preparation typology could be created. Four preparation types, shown in Figure 6, were defined based on duration and number of classroom lesson-hours (45 minutes each) devoted to preparation.

Figure 6: A classroom preparation typology was based on duration and lesson-hours.
Figure 6: A classroom preparation typology was based on duration and lesson-hours.

One explanation for the low variability of materials used by teachers for classroom preparation could be the small sample of (9) teachers. An even more likely reason was that, even though the mobiLLab manager shared new preparation materials with only five of the teachers (treatment group), other teachers (control group) sometimes gained access to these same resources. This sample ‘contamination’ is illustrated in Table 4, which shows how control group teachers used most of the new preparation materials, likely acquired from colleagues in the treatment group who worked at the same school. All new resources except for the novelty space triangle were used by at least one control group teacher. Because of the popularity of some of the new resources with teachers, such as the Planning Guide, they became a permanent part of website materials the mobiLLab program offers for classroom preparation.

Table 4: Preparation resources offered to treatment group teachers (N=5) were used by both control and treatment group teachers (N=9).
Table 4: Preparation resources offered to treatment group teachers (N=5) were used by both control and treatment group teachers (N=9).

Pupil sample

Responses from pupils (108 male; 97 female; 3 no response) about core S&T outcomes from the pre- and post-visit survey are shown in Figure 7. Pupil ratings of technology-related core S&T outcomes showed slight or insignificant changes. That is, pupils’ interest in technology was moderate and decreased significantly from pre- to post-survey, with small effect, (M=2.55->2.43, p<.001, Cohen’s d=0.18). In contrast, their attitude was somewhat positive and showed no significant change (M=3.04->3.07; p=.284), and their somewhat positive self-concept decreased significantly, with small effect, (M=2.86->2.80, p=.006, Cohen’s d=0.10). Responses about natural science were similar: pupils indicated a moderate interest in natural science that decreased significantly, with small effect, (M=2.52->2.44, p=.005, Cohen’s d=0.13); a somewhat positive attitude that showed no significant change (M=2.94->2.97; p=.384), and a somewhat positive self-concept that decreased significantly, with small effect, (M=2.87->2.82, p=.046, Cohen’s d=0.09). These results reflect the collective results from other studies of science learning at mobile laboratories and science centers, which show that pupils interest sometimes decreases and sometimes increases, and that these changes often fade over time (Barmby et al., 2005; Brandt et al., 2008; Dowell, 2011; Guderian, 2007; Jarvis & Pell, 2005; Pawek, 2009; Sasson, 2014).


Figure 7: Pupils’ S&T interest, attitude, and self-concept; mobiLLab pilot study sample (techn=technology; ns=natural science).
Figure 7: Pupils’ S&T interest, attitude, and self-concept; mobiLLab pilot study sample (techn=technology; ns=natural science).

Results: program satisfaction and classroom preparation materials

This section begins with a description of findings from an improved version of the pupil pre- and post- surveys (N=215) completed in 2015. Qualitative data from the pilot study provides further insights into participants’ program satisfaction. Also described are teachers’ ratings about the usefulness of frequently used preparation materials.

Program satisfaction
Pupils’ program satisfaction was measured through a grade they gave the mobiLLab program and through several question about how they liked the mobiLLab visit. Pupils gave their mobiLLab experience an average grade of 4.8 (SD=0.9), which is more than a full grade higher than the grade they gave the mobiLLab in 2010 (M=3.2, SD=1.5), as shown in Figure 8. MobiLLab team members attributed this improved grade from mobiLLab pupils largely to the addition of the E-Learning and step-by-step procedural guides (Kurzanleitung) for each post in 2011. MobiLLab team leaders also point to other factors that could have contributed to this increased program satisfaction: there are more teachers each year who have worked with mobiLLab in a previous year and can therefore better support pupils to prepare for the visit; new posts, such as Food Analysis, are easier to operate and can test more items from home; and recent additions of new objects, such as a prism to the Visible Light post, which appear to be popular with pupils.

Figure 8: Pupils gave mobiLLab a higher grade in 2015 than in 2010.
Figure 8: Pupils gave mobiLLab a higher grade in 2015 than in 2010.

Pupils’ responses to three questions about their satisfaction, shown in Figure 9, indicate that their mobiLLab experiences were fairly positive. On average, pupils gave a positive rating for liking the visit (M=3.1, SD=0.8). Responses about whether they would like to participate in another mobiLLab visit were slightly better than neutral (M=2.7, SD=1.0). Finally, pupils thought they had to work at least as hard during the mobiLLab visit as they usually do during science class (M=2.4, SD=0.8). These findings suggest that pupils liked their mobiLLab experience, even though it involved some work. This supports the assertion by researchers that informal learning is more than just play, offering an environment where learners work but also enjoy themselves (Rennie, 2007).

Figure 9: Pupils worked about as hard during the mobiLLab visit as they do in their regular science class, and still liked the mobiLLab day very much.
Figure 9: Pupils worked about as hard during the mobiLLab visit as they do in their regular science class, and still liked the mobiLLab day very much.

During interviews, several teachers explained that during classroom discussions after the mobiLLab visit, pupils also voiced positive feedback about the program. Teachers themselves also indicated that they were satisfied with the program, with about half of teachers expressing (unsolicited) interest in another mobiLLab visit. Teachers said mobiLLab is valuable to them because it offers pupils a chance to work with equipment and materials the schools do not have and because pupils can develop and implement their own ideas.

Results: Teacher ratings of classroom preparation materials

Teacher responses about classroom materials, shown in Figure 10, were relatively encouraging. They found the Introduction to mobiLLab to be at a good content level (M= 3.4, SD=0.7), clear and understandable (M= 3.4, SD=0.7), interesting and exciting for pupils (M= 3.2, SD=0.7), and did not need much changing before use (M= 1.6, SD=1.1). Similarly, teachers rated E-Learning online tutorials as having a good content level (M= 3.3, SD=0.9), as clear and understandable (M= 3.1, SD=1.0), interesting and exciting for pupils (M= 3.4 SD=0.7), but indicated they could use some modification (M= 2.2, SD=1.0). The post step-by-step instructions received ratings that were almost as good, with teachers indicating a good content level (M= 2.9, SD=0.9); clarity and understandability (M= 2.9, SD=0.7); that they were interesting and exciting for pupils (M= 3.0, SD=0.6); but that they could use some adjustment before use (M= 2.1, SD=1.2). The Journalblätter worksheets received more moderate reviews. Teachers indicated that they had a good content level (M= 3.1, SD=1.1); were clear and understandable (M= 2.9, SD=1.1); were somewhat interesting and exciting for pupils (M= 2.7, SD=0.5); but indicated they needed some adjustment before use (M= 2.3, SD=1.2). During interviews, teachers offered specific suggestions about modifying the Journalblätter worksheets that led to a major shortening and revision of this resource. Also in response to specific suggestions offered during interviews, the mobiLLab team managers revised several other online resources, reorganized the website, and added some information to teachers’ orientation materials.

Figure 10: Teachers' ratings of four frequently used preparation resources on a scale of 1 to 4.
Figure 10: Teachers’ ratings of four frequently used preparation resources on a scale of 1 to 4.


Results: Factors that affect pupils’ educational outcomes

Results of a multivariate analysis of regression (MANOVA) indicated that two factors affected how pupils’ core S&T outcomes changed from before to after the mobiLLab visit. These two factors were preparation time and pupils’ perception of their technologically capability.

Preparation time. Preparation time had an overall small effect on core S&T outcomes, ɳp2 =.03. A closer look through post-hoc tests suggest that pupils who experienced a preparation that started closer to the mobiLLab visit and involved more classroom time (’duration short, lesson time high’), showed significantly greater interest (science, p=.049; technology, p=.012) and had a more positive attitude (science, p=.011; technology, p=.010). These results could suggest that when preparation starts too early, pupils have difficulty recalling preparation lessons and feel unprepared for the visit. Also, more classroom time may simply give pupils more opportunity to become familiar with relevant content, equipment, and the schedule for the visit. Qualitative data provide insights into how prepration time can be used most effectively. That is, during pilot study interviews, teachers emphasized that an effective preparation 1) involves pupils reviewing the E-Learning tutorials; 2) relates mobiLLab to pupils’ interest; 3) relates classroom activities and assignments to mobiLLab; and 4) orients pupils to the plan for the day.

NOTE: Data about teacher pre-visit attitudes about the importance of situated (M=2.9, SD=.06) and constructivist (M=2.8, SD=.04) learning did not change significantly from before to after the mobiLLab visit. Also, teacher attitudes were not found to be significant moderators of the relation between impact factors and pupils’ core S&T outcomes.

Comfort with technology. Pilot study findings suggest a link between pupils’ comfort with mobiLLab equipment and engagement with mobiLLab visit activities. That is, during interviews, several teachers talked about how pupils’ engagement with mobiLLab activities depended upon them becoming comfortable with the idea of handling equipment, without for example breaking something.

Quantitative data also suggest that pupils’ comfort interacting with technology is linked to their program experience. Specifically, findings showed that more technologically capable pupils (tinkerers), reported significantly different changes in their core S&T outcomes, from before to after the mobiLLab visit, than direction seekers (medium effect: ɳp2 =.05). Follow-up ANOVA tests for individual outcomes revealed significant relations between technological capability and changes in pupils’ interest in and self-concept to technology. That is, pupils’ technological capability accounted for differences in how their interest in technology changed from before to after the mobiLLab visit with small effect, F(1,199)=5.69, (p=.018), Ƞp2=.028. As illustrated in Figure 11, tinkerers had more positive interest in technology than their direction-seeking peers. However, tinkerers’ interest in technology decreased slightly from pre- to post-visit, while direction-seekers’ interest remained unchanged. This could mean that tinkerers were bored or that somehow their expectations for the visit were not met. These results could also reflect a trend of decreased interest in science with age, a phenomenon identified in other studies of similar programs (Barmby et al., 2005; Guderian, 2007). This interpretation is based on the fact that there was a timespan of five to twenty weeks between pre- and post-visit surveys, depending upon when the mobiLLab visit for a given class took place.

Figure 11: Tinkerers’ interest in technology decreased slightly from before to after the mobiLLab visit, while direction-seekers’ interest remained steady.
Figure 11: Tinkerers’ interest in technology decreased slightly from before to after the mobiLLab visit, while direction-seekers’ interest remained steady.

ANOVA results also show that pupils’ technologically capability accounted for small but significant differences in changes in pupils’ self-concept to technology, F(1,199)=3.90, (p=.050), Ƞp2=.019. This effect is illustrated in Figure 12, which shows how tinkerers started with greater self-concept to technology than direction-seekers. However, direction-seekers’ self-concept decreased significantly more than than tinkerers’ self-concept to technology, which remained virtually unchanged. One could imagine that direction seekers felt less comfortable with the equipment at the mobiLLab visit and/or perhaps overwhelmed by the challenge of using it, which caused them to feel frustrated and therefore disengage with the activity.

Figure 12: Tinkerers’ self-concept to technology remained steady from before to after the mobiLLab visit, while direction-seekers’ self-concept decreased.
Figure 12: Tinkerers’ self-concept to technology remained steady from before to after the mobiLLab visit, while direction-seekers’ self-concept decreased.

There was no significant relationship between pupils’ technological capability and changes in their attitude to technology, F(1,199)=.147, (p=.702). Also technological capability did not account for differences in changes in pupils’ natural science educational outcomes F(3,195)=.41, (p=.746). Likewise, pupils’ science grades, math grades, and how often they visited other informal learning programs were not significantly linked to how their core S&T outcomes changed.

Summary and outlook

The mobiLLab team sought to identify and measure indicators of program effectiveness that were meaningful for their work in the field. Through an exploratory background investigation, indicators of program effectiveness were identified: participant satisfaction, usefulness of mobiLLab website materials for classroom preparation, and changes in pupils’ S&T interest, attitude and self-concept from pre- to post-visit. These indicators were examined through pupil and teacher surveys and teacher interviews during a pilot research investigation. Findings about program satisfaction produced encouraging results, indicating that pupils and teachers were satisfied overall with their mobiLLab program experience and that pupil satisfaction improved over time. Results also showed that teachers are generally pleased with classroom preparation materials provided on the mobiLLab website and offered useful input for improving these resources.

Like results from other studies about informal science education programs, our results showed that pupil’ S&T interest, attitude and self-concept changed slightly or not at all significantly from before to after the visit. Fortunately, the investigation also explored factors that influence these outcomes. Results show that classroom preparations that began less than 15 days before the mobiLLab visit and lasted longer than eight lesson hours were linked to more positive pupil S&T interest and self-concept. This offers evidence that the time invested by the mobiLLab team in developing preparation materials and by teachers in conducting classroom preparation activities is worthwhile.

A second factor that predicted how pupils’ S&T outcomes changed from before to after the mobiLLab visit was their comfort interacting with technology. That is, findings provide evidence that interest in and self-concept to technology for tinkerers, or pupils who see themselves as more technologically capable, changed differently than their direction-seeking peers. The nature of these differences was unexpected. It was perhaps no surprise that tinkerers had greater S&T interest, attitude, and self-concept than direction seekers. However, tinkerers’ interest in technology decreased slightly, while direction seekers interest remained unchanged. In contrast, tinkerers’ self-concept of ability with technology remained steady, while direction seekers developed a slightly lower self-concept of ability with technology. Qualitative data also point to how pupils’ comfort with technology affects their mobiLLab experience. That is, during pilot study interviews, teachers asserted that the more comfortable pupils feel with the mobiLLab equipment, the better they engage in activities and profit from the visit. Through the lens of novelty, this could mean that the mobiLLab needs to offer more appealing novelty, such as a more authentic laboratory environment with lab coats and clipboards, to attract pupils’ interest. Perhaps additional ‘whacky challenges’ need to be added to maintain the interest of tinkerers and keep them from being bored. In contrast, for direction-seekers, mobiLLab could try to reduce unfamiliarity by offering more opportunities for pre-visit practice with equipment and/or some simple tasks at the mobiLLab visit with which they can succeed. These activities could reduce how overwhelmed and intimidated direction-seekers feel and boost their self-concept. Future studies should examine how these approaches affect learners’ S&T interest and self-concept of ability.

The mobiLLab pilot study was designed based on the idea that classroom preparation reduces unfamiliarity and promotes at-visit engagement, which, in turn, promotes the development of S&T interest. This link between learners’ novelty factors, at-visit experience, and their educational outcomes has been put forth by several models for informal learning research, yet few studies have measured learners’ at-visit experiences. Future studies should examine how individual novelty factors, such as technological capability, relate to how learners perceive novelty during a visit, measured through indicators such as exploratory behavior, oriented feeling, cognitive load and curiosity feeling. Such studies would demonstrate, for example, whether a novelty-reducing preparation indeed improves how oriented pupils feel at a science center visit. By examining relations among learner novelty impact factors, at-visit novelty factors, and educational outcomes, studies can deepen our understanding of the role of novelty in informal learning.

The investigation process and findings offer a model that can inform other informal learning programs about evaluating their own programs. The investigation followed many of the criteria that are part of quality research to evaluate science education (Bennett et al., 2006). For example, by exploring mobiLLab program priorities and goals with team members and other program stakeholders, researchers developed measures of program effectiveness that represent the real-world challenges of an informal science education program. And by involving mobiLLab team members and local youth in developing and testing measurement instruments for the pupil survey, they felt relatively confident that they collected responses from pupils that match what they aimed to measure. Collecting teacher responses through both interviews and an on-line survey is a form of data triangulation that contributed to the validity of some variables. Moreover, data was collected both before and after the mobiLLab visit and the pilot study involved a moderately large pupil sample.

Investigators also learned about the challenges of studying informal learning programs, including some factors that commonly limit such studies, which must often organize research activities to conform with classroom pupil groupings and course schedules (Bell et al., 2009; Brownell et al., 2013). For example, the pilot study did not include a control or comparison group, so conclusions cannot be made about whether educational outcomes from a mobiLLab visit are different from outcomes that result from classroom learning. Also, pupil and teacher samples were not chosen randomly, but consisted of those classes whose teachers made the extra effort to request a mobiLLab visit. It is also worth noting that the one-time, transient nature of informal learning programs like mobiLLab introduces questions about whether findings are the result of the program experience or of other factors in learners’ lives. That is, during the pre- and post-visit surveys, pupils could have encountered other classroom lessons or out-of-school experiences that influenced their science interest, attitude and self-concept.

A final note is about the high-technology nature of some informal learning programs, which reflects how technology has become more prevalent in our lives. The mobiLLab evaluation reveals that pupils’ interest in and self-concept to technology are different from how they view science, depending upon their perception of how technologically capable they are. By recognizing these links, studies about mobile laboratories and science centers can help us better understand how we are preparing young people for life in the 21st century, much of which is high-tech. How technologically capable pupils see themselves as has been recognized as an important skill for thriving and contributing to Digital Age societies. The National Academy of Engineering (NAE) and US National Research Council (NRC) described technological capability as one of three dimensions of technological literacy, which consists of dimensions of capabilities, knowledge, and critical thinking. They explain how technological literacy has become a critical aspect of how people function in and support today’s economy and society (Garmire & Pearson, 2006):

“There are a number {of benefits of technological literacy} … some of the most important relate to improving how people—from consumers to policy makers— think and make decisions about technology; increasing citizen participation in discussion of technological developments; supporting a modern workforce, which requires workers with significant technological savvy; and ensuring equal opportunity in such areas as education and employment for people with differing social, cultural, educational, and work backgrounds” (p. 22).


Rebecca Cors*, University of Teacher Education, Institute for Teaching Natural Science, Switzerland, rebecca.cors(at)
Nicolas Robin, University of Teacher Education, Institute for Teaching Natural Science, Switzerland, nicolas.robin(at)

*corresponding author

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Developing new models for earning study credits from daily work – challenges in developing competence in nursing education

Clinical learning of nursing students in Finland

In Finland, students study to become registered nurses for 3.5 years (210 ECTS) in universities of applied sciences. At the EU level, clinical practice covers at least 50% of the total degree. During their education and particularly in clinical practice situations, it must be ensured that nursing students are able to prepare their skills in evidence-based nursing (Ministry of Social Affairs and Health, 2012). There is a need for special learning situation arrangements in the context of health care and social services. Typically, nursing students carry out clinical practice as unpaid workers, acting as ‘extra’ persons in the workplaces, not included in staff resources. This is supposed to allow students a chance to have better circumstances for the placement and give them time for learning. One of the reasons that, for example, nursing students may not get opportunities to practice their competencies in their work as paid employees in the fact that, in Finland, nursing students are allowed to work as a fill-in for a registered nurse only once they have completed at least 140 ECTS of their nursing studies. The law contains many restrictions concerning health care and social service workers who have not yet graduated regarding what they are allowed to do in their work.


For instance, if the nursing student is allowed to perform some task during his or her clinical practice before reaching certain level of studies, they must be accompanied by an employee qualified for the task, who in turn shall take the responsibility of guiding the student to conduct the task in an appropriate and safe way. Registered nurses, referred to as the students’ mentors, guide and assess nursing students in the clinical practice situations; however, in Finland, university-educated teachers are also responsible for guiding and assessing the students during their clinical placements (Ministry of Education, 2006).

Competence Areas

Nursing students must be trained to meet medical standards and have competence in nursing diagnoses and interventions (Eriksson et al., 2015). However, according to Kajander-Unkuri et al. (2013), specific competence areas in nursing are yet to be defined in the European Union. For example, Gardner, Hase, Gardner, Dunn & Carryer (2007) have argued that there are limitations to the use of a competency-based assessment: Nurses may have knowledge accumulated through education and experience, but they may nevertheless be unprepared to use it in their clinical practice actions. The nursing students’ capability describes their ability to use their competencies in novel as well as familiar circumstances. Rochester, Kilstoff & Scott (2005) found that while capability in technical skill is required in successful practice as a nurse, the capabilities of social and personal ‘emotional intelligence’ are also significant. The highest-ranked item in Rochester et al.’s (2005) important study was the interpersonal aspect of emotional intelligence, which was defined as ‘ability to empathize and work productively with people from a wide range of backgrounds’. Mentors in clinical placements spend a lot of time with students, which puts emphasis to their ability to assess how the students manage combining theoretical knowledge with the real word of nursing.

Verkkovirta project and nursing students’ learning by working

The goal of the Verkkovirta project, financed by the European Social Fund, is to develop new models that allow students to earn study credits from daily work. Haaga-Helia School of Vocational Teacher Education coordinates the project, while the subprojects are implemented in Saimaa and eleven other universities of applied sciences. (Verkkovirta 2016.)

Competencies required by a degree in nursing can be obtained both in the classroom and in the workplace. Therefore, new innovative methods are needed. In different fields of education, there is a need for different and novel arrangements of education. Indeed, this project has excellent potential to develop good practices that combine work and study. When nursing students obtain study credits for their daily work as employees, it must be ensured that successful practice is underpinned by the graduates’ ability to integrate and consistently apply a number of capabilities beyond profession-specific skills and knowledge. For example, Bisholt et al. (2014) and Stayt & Merriman (2013) have argued that nursing students may not get consistent opportunities and experiences of clinical skill development in their clinical placements, which may have consequences on nursing students´ learning and competency development. This might cause difficulties in placing students effectively in clinical contexts to ensure maximal learning opportunities (Walker et al., 2011). Through the placements, nursing students get to work in very different kinds of hospitals, nursing homes, home care etc. It is challenging to analyze what kind of possibilities they have during these placements to achieve certain kinds of competency and what is the level of these competencies.

Managers’ perspectives of the possibility of earning money and completing a degree at the same time

One of the roles of Saimaa University of Applied Sciences in the Verkkovirta project was to investigate working organizations’ perspectives of development needs in situations where students are able to receive payment for their work while at the same time have possibilities to build their competency for degree purposes.

Data collection and data analysis

Ten managers in different kinds of health care and social services (public, private and third sector) were contacted by visiting them personally at their workplaces. The purpose of the visits was to find out about the managers’ opinions of this aim. Interviews were held as dialogical discussion sessions, and the author was taking notes at the same time. After each interview, the notes were supplemented by the author to make them more accurate. The written data were analyzed by content analysis and themes were formed by combining the managers’ conceptions of the development needs related to this new way of earning money and studying at the same time in clinical situations.

Permanent worker as a nursing student

It has been common in nursing and social service organizations that when a worker holds a permanent position, he or she might get opportunities to combine some of their studies in higher education with their current job, getting to complete some study assignments, such as clinical practice periods or theoretical tasks at their workplace. For example, if the student has been working in a hospital or home care as a practical nurse, they can complete parts of their registered nurse education at the same workplace. The interviewed managers reported that they support workers who want to advance their studies in health care or social services. In some cases, workplaces may even have offered to change the student’s job description to provide them with more opportunities to use the working periods for educational purposes during the education. The support of colleagues plays an important role, as such arrangements may also effect the entire workplace. Managers highlighted that the main responsibility of employees is to perform their normal tasks at the workplace, and situations supporting the education may be arranged if the main work situation allows this without any major problems. The main focus must be on clients and patients, not just educational purposes.

The managers suggested that it is easier to manage simultaneous work and degree-earning when the worker conducting studies is has a permanent job contract. Nevertheless, managers also planned and provided options for temporary workers to combine their work and studies, for example, in some cases, work tasks could be arranged just for a given student. For example, a nursing student may have a summer job in home care of which, each week two or three days could be arranged to include certain type of work for the mere purpose of helping the student reach the level of competence required by their degree. Managers described that this might influence the students’ motivation as workers in the organization not only during the work practice period, but also later. Most of such arrangements could be facilitated by a multi-professional workplace where there are employees working in the profession pursued by the student. In fact, the managers highlighted the possibilities for students to collaborate with professionals during their work practice periods and the fact that it is not always possible if they are paid workers and not the ‘extra people’ as students with no financial impact to the organizations as usually.

Multi-professional mentoring

Especially in small working places, the managers also brought up the question of the mentor having the ‘same profession as the student. Educational institutes typically require for the workplaces where health care and social services students practice their skills of competency to provide the student with a mentor in the same profession as the one which the student is working towards. Mentoring could also be arranged at times by providing multi-professional mentors; however the mentor who bears the responsibility of the student’s final assessment at the end of the clinical practice period should be in the profession as the one for which the student is studying. Managers shared the opinion that it should also be possible that, for example, a registered nurse should be allowed to assess a physiotherapist student’s ability to work in certain circumstances. The question of the managers was that ‘what is the problem of the multi-professional assessment’.

Mentoring resources

In order to successfully combine work and achieving competency for educational purposes, the importance of proper guidance and mentoring was highlighted. The managers argued that it is important for mentors to have more knowledge, for example, of the nursing education curriculum and skill requirements set for nursing students. There was also an apparent need for mentors to enhance their skills in assessing nursing students’ competence in clinical situations. Therefore, there is a need for instructions from educational institutes to the work placement sites. The main question seems to concern timing problems: mentors have a lot of responsibilities in their work settings and there are few resources for substitute employees. Therefore, it may not be easy to set time aside from patient care in order to study nursing student’s learning and assessment needs. In addition, if the registered nurses do get the opportunity to participate in training, they prefer to enhance their patient care knowledge, especially in case of nursing in specific fields (e.g. surgical or mental health nursing). Nursing guidelines and techniques are constantly in progress, and nurses are required to stay updated on these important issues, which also explains the order of importance for using nursing resources for education purposes.

Mentoring education arrangements

When asked about good practices for mentoring training, managers suggested events that would take only three to four hours in the evening and offering the same contents twice on different days would enable as many as possible to participate in the education and using necessary shift arrangements to take care of clients and patients. Managers argued that it would be easiest to arrange mentoring training at the work organization so that the workers would not have to travel a long way in order to attend, and it would also be ideal if the events were held at the working places of the mentors.

Support from teachers

It has not always been possible to ensure that mentors have completed mentor training, which makes the support of the students’ teachers even more important. The managers highlighted that teachers should visit the clinical placements in the beginning of the working period so that the mentors and students get orientation to the clinical practice period and the assessment process, including determining what the student should learn and what competency levels should be reached for educational purposes during the working period. Teachers should also clarify the responsibilities of each party: what should managers/organizations do, what is the student responsible for, what are teachers/educational institutes’ responsibilities? Managers also highlighted the role of the students: they may have broad responsibility of the whole process and must be particularly proactive in arranging and ensuring that they get possibilities for learning and earn the level of competency set for their degree. According to the managers’ views, the students who are willing to be active in process are more likely to take care of their own learning and related situations. This may help them graduate earlier than other students or possibly enhance their financial circumstances during their education.

Independent working situations

The issue of mentoring in independent working situations was also highlighted by the managers. Health care and social services involve certain situations that require employees to work by themselves, without any help from colleagues at the worksite. Home care and work conducted alone with the customer/patient in an examination room are typically one-worker jobs.  Working alone is usually an outcome of limitations to financial and timing resources. What consequences could there be for student nurses needing to have someone to accompany them so that they could assess their behavior in real customer/patient situations? Would the rest of the employees have to work more because one of the workers cannot work independently all the time? This could also affect the willingness for the aforementioned arrangements at the whole work place and among workers.

The managers had a very positive view on improving students’ ability to earn study credits from their daily work. They had often witnessed students having to work during their studies to earn money to in order to support their family, small children or meet their financial needs. This might cause a delay in the students’ education, but the employers would like to employ this specific student after graduating and this is not possible because of the situation. The managers consider that combining work and studying gives ‘good drive’ to the whole workplace because the students may be highly motivated to improve the circumstances of working processes. In many cases, the students take on theoretical tasks, such as a final thesis, for certain work place needs.


Students’ ability to work in the ‘real world’ is very important for their professional growth by combining their theoretical knowledge with actions in a workplace. These learning situations are important, but it is also crucial that students increase their knowledge of their competency as nurses or other professionals. Final assessment in clinical practice during nursing education is extremely import for ensuring the sufficiently high quality of nursing graduates. In every profession, awareness of what employees know and do not know, and their ability to identify what they need to know is key to lifelong learning and becoming a better professional (Gardner et al., 2007). For example, Blackman et al. (2007) and Lauder et al. (2008) have argued that nursing students’ self-assessment skills may be insufficient and that self-assessment might thus not be a reliable method for ensuring the competence of nursing students. The challenges in combining work with earning credits to a degree also highlight this challenge of assessment. What are the circumstances in which students are working; what are the utilized competency areas, are the students able to do practice everything required by their studies, how is mentoring arranged, and how do students get relevant feedback and assessment?

Mentors are clinical nurses who supervise and assess nursing students during their clinical practice. Therefore, mentors play an important role in identifying nursing students’ capability (Jokelainen et al., 2011). If working organizations had possibilities to ensure that students get proper learning opportunities with the help of good mentoring and appropriate assessment practices, we could ensure meeting the objectives set for nursing students also in a situation when a student is paid for work during the period they learn nursing skills. In many other education sectors, it is not uncommon that students receive payment for their work also when the aim of their work period is to meet objectives set for their studies.. For example, in technological education in Finland, students are encouraged to get a summer job to earn credits for their studies. In contrast, in education in the field of health care and social services, students are typically considered to be unable to learn enough if they are working as paid workers. But again: high quality assessment is the way to ensure high quality of learning.

Educational institutes must carry out good teamwork with clinical practice placement sites and mentors to ensure high quality in the assessment process, especially when nursing students are also employees at the sites. This is a challenging set of circumstances because it differs from typical arrangements for nursing students’ clinical practice periods where students are perceived as ‘extra’ persons in the working places. The role of nursing teachers in the clinical placements has been sometimes debated, while findings by Helminen et al. (2014) and Löfmark et al. (2012) showed that nursing students and mentors rated highly the supervision they had from teachers. The opinions of the managers who participated in this inquiry belonging to the Verkkovirta project were similar. Mentors need support from teachers to improve the clarity of assessment plans and documentation: what nursing students are required to complete and explanations regarding the meaning of the ‘pass’ and ‘fail’ grades. Mentors and nursing teachers have their own roles in the clinical placements: mentors are the experts on clinical practice, while teachers´ role includes familiarity with learning outcomes defined for clinical practice and how these can be reached and assessed (Collington et al., 2012; Broadbent et al., 2014; Helminen et al., 2016). Therefore, nursing teachers’ visits to clinical placement sites for ensuring that nursing students get an opportunity to receive feedback on their performance from mentors are important for the good quality of the assessment process. Work organizations play a central role in enabling this special opportunity for students to arrange their studies in personal ways and, therefore, educational institutes and teachers should also invest in and carefully consider employers’ opinions and make this cooperation as good as possible.

The purpose was to investigate perspectives in work organizations on development needs related to students combining work and studies. By interviewing managers, we gained important knowledge that can be used in developing educational situations to provide students with opportunities to study flexibly and graduate within the appropriate timeframe. The importance of support and arrangements for the entire workplace and employees is highlighted. Finally, educational institutes must also guarantee that the teachers provide support to the students, mentors and managers during the process.


Kristiina Helminen, Saimaa University of Applied Sciences, Senior Lecturer, MHSc, kristiina.helminen(at)

Bisholt, B., Ohlsson, U., Kullén Engström, A. & Sundler Johansson, A. 2014. Nursing students´ assessment of the learning environment in different clinical settings. Nurse Education in Practice 14, 304-310.

Blackman, I., Hall, M. & Ngurah, I.G. 2007. Undergraduate nurse variables that predict academic achievement and clinical competence in nursing. International Education Journal 8, 222-236.

Broadbent, M., Moxham, L., Sander, T., Walker, S. & Dwyer, T. 2014. Supporting bachelor of nursing students within the clinical environment: Perspectives of preceptors. Nurse Education in Practice 14, 403-409.

Collington, V., Mallik, M., Doris, F. & Fraser, D. 2012. Supporting the midwifery practice-based curriculum: The role of the link lecturer. Nurse Education Today 32, 924-929.

Eriksson, E., Korhonen, T., Merasto, M. & Moisio, E-L. 2015. Sairaanhoitajan ammatillinen osaaminen – Sairaanhoitajakoulutuksen tulevaisuus -hanke. Ammattikorkeakoulujen terveysalan verkosto ja Suomen sairaanhoitajaliitto ry. Bookwell Oy, Porvoo. Also available at (includes English version):

Gardner, A., Hase, S., Gardner, G., Dunn, SV. & Carryer, J. 2007. From competence to capability: a study of nurse practitioners in clinical practice. Journal of Clinical Nursing 17, 250-258.

Helminen, K., Tossavainen, K. & Turunen, H. 2014. Assessing clinical practice of student nurses: Views of teachers, mentors and students. Nurse Education Today 34, 1161-1166.

Helminen, K., Coco, K., Johnson, M., Turunen, H. & Tossavainen, K. 2016. Summative assessment of clinical practice of student nurses: A review of the literature. International Journal of Nursing Studies 53, 308-319.

Jokelainen, M., Turunen, H., Tossavainen, K., Jamokeeah, D. & Coco, K. 2011. A systematic review of mentoring nursing students in clinical placements. Journal of Clinical Nursing 20, 2854-2867.

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Real life solutions to real life problems: Living Labs approach within university of applied sciences pedagogical practice

Recently, institutions of higher education have adapted practices that bring together students, members of the teaching staff and institutional partners. It is typical for these practices that students work in teams to solve challenges provided by partnering institutions (private business, public agencies, NGOs, etc.).  Current pedagogical theories fail to cover certain aspects of these practices. The aim of this article is to describe pedagogical practice in question through theoretical inquiry and a case study. As a result, the Living Labs approach is proposed in order to complement current pedagogical theories.

Questions of learning and how the pedagogical process should by designed accordingly are central to each pedagogical institution. As a community of experts, every pedagogical institution needs a shared vision and defined curriculum to be communicated to teachers, students and partners.

Institutions of higher education have adapted practices that bring together students, members of the teaching staff and institutional partners. Students work in teams to solve challenges provided by partnering institutions (private business, public agencies, NGOs, etc.). Also, concepts of innovation and innovation pedagogy are considered important.  Faculty members serve as facilitators. They mediate between the wishes of the partnering organizations providing the student teams with tasks and requirements of the curriculum.

Even within Finland, examples are many. University of Tampere has Demola, Laurea University of Applied Sciences has introduced Learning by Development. Metropolia University of Applied Sciences has Minno and Aalto University has developed similar practices (i.e. Hämäläinen 2015).

As a case author uses his employer, Diaconia University of Applied Sciences. Diaconia University of Applied Sciences (Diak) is a nation-wide university of applied sciences, which offers Bachelor’s degree programmes in social services, youth work and diaconia, nursing, sign language interpreting, and community interpreting. All Diak’s five campuses are actively engaged in the development of social and health issues in the regions where they are set. Diak has about 3,000 students, which makes Diak the largest higher education institution providing social work education in Finland. Diak has a distinct profile among the Finnish higher education institutions in immigration and refugee issues, the work against poverty and marginalization, and social inclusion. (Diaconia University of Applied Sciences, 2016.)

Author works as a lecturer and development team leader in Diak. Author has taken part in the process described below.  First of all, author and his team designed the new thesis process to fit into Curriculum 2015 and ideals presented in OSKE –pedagogy.  Secondly, team has implemented these ideals into study assignments and instructions. Thirdly, team has been central in communication new practices to students and staff members.

Knowledge creation approach in pedagogy

Pedagogical practice referred to above falls under the constructivist learning theories.  In the following different categories within constructivist learning theories are discussed.

Characteristic of the knowledge-creation approach is to examine learning in terms of creating social structures and collaborative processes that support knowledge advancement and innovation. The knowledge-creation view represents a ‘‘trialogical’’ approach because the emphasis is not only on individuals or on community, but on the way people collaboratively develop mediating artifacts (Paavola & Hakkarainen 2005, 539).

Scardamalia and Bereiter (2014) use the concept knowledge creation in order to differentiate between knowledge building and knowledge creation. They see the former as deriving from the learning sciences and latter from the organizational sciences. Both these approaches consider knowledge as created, rather than discovered.

In their view, Knowledge creation refers to learning organizations. Knowledge creation is about a socio-cognitive process in which the tacit knowledge of individuals figures centrally both as source and an outcome. Organizations develop and became more productive and efficient through the knowledge  process of knowledge creation. Also, within the knowledge creation approach, students are valued for their contribution. Students learning is not a process taking place within their minds. Rather, learning is a shared process aiming for a certain outcome.

While organizational sciences see learning and human development as tools for better organizational performance, learning sciences consider learning and human development as aims in themselves. What can we expect of the students, and what conditions for leaning and development can we set?

Insightful interpretations or explanations of the work of others qualify as knowledge creation, as do identification and clarification of problems, providing supportive or disconfirming findings, offering a different perspective on an issue, and even popularizing knowledge advances – putting them within reach of the less sophisticated. All of these are within the capacity of students working collaboratively. (Scardamalia & Bereiter 2014, 398.)

One strong argument for the knowledge creation approach within learning sciences is that they prepare students for the current conditions of life in general and working life especially. These are the 21st century skills for the knowledge driven societies and knowledge driven organizations.

The knowledge creation approach is developed through different concepts.  According to Krajcik & Shin (2014) project-based learning (PBL) environments have certain key features such as (i) the driving question, a problem to be solved; (ii) focus on learning goals; (iii) student participation in scientific practices, etc.

In the pursuit of solving the driving question, students engage in a meaningful process which is characterized by social interaction and the use of cognitive tools. In project based learning, driving questions are selected or students can develop their own driving questions for projects. A good driving question is feasible (students can design and perform investigations in order to answer the question), worthwhile (they contain rich scientific content), (iii) contextualized (relate with real world), (iv) meaningful (interesting and exciting) (v) ethical (not harming the participants’ environment etc.) (ibid. 281.)

Problem based learning, on the other hand, is “an active approach to learning in which learners collaborate in understanding and solving complex, ill-structured problems” (Lu et al 298). Central to problem based learning is the tutorial process. The facilitator, usually a member of the teaching staff, uses different strategies in order to enhance learning and problem solving. These include the use of open-ended and metacognitive questions, revoicing, summarizing, etc. (ibid. 307.)

Also, the role of the problems themselves is high-lighted. Out of four types of problems (diagnostic problems, design problems, strategic performance problems and decision-making problems), two are the most efficient. Design problems and strategic performance problems proved the greatest achievement effects. Design problems involve creating an artifact, generally based on a set of functional specifications. Strategic performance problems ask for “applying tactics to meet strategy in real-time complex performance” (ibid. 304-5).

For the knowledge creation approach in general, Scardamalia and Bereiter suggest that a meta-discourse should be created and supported. This is especially important from the point of view of engagement of all students in sustained creative activities. Metadiscourse is the discourse of the students themselves regarding their ongoing   building practice and discourse. It is a discourse on discourse. Students should be given tools and stimulus to discuss and evaluate their progress, ways of argumentation and recognizing and dealing with obstacles etc. (Scardamalia & Bereiter 2014, 407),

The previous issue relates with the question of adequate and authoritative literature. In an information society, where information is more and more easily available, it has become more and more unclear who or what defines the authoritative sources of literature. Traditionally literature has been regarded as providing the theory on a given issue, while student engagement in the practical process provides the practice or experiment. Who should provide the coherent theoretical and conceptual framework for the students in which to reflect on their practical process?

This is also one of the skills in the 21st century tool box. Transliteracy, the ability to use different sources of information in order to produce a coherent understanding of the phenomena and issue at hand, is a valuable skill.

Bereiter (2014) uses the term principled practical knowledge to refer to know-how combined with know-why. In a more formal manner principled practical knowledge can be defined as “explanatorily coherent practical knowledge” (Bereiter 2014). This type of knowledge is created in the process of solving problems. However, there is an additional element here. Instead of merely solving a problem at hand, explanatorily coherent practical knowledge includes aspects that are useful beyond the immediate problem. These elements enable the development of the field of practice.

Explanatorily coherent practical knowledge does not make a difference between conceptual knowledge and practical knowledge. It is explanatory, it makes easier to understand the issue and the field at hand. Also, it is coherent. Explanatory practical knowledge cannot refer only to one issue or topic. Rather, the reference is on the wider field which is explained and described coherently.

Open Innovation 2.0 and UAS curriculum: the case of Diak

Within the Finnish framework, institutions of higher education are relatively free to set they own curriculum. Legislation (Ammattikorkeakoululaki 20.3.2015/325 14§; Valtioneuvoston asetus ammattikorkeakouluista 18.12.2014/1129), the definition of competences for each profession (i.e. social worker, nurse, etc. defined by network of UAS’s) and the UAS contracts with Ministry of Education set a frame for institutions of higher education to create they own curriculum.

Diak published a new curriculum in the fall of 2014. Compared with the previous one, Curriculum 2015 is structured differently and includes new biases. Here I will focus only on the issues relevant to the topic at hand, without trying to cover all the aspects of Curriculum 2015.

From the RDI point of view, Curriculum 2015 builds on the idea and practice of participatory action research. Partners, citizens and service users should be included in the RDI process. They should not be considered as objects of the study. Rather, they should be understood as active participants of the process. Within Diak, participatory action research goes under the acronym OSKE (Osallistava ja tutkiva kehittäminen; see Gothoni et al 2015).

Even if the thesis process is traditionally the central channel for a student to take part in RDI, Curriculum 2015 aims further. Participatory action research should be present also in other study units, not only in those related to thesis process.

On the level of implementation, this means the integration of different processes. These include the process of the students, the Diak RDI –process and the process of the Diak partners. Within Diak, there had been previous attempts to integrate these aspects. However, Curriculum 2015 is unique because for the first time these ideas are included in the curriculum. Previous attempts to bring together the student process with RDI were less structured and based on the decisions of individual lecturers. Within Curriculum 2015 there are specific study modules under the OSKE head-line to give a defined place and room for the practices integrating the students’ process, the RDI –process and the needs of the Diak partners.

Having a new curriculum is not enough, however. An implementation process is also needed. Implementation took place in phases. The way to arrange the co-operation between the students, lecturers and Diak partners is based on the long lasting collaborative workshops. These workshops are called OSKE -workshops. Several workshops were to be set up, each based on the specified theme. The core of each workshop is practical co-operation between the Diak teaching staff (i.e. lecturers) and the representatives of Diak partners.

Since the OSKE –study modules form the core of the thesis process for the student, it was necessarily to make sure that these study modules provide possibilities for students to plan and execute one’s thesis process. During the process, questions of innovation pedagogy and entrepreneurship studies were taken up. As a result, Innovation pedagogy and entrepreneurship studies were considered necessary to include these aspects into the OSKE –study modules.

In order to facilitate different ways of developing and indicating students’ professional competencies, an OSKE –blog was developed and taken into use in spring 2016. This is based on the older Diak experiment with a blog provided for students (Alavaikko 2010). The OSKE –blog provides an easy access publication channel for students to publish their texts, videos, photographs etc. The OSKE -blog also creates a semi-open forum for communication between students, lecturers and Diak partners. Students and the Diak staff can comment on each other’s ideas, external experts and Diak partners can be invited to comment on a student’s publications. (Alavaikko 2016.)

Arenas for interaction

Several arenas for interaction were created. First of all, the OSKE blog aims to bring together students, lecturers and Diak partners. It provides a possibility to communicate ideas and implementation plans from students to lecturers and Diak partners. Furthermore, OSKE blog gives a possibility to comment on these ideas and develop them further.

Since the first study modules were implemented fall 2015, became apparent that a forum for student recruitment was needed. There was no channel to recruit students into the OSKE –workshops.  To meet the need for student recruitment, the first OSKE –forums were arranged in February 2016. The OSKE –forum is an event taking place in each of Diak campuses. OSKE –forum lasts approximately 3 hours and brings together students, Diak lecturers and Diak partners.

The OSKE –forum is a key element in combining the student process, the Diak RDI -process and Diak partners. Their schedule defines possibilities to combine processes of different shareholders. For instance, there are short term projects (1-4 months). They have a limited possibility to be linked with the students’ process. On the other hand, scheduling OSKE –forums beginning at the beginning of the term, means that planning needs to be done during the previous term. Lecturers need to work with their partners, plan what they provide for the students at the next OSKE -forum and during next term.

This way, several arenas for interaction were created. First of all, OSKE workshops are the central element of the system. They are the ones where cooperation takes place, where credits are turned into action and practical real-life problems are solved. These long term processes bring together students, staff members (lecturers and RDI) and partners (business, public sector, civil society).

On the other hand, OSKE forums, arranged 1-2 times every semester at every Diak campus, are the arena for networking and student recruitment into OSKE workshops. Thirdly, the OSKE –blog makes one arena of its own. While the OSKE forums take place 1-2 times every semester, the blog remains. Future students can build on the texts and other products published by the previous student generations, students can interact amongst each other and exchange ideas with the Diak staff members and partners.

The blog for testing one’s ideas is central during the first stage, innovation and planning. Innovation and planning of one’s process consists of two courses, one focused purely on innovation and the other focused on creating a plan for executing and documenting one’s idea. Students’ ideas are based on the earlier Diak projects with domestic or EU funding, and/or ongoing cooperation with our partners. These ideas are published in the blog. This means that ideas can be commented on by ‘outsiders’, outsiders referring here to representatives of projects and organizations outside Diak.

Several cooperation processes between students, faculty members and partners are currently taking place. (i.e. Alavaikko et al 2016). Considering these experiences, it is possible to reflect between the pedagogical theories (above) and reality of the pedagogical practice within Diak.

As discussed by Krajcik & Shin (2014) above, experience has proved that the nature of the problem is significant. Also, the tutorial process is of central importance, as pointed out by Lu et al. (2014). However, there is a certain aspect in Diak OSKE –practices that theoretical approaches above fail to acknowledge. All problems, tasks or challenges that students are facing within OSKE practices, are real. They are provided by Diak partners (private, public, NGOs) for the student teams. The student teams then work collaboratively in solving these problems, in projects facilitated by staff lecturers. In order to highlight this aspect, the Living labs approach is defined below.

Living Labs approach and Open innovation 2.0

By Living labs, we mean reconstructing the interaction space. This space for interaction can be any space, anywhere, suitable for collaborative design, the application of knowledge for empowerment, uplift, and the development of people and communities for the use of innovation. (quote from the interview, Leminen et al 2012.)

Living labs wish to accentuate their informal nature and define themselves as a movement (Garcia et al. 2015, 16-27). Still, there are certain ways of formalizing Living labs. Living labs are benchmarked by European Network of Living Labs (ENoLL), and through benchmarking process it is possible to get a membership in ENoLL. Five basic requirements for a Living labs are as follows:

  • active user involvement (i.e. empowering end users to thoroughly impact the innovation process)
  • real-life setting (i.e. testing and experimenting with new artefacts ”in the wild”)
  • multi-stakeholder participation (i.e. the involvement of technology providers, service providers, relevant institutional actors, professional or residential end users)
  • a multi-method approach (i.e. the combination of methods and tools originating from e.g. ethnography, psychology, sociology, strategic management, engineering)
  • co-creation (i.e. iterations of design cycles with different sets of stakeholders).

(Garcia et al 2015, 19)

Apart from this ‘official’ definition, Living lab is also used as general reference to practices and organizations of similar characteristics, with or without membership in ENoLL (i.e. Curley 2016, 314). In this general sense Living Labs refer to user-centric research methodology for sensing, prototyping, validating and refining complex solutions in multiple and evolving real life contexts.

In fact, Living labs are usually seen within the discourse of innovation and co-creation. Open Innovation 2.0 and the concept of innovation ecosystems put innovation onto the forefront. Innovation is regarded as a driver for economic growth. (OECD 1998). For these reasons, innovation discourse has a strong political backing and therefore innovation draws economical and other resources. In the current discussion, Open Innovation 2.0. and innovation ecosystems came hand in hand.

[i]nnovation as a discipline has now moved from being something invented by a brilliant researcher, through the era of open innovation, into an ecosystem-centric view of innovation, where the ecosystem is often the distinguishing unit of success, not individual companies or universities. (Curley & Salmelin 2013, 3.)

No company or institution of higher education can pursue their aims alone. Co-operation is the key to success. What is also needed is openness. Ideas need to be tested and developed together or by the users, not in an isolated laboratory.  Quaprable helix refers to academia, government, civil society and business to work together in developing products and practices (Curley & Salmelin 2013; Curley 2016).

In a sense, the circle is full: the innovation ecosystem, with co-operation and co-creation between academia, government, society and business, provides a framework and a function for institutions of higher education to engage in development processes, providing challenges for students and staff members alike. On the other hand, institutions of higher education want to ‘mingle in’, they wish to be part of the regional ecosystem of private companies, public sector organizations and civil society. They wish to find they place in the quaprable helix for Open Innovation 2.0, formed in the co-operation of academia, government, private sector and civil society.

As for the concepts, I will use the Living Labs approach in order to refer to the web of concepts created by Living Labs, Open Innovation 2.0 and Innovation ecosystems. They are interlinked and related, even if they all have they own point of reference. The idea of innovation ecosystems forms the rationale for institutions of higher education to seek their place alongside the public sector, the private sector and civil society. Within this framework, institutions of higher education seek to relate with local and global systems of innovation, economics and production (i.e. ecosystem).

Open innovation 2.0 comes hand-in-hand with the idea of innovation ecosystems. Open Innovation 2.0 underlines the open nature of the way innovations are understood to come about. While RDI used to be the business for the highly ranked experts, innovation is currently understood as an open, almost chaotic system where the brokering of seemingly unfitting ideas and approaches plays the crucial role. Innovation is not about geniuses in their ivory towers, innovation is about every one of us relating our ideas with others.

The driving force behind Open Innovation 2.0 and Innovation ecosystems is that innovation is believed to be the central ingredient of economic growth. Living Labs, both in their formal and loose sense, form the practice where the representatives of academia, civil society, public and private sector come together for innovation. Universities feel the pressure: the list of most innovative universities in the world was currently published (Ewalt 2015).

Without the openness of the current practice of innovation, students who are not yet experts would not have a role in the innovation. Within the framework of Open Innovation 2.0 students can represent the everyman and everywoman in the innovation process, while at the same time learning the ideas and procedures of the innovation. Organizations representing the private and the public sector and civil society are the ones that UAS’s co-operate with, in that they bring them into contact with students. These organizations provide students with content, with tasks for their assignments, team-works and theses. It is then a task for the teaching staff to arrange and formulate these tasks so that they communicate with the curriculum and are functional and logical from the pedagogical point of view.

It should also be noted that the discourse of innovation forms something resembling an ideology. Key words are the economic growth and national competitiveness, as Professor Pauli Kettunen has pointed out (Kettunen 2011). Innovation discourse is not politically or socially neutral. According to Kettunen, innovation discourse it is not merely a question of how to arrange elements of RDI in the best possible order. Innovation discourse has its connotations and political implications also.


I propose the Living Labs approach to be used when referring to pedagogical practices that fulfill the following criteria:

  • real life problems and challenges (the public sector, the private sector, NGOs) are brought into pedagogical practice
  • activity takes place in an ecosystem (multi-stakeholder environment)
  • active user-involvement is central for the process

The Living labs approach does not remove a need for other theoretical concepts. On the contrary, the knowledge creation approach in general and problem based learning and project based learning are the most relevant tools in analyzing and designing the students’ processes within the Living Labs approach.

It is also important to differentiate the Living Labs approach from other pedagogical approaches within knowledge creation. Differentiation is important in order to be able discuss possible problems and challenges.

For instance, it is possible that a focus on the needs of the partnering institutions and their clients overshadows the pedagogical aims. The development and learning of the students should be the aim of the pedagogical institutions. How to combine this aim with the aims of partnering organizations?

The Living Labs approach brings into light further topics. A significant dimension is that attention should be paid to the problem itself. In this respect, problem based learning identifies two dimensions. First, how structured the problem is, and secondly, how complex the problem is (Lu et al 304-305). However, the framework where the problem is set receives less attention. Within the Living Lab approach, problems are supposed to be real-life problems. Urge to solve real-life problems with real-life partners creates a new, difficult-to-control dimension into the learning process.

Even if the literature suggests that problem based learning should be the core of the curriculum rather than an addition (Lu et al 2015, 300), there are also other catch-words present. Innovation pedagogy, entrepreneurship studies, start-ups… How to relate these together, how to include these aspects into a curriculum and still have a logical and approachable curriculum?

It is, however, also a pedagogical and practical question how to arrange the principles of Open Innovation 2.0 and Living Lab within an institution of higher education. How to create arenas for sharing and discussion and interaction (civil society, business, government) within a pedagogical institution? What type of the student process is needed and what type of arenas (virtual, face-to-face, mixed, etc.) are needed at the different stages of the process? How to link the pedagogical approach with interests in business and government and civil society interests?

Also, an ecosystem -type of environment (different types of organizations, focus on the contacts, sharing and learning between organizations, not within a given organization) poses new challenges from the pedagogical point of view. There is a significant amount of literature on the management of innovative ecosystems and networks (i.e. Harmaakorpi 2013; Parjanen 2014; Prince 2014). This literature needs to be related with pedagogical theory and practice.


Mika Alavaikko, Lecturer, development team leader, Master’s Degree in Social Sciences, Diaconia University of Applied Sciences, Finland, mika.alavaikko(at)

Alavaikko, Mika. 2010. Blogipohjaisen verkkoalustan käyttö ammattikorkeakouluopetuksessa. In Hankekirjoittaminen., eds.  Pirjo Lambert, Liisa Vanhanen-Nuutinen.

Alavaikko, Mika. 2016. Blog as an arena of cooperation in problem based learning. Paper presented at ICERI 2016, Seville, Spain. [forthcoming]

Alavaikko, Mika, Katisko, Marja, Riihimäki, Titta and Sukula-Ruusunen, Kirsi. 2016. Yhteisöllinen kehittämisprosessi Katriinan sairaalassa. In Diakin pedagoginen vuosikirja 2016., eds. Raili Gothóni, Marjo Kolkka. [forthcoming]

Ammattikorkeakoululaki 20.3.2015/325.

Bereiter, Carl. 2014. Principled practical knowledge: Not a bridge but a ladder. Journal of the Learning Sciences 23 (1): 4-17.

Curley, Martin & Salmelin, Bror. 2013. Open innovation 2.0 — A new paradigm. Paper presented at EU Open Innovation and Strategy Policy Group.

Curley, Martin. 2016. Twelve principles for open innovation 2.0. Nature 533 (7603): 314-6.

Diaconia University of Applied Sciences 2016, webpages, Retrieved 5th of October 2016.

Ewalt, David. 2015. The World’s Most Innovative Universities. Reuters, Retrieved 5th of October 2016.

Garcia, Ana Garcia, Anu, Hirvikoski, Dimitr, Schuurman, and Lorna Stokes, eds. 2015. Introducing ENoLL and its living lab community. First ed. Brussels: European Network of Living Labs.

Gothóni, Raili, Susanna, Hyväri, Marjo, Kolkka, and Päivi, Vuokila-Oikkonen, eds. 2015. Osallisuutta, oppimista ja arviointia : Diakonia-ammattikorkeakoulun TKI-toiminnan vuosikirja 2015. Helsinki: Diakonia ammattikorkeakoulu.

Harmaakorpi, Vesa. 2013. Complex adaptive innovation systems. Papers in Regional Science 92 (2): 440-2.

Hämäläinen, Erkki. 2015. Experiences of a professor of practice at Aalto University. In Orchestrating regional innovation ecosystems., eds. Pia Lappalainen, Markku Markkula and Hank Kune, 191. Finland: Aalto University in cooperation with Laurea University of Applied Sciences and Built Environment Innovations RYM Ltd.

Kettunen, Pauli. 2011. The transnational construction of national challenges: The ambiguous nordic model of welfare and competitiveness. In Globalization and welfare : Beyond welfare state models : Transnational historical perspectives on social policy., eds. Pauli Kettunen, Klaus Petersen, 16-40. Cheltenham, GB: Edward Elgar Publishing Limited.

Krajcik, Joseph S., and Namsoo Shin. 2014. Project-based learning. The Cambridge Handbook of the Learning Sciences (2nd Ed.).: 275.

Leminen, Seppo. 2012. Living labs as open-innovation networks. Technology Innovation Management Review 2 (9): 6-11.

Lu, Jingyan. 2014. Problem-based learning. The Cambridge Handbook of the Learning Sciences (2nd Ed.).: 298.

OECD 1998. Technology, productivity and job creation best policy practices. Paris.

Paavola, Sami, and Kai, Hakkarainen. 2005. The knowledge creation metaphor–an emergent epistemological approach to learning. Science & Education 14 (6): 535.

Parjanen, Satu. 2010. Collective creativity and brokerage functions in heavily cross-disciplined innovation processes. Interdisciplinary Journal of Information, Knowledge & Management: 1-21.

Prince, K. 2014. Dialogical strategies for orchestrating strategic innovation networks: The case of the internet of things. Information and Organization 24 (2): 106-27.

Scardamalia, Marlene, and Carl Bereiter. 2014. Knowledge building and knowledge creation: Theory, pedagogy, and technology. The Cambridge Handbook of the Learning Sciences, Second Edition: 397-417.

Valtioneuvoston asetus ammattikorkeakouluista 18.12.2014/1129.

Oamk LABs practices for bridging work life 21th century skills and higher education

Problem and context

The demand for professionals who are able to create new solutions and innovations across disciplines, professions and perspectives is increasing. Innovations are needed for creating economically and ecologically sustainable communities (Capra 2007; Dumont and Istance 2010) and they are dependent on the capacities of people, organizations and networks to create and utilize knowledge (Boreham and Lammont 2000). Practitioners are functioning in societal structures and organizations that are constantly changing since expertise is no longer manifested exclusively in performing known tasks in a particular setting. Challenges that often cannot be addressed by routine solutions are constantly arising. These challenges have to be addressed by experts from different fields collaborating across different contexts (Engeström, Engeström and Kärkkäinen 1995; Tynjälä 1999). These are often called wicked problems, as they are characterized by confusing data, multiple users with differing values and not having a right or wrong answer. Furthermore, any possible explanation for one of these problems is strongly dependent on the worldview of the designer (Buchanan 1992).

The development in society and the economy described above requires that educational systems equip young people with the right competences that include attitudes, skills and knowledge to allow them to contribute actively to economic development under a system where the main asset is expertise. These skills and competencies, 21st Century Skills, are closely related to the needs of emerging models of economic and social development than with those of the past century, which were more suited to an industrial mode of production (Ananiadou and Claro 2009). Universities and institutions for vocational higher education are all challenged to educate these knowledge workers, since students of vocational education today are expected to function in a knowledge-based society.

As questioned by Ritchhart (2002),

“What if education were less about acquiring skills and knowledge and more about cultivating the dispositions and habits of mind that students will need for a lifetime learning, problem solving and decision making? What if education were less concerned with end-of-year exam and more concerned with who students become as a result of their schooling? What if we viewed smartness as a goal that students can work toward rather than as something they either have or don´t have?”

We, the authors, believe that 21st Century Skills represent the lens through which to address these questions. This article is an overview of the case of Oamk LABs which educates for those skills in higher education within a LAB studio model educational setting. The skills described within Oamk LABs education case, include descriptions of key practices as well as Oamk LABs student experiences with quotes from self-evaluations, course feedback or thesis work.

Studio pedagogy and LAB studio model

Studio based pedagogy

Studios have been used for educational purposes for centuries and can be traced to Middle Age schools of art and architecture. Today, besides the worldwide usage of studios in those schools, central features of the studio model of education hold interesting possibilities for education in other fields of vocational education as well for example in computer science (Kuhn 2001; Bull and Whittle 2014; Carter and Hundhausen 2011).

Studio based pedagogy can be defined as an instructional strategy that provides students with opportunities to engage in relevant, authentic learning in a school setting (Boyer and Mitgang 1996; Burroughs, Brocato and Franz 2009). The basic objective of the studio is to practice professional skills in small groups where one’s professional skills are challenged by others ­both peers and mentors (Schön 1983,1987). Studio based pedagogy is a constructivist approach, utilising project based learning (Blumenfeld et al., 1991). Also the approach of learning­-by-­doing, initially promoted by John Dewey (1897), is also a critical pedagogical principle. In this way, studios parallel the need for collaboration and creativity existing in work­place environments in the creative disciplines, design, art, etc. Traditionally, studios focus on visually ­centred work; and “reflective practice” (Schön 1987) observing and refining practice in a continuous cycle, supported by coaching and peer ­learning.

Studio based pedagogy suggests a more practical approach to professional education. Schön (1983) summarizes this process as reflective practice or “knowing­ and reflecting-­in-­action”. Pakman (2000) adds that this model of learning can allow practitioners to reconstruct their theories of action making and form action strategies explicitly open to criticism. This process is aligned with the knowledge creation practices, e.g. SECI-model (Nonaka and Takeuchi 1995). Another aspect of the studio model is the use of real world problems around which teaching is constructed (Schön 1985). Overall, research related to design education suggests that studio­ based pedagogy is an effective method for cultivating students’ identities as designers, developing their conceptual understanding of design and the design process, and fostering their design thinking (Kuhn 1998, 2001; Schön 1983).

LAB studio model characteristics supporting connection to work life

The LAB studio model (LSM), as a pedagogical model utilising studio based pedagogy, is a higher education model aimed at training competent new professionals, self-­directed teams and new businesses. The recent publication by Heikkinen and Stevenson (2016) has shown LSM to include several new factors compared to existing definitions of studio based learning such as by Bull, Whittle and Cruickshank (2013). According to Heikkinen and Stevenson (2016), these factors include:

  • offering a form of instruction that is more competitive in structure in contrast to other studio models (competitiveness);
  • integrating experienced professionals and coaches from the industry (work-life connection);
  • including problems or ideas directly from targeted industries;
  • building project teams that cross professional and higher education faculty boundaries (interdisciplinary).

The factors above described factors support the development of T-model learners and 21st Century Skills. Professionals having T-shaped skills “are deep problem solvers in their home discipline but also capable of interacting with and understanding specialists from a wide range of disciplines and functional areas” (IfM and IBM 2008).

LSM supports the work-life connection through various themes. By being intergenerational, interdisciplinary and international, project teams are connected to diverse expertise and experiences. The project based learning method involves interaction with an external client and starting from the problem connects both students and coaches to the industry, as well as the reflective practice given by industry participants. New knowledge is created in organised and impromptu common happenings where social interaction, networking, informal peer-coaching and critique or constructive feedback is promoted.

LSM is founded on two values: Trust and Care. In general, these values reflect the LAB’s inherent entrepreneurial thinking and approach to problem solving. Among other things, the value ‘Trust’ refers to the fact that students are trusted to do their best towards the common goals defined within their team, leading to trustful and equal relationships, which also concern staff of the LABs. The value ‘Care’ means taking proper care of everyone and everything involved, from the educators and students to the development and learning results of the projects and teams. This value also emphasises tutoring as a means for ensuring professional growth during and after the LAB studies (Heikkinen 2014). Failures and mistakes are considered an essential part of the learning. Students have to face the challenges, practice and find new solutions after they have recognised their mistakes. Learning and success is a result of effort and self-inquiry. This is viewed as the way to support students to become more independent learners (cf. Dweck 2009; Saavedra and Opfer 2012).

Oamk LABs Studies

Established in 2012, the Oamk LABs are a higher education program offered at the Oulu University of Applied Sciences (Oamk) in Finland. This program is based on the LSM and is a full-time, interdisciplinary, international and intergenerational program to train new professionals and build new businesses. The Oamk LABs can be characterized as pre-incubators (Heikkinen , Seppänen and Isokangas 2015) where students are working together in interdisciplinary teams to build real prototypes, products and possible startups. As of January 2016, Oamk LABs consists of three LAB studios (LABs) each targeting a specific global industry: Oulu Game LAB (games industry), EduLAB (edtech industry) and DevLAB (health, energy and environmental industries). The Oamk LABs program is taught in English and currently brings together roughly 150 students from around the world, with a new cohort joining the LABs every semester.

Picture 1: A LAB Master advising a student.
Picture 1: A LAB Master advising a student.

The first part (one to two semesters) in Oamk LABs consists of two main phases: a concept development phase, called LEAD, and a demonstration development phase, called LAB. In the LEAD-­phase students produce concepts for needs provided by existing companies, organisations or from the participants themselves. The concepts are presented in specific events called Gates. (Heikkinen 2014). In the LAB­-phase, larger teams are formed to develop demonstrations (demos) of the concepts and a related business model. The LAB­-phase and the first semester ends with a final presentation event, which is open for all the students and LAB staff, as well as for professionals from the industry. In the events, student teams present their solutions and business models to receive customer oriented and professional feedback. The second semester is optional for the teams which are willing to continue developing their demonstration into a more complete product and it includes more focused business and product delivery coaching and connections to the industry.

The students participating in Oamk LABs in Spring 2016 were from various fields of study and represented over 30 different nationalities. The fields of study were teacher education, software engineering, business development, graphical design, social work, occupational therapy and physiotherapy with the addition of unemployed professionals. A wide range of experience and expertise is expected to cover the key areas of competences necessary for establishing new ventures (Timmons and Spinelli 1994) – start­up companies for the industries in focus. This also brings possibilities for students to gain valuable skills:

“Working in an interdisciplinary team has been new for me. This might have been the best experience I’ve had in DevLAB. Learning about each other’s background / culture was really important for me. This way of group work also improved my competences about responsibility and organizing, because every culture and background needs another kind of behavior.” (Industrial engineering student, The Netherlands)

Each Oamk LABs studio is led by a LAB Master. Together with coaches and tutors the LAB Master acts as a supervisor of learning and directs the students to find and build new knowledge and to commit them to work toward the promotion of learning. The staff has the responsibility of supporting student development, both in terms of specific professional career goals and in their project task and goals (Heikkinen and Stevenson 2016). Additionally in studios, coaching often requires the improvisation of teaching (Sawyer 2004). At Oamk LABs this calls for variations of methods used at the moment of coaching.

As a result, over the four years that the model has been developed a significant amount of students, credits and companies have been achieved. Based on the Oamk internal statistics (Oamk LAB´s Yearly Statistics 2016) between the years 2012-2015 Oamk LABs resulted in: roughly 600 new professionals, over 15000 ECTS credits, 152 new concepts, 59 demonstrations and 14 new enterprises. Oamk LABs has also been externally acknowledged to be the most innovative higher education model in Finland. In 2014 the LAB studio model was recognized for its ”Innovation and Entrepreneurship Teaching Excellence” and in 2016 Oamk LABs received the second highest honour at the European Conference on Innovation and Entrepreneurship conference award for Innovation and Entrepreneurship Teaching Excellence (ECIE 2016).

Learning and 21st Century Skills

Twenty-first Century Skills or competences are described by various sources (Ananiadou and Claro 2009; Binkley et al. 2012;  Burkhardt 2016; Dede 2009;  P21 2011). In Oamk LABs, these competences are seen as a dynamic combination of knowledge, attitude and skills (c.f.Ananiadou and Claro 2009). The competence areas at Oamk LABs are presented in Figure 1. We believe that the development of these six competence areas leads to a future professional mindset where the core is a positive attitude towards innovation and development. The facets of the future professional mindset are: confident person, concerned citizen, self-directed learner and an active professional. For each competence area, the model uses various learning methods and methods often overlap several competence areas.

Figure 1: 21st Century Skills at Oamk LABs
Figure 1: 21st Century Skills at Oamk LABs

Communication and collaboration

Professionals focusing on knowledge economy work require efficient skills for communicating and for working in teams. The ability to collaborate with others is one of the most important 21st Century Skills and also important for active lifelong learning (Saavedra and Opfer 2012). Future professionals need to be able to communicate face to face, by using distance communication tools and in different languages. They need to be clear both orally and in writing when using professional language to be able to influence and persuade others. They need to have effective team working skills: the ability to relate with others, to have patience with others, to trust others and skills to present, negotiate and listen actively (Dede 2009).

When working in teams at Oamk LABs, students have to overcome the lack of a shared vocabulary and different communication cultures. Because of the so-called disciplinary “silos” (Ashcraft 2011; Cohen and Lloyd 2014), students from different professions are speaking different professional languages. In order to work and develop concrete, user-centred projects and products in cooperation, students need to learn to understand each other’s professional terms and meanings and the way of communicating. Students also recognise the learning in themselves:

“Regarding communication and collaboration I feel that I have made significant improvements during Devlab. Working (…) has improved my overall team working skills, but also improved my personal communicational skills as well. I am more ready to start conversations both regarding project and other non-project related things as well.” (Master of Science Information system design Oamk Open University student, Finland).

Students learn how to observe body language and acquire skills to know how and when to show empathy. During the LAB each student gives multiple presentations. This is one way to learn how to communicate information and ideas to different audiences using a variety of media and presentation formats. Additionally, students develop networks in order to build collaboration that supports their future careers. During studies in Oamk LABs, the students’ learning network expands significantly (Heikkinen et al. 2015).

Disciplinary knowledge

Students at Oamk LABs are usually 3th or 4th year Bachelor or Master degree undergraduate students. Before joining a LAB, students need to have solid knowledge in their own discipline since during the LAB program they need to bring the skills and knowledge of their own profession into an interdisciplinary team. Students must use a wide range of content knowledge within their disciplines and profession: existing disciplinary knowledge, expertise, skills, networks and communities, professional interest areas and understanding of the future challenges in the field, and professional and research approaches.

While working as part of an interdisciplinary team, students learn how to apply and deepen their disciplinary knowledge and professional roles. Each student and profession is served by coaching specifically targeting his or her professional roles. Projects are also served by mentors to ensure an industry customer relationship (Carnell, MacDonald and Askew. 2006). Coaching and mentoring is performed by the teachers and external experts. The learning process is viewed as a process of learning and building new knowledge, which is shared within and between professions as peer-­learning (c.f. Boud, Cohen and Sampson 1999; 2014). The challenge has been ensuring that the learning of disciplinary topics of the curriculum studies fit with the requirements from the degree program. The solution for the above challenge has been to create an agreement associated with the individual learning objectives for each student together with their personal goals and a commonly defined curriculum together with the degree programs and Oamk LABs.

Teamwork is done in an unfamiliar and challenging context which requires students to apply and recognize their knowledge and share it with students from other fields. They learn about other professions, but most of all about their own profession and how they as representative of his/her own profession can contribute as a team member. Furthermore, students learn T-shaped skills which are required in order to effectively interpret and utilize unfamiliar knowledge for exploration focusing on gaining new knowledge aimed at innovation (c.f. Hamdi, Silong, Omar and Rasid 2016). Students are also gaining experience about how work should be done and divided for the best result from the product development point of view, such as demonstrated by the following lead software developer:

“…the thing that I learned is how to split the work among developers, making sure that not only everybody gets a fair share of the work, but also importantly, that our works do not conflict with each other’s when we merge our work tighter.” (Information Technology student, Lithuania).

According to Litendahl (2015) and Perka (2016), studying at Oamk LABs develops disciplinary competences and even new, future-related competences (Litendahl 2015) as well as knowhow to use disciplinary competences become wilder (Perka 2016).

Responsibility and global awareness

To effectively develop user-centred innovations, professionals need to have the ability to empathise and share the pain of the user. This means courage to respect differences of cultures, ways of living and values of people (c.f. Ikeda 2005). When truly doing this, professionals become more aware about the global needs, limitations, opportunities and future trends. Responsibility becomes a personal obligation to be productive, including intrapreneurship and entrepreneurship, and the work has to respond to the needs of the customer.

Sustainability is a central theme in DevLAB for the academic year of 2016-2017. Sustainability is accepted nowadays as a guiding principle by public policy making and companies (Finkbeiner, Schau, Lehmann and Traverso 2010). Moving towards the goal of becoming more sustainable requires fundamental changes in attitudes and behaviour. Every student learns accountability, personal and social responsibility and being a responsible team member. For many students, the way to approach clients and customers to find solutions for real life problems is different from what they have had before:

“Now I know how to ask the right questions without leading (myself or the person to interview) too much to the solution that I have on my mind. This enables me to get the honest answers to the problem I’m solving.” (Business information systems student, Finland).

One practice used to become more aware about global issues and responsibility is a Megatrends workshop. Within Megatrends workshops students deepen their knowledge about a global megatrend, which is connected to the actual problem they will be dealing with later in the program. During the spring 2016, key megatrends that students were studying were: aging, urbanisation, decline of resources, digitalisation, global environmental change, rising healthcare costs, the changing nature of work and the rise of personalisation. Students got familiar with the megatrends during the first week of the semester and they prepared short presentations for the group. This was one way of preparing students for the mindset of being active and using all available expertise in the LAB. At Oamk LABs new knowledge is created in cooperation between students, coaches and work­-life partners, thus forming a community of learners (c.f. Brown and Campione 1994; Rogoff, Matusov and White 1996). This allows students to create some common understanding about the world.

Creativity and innovation

According to the organization Partnership for 21st Century Learning (P21 2004), there are three skills essential for creativity and innovativeness: thinking creatively, working creatively with others and implementation of innovations. In order to think creatively one needs to use a wide range of idea creation methods or techniques. Future professionals have to know how to create new and viable ideas both by themselves and as part of different teams. To work creatively with others means developing, implementing and communicating new ideas effectively to others. Future professionals need to be open and receptive to new ideas and diverse perspectives. They also need to have a mindset that being creative and innovative is a long-term cyclical process, floating between mistakes and success. They also have to tolerate that it could take a lot of time to create something real, unique and useful. This happens only if one is curious and ready to take some risks. In order to be able to think and act like this, the professionals have to have creative confidence – a mindset to see one’s own creative potential (c.f. Kelley and Kelley 2013).

Learning by doing as a work-based learning method has been recognized for a long time as an important way of learning innovation creation (Toner 2011). Learning in Oamk LABs is strongly based on the concept of learning by doing; developing a concept for a product or a service. In Oamk LABs, the Concept Development Process has been used based on the Design Thinking (Brown 2008) methodology in the academic year 2015-2016. This process was an experiment to see how Design Thinking fit in with the LAB Studio Model. Students were creating solutions for various different user groups and needs well outside of their own experience. The concept development process, not based on any of the fields of the students, is an equalizing force that allows everyone to participate. The promise of design thinking is that anyone can do it if they follow the mindset. For the spring semester 2016, the concept development process was fully implemented and realized as two subsequent cycles though the design thinking modes during the Lead phase to create a solution concept (Karjalainen 2016).

Critical thinking and civic literacy

Open-mindedness, flexibility, willingness to self-correct and pursuit of consensus are needed skills for future professionals. These are also characteristics of a critical thinker. Professionals, who are critical thinkers are motivated to exercise the effort needed to work in a resourceful manner, to check for accuracy, to gather information, and to persist when the solution is not obvious or requires several steps (Halpern 2003). Critical thinking uses evidence (Halpern 2003) and that is why it is connected to skills of civic literacy.

The aim of learning critical thinking is to help students to develop their abilities to reason, analyse, evaluate and create. Students need to develop these abilities and at the same time learn to express one’s feelings, thoughts and actions in a way that is rational and clear (Mulcahy 2008). Learning critical civic literacy enables students to question the assumptions that undergird current ideas, practices, policies and structures (Teitelbaum 2011). These are skills needed when students are identifying and defining problems from partners, collecting and analysing data (e.g. identifying existing problems and already made solutions for them in order to find the real problem behind the problem). An essential component for the future work is that professionals are encouraged to think and use their skills in different situations and environments (e.g. skills transfer).

Coaching provides opportunities to learn critical thinking skills. In Open Coaching Sessions students are challenged to discuss, ideate and find new points of views. Both staff members, students from different LABs and external coaches gather together to exchange ideas. Another coaching practice is Professional Coaching within which students of a specific field or profession have either an expert from the industry or coach from the university staff focusing on their specific professional issues and challenges. With the help of coaching, students can critically think about their projects:

“We were able to come up with new ideas, criticise them as much as we could from all areas such as from a business or development standpoint, and then we would research heavily what would need to be done to make the product/service and if there were any similar devices and their downfalls.”  (Graphical design student, Ireland).

Self-knowledge and self-awareness

High self-awareness leads to better team performance; it affects positively to decision-making, coordination and conflict management (Dierdorff and Rubin 2015). The LAB Studio Model-learning is based on reflection and reflection is described as a process of self-analysis, self-evaluation, self-dialogue and self-observation (c.f. Yip 2006). The starting point of the learning process is for every student to identify his / her own needs and goals for learning. This helps students to define what and how they want to achieve their goals as a person and as a team member. Personal development in Oamk LABs is viewed from a team working point of view, thus goals are discussed, defined and reflected with other team members, LAB Masters and tutors. During the course of the LAB, the learning goals are aligned with the project goals.

Personal evaluation discussions are individual meetings with students. Before the meeting the student prepares 2-4 personal development needs from the point of view of their future expertise. Discussions are done with the same person(s) throughout the semester: at the beginning, in midway and at the end of the semester. In spring 2016, one student told about how displeased he was about the quality of his work, his unorganized way of using time and not being productive enough. The student set himself appropriate goals in cooperation with LAB Masters. As part of his self-evaluation, at the end of the semester, he writes:

“I feel I am now much more capable at determining my strengths and weaknesses and I am also much more aware at what my current skill levels will allow me to do. I have realised that rather than doing everyone’s job, I have to have more trust in my team and have one job that is done to its best standard.”  (Graphical design student, Ireland).

During the process of studying in Oamk LABs, goals as well as methods to achieve the goals, are discussed several times both individually and in teams, because goals become more clear and will need adjusting during the study process. Depending on a student’s own wishes this can be more individual, but most students are open and willing to share their personal development areas at least with their team, some of them also with the larger learning community. This enables possibilities to have feedback and support from peers as well.

Development of self-knowledge and self-awareness happens both in planned activities as well as in serendipitous encounters which the LAB learning enables. The goal is to become a more self-directed learner. As a result, learning is dependent on the interests, experiences and actions of each learner and the circumstances in which learners find themselves. The fact that students and staff members are working together in close contact for at least one semester opens the possibility for a trusting relationship to develop. Cooperation with LAB Masters and coaches is partly planned beforehand, but students also know that whenever they need to have coaching, they can ask for it. Acting according to these principles reflects in action one side of the key values of LAB Studio Model, Trust and Care.


As an operational model, Oamk LABs work more as a small company than as a school and according to our values the coaches treat the project teams like startup companies. We allow them to self-organize, divide the tasks and make their development plans. However, to support a climate of critical consciousness, feedback in LABs is given to individuals and to project teams and coaching groups during formal and informal sessions. In this way, giving and receiving feedback is a regular part of LAB studio daily activities. Learning at Oamk LABs mostly happens in relation to the team and the project.

Oamk LABs employ several practices to achieve both the learning goals and to bridge the academic work with the work-life. Some practices happen regularly over the course of a semester while others are one-time events. Figure 2 maps some of these practices with regard to two aspects. The vertical axis represents whether the activity is more team or individual focused and the horizontal axis tracks if the reasoning for the activity is more related to academic work or the work-life. We feel it is important to a have mix of practices for bridging academic training and the work-life while allowing learning to happen both as individuals and as team or group members. Academic methods aim for reflection of one’s values, attitudes and actions, while practices with a team dimension are more closely related to work-life skills and advancing the project goals. These practices teach students to recognize the joys and challenges of teamwork and to value the contributions of team members. This helps to build a future professional with T-shaped skills.

Figure 2: Some practices at Oamk LABs mapped according to the target of the activity and relevance in academic versus work-life needs.
Figure 2: Some practices at Oamk LABs mapped according to the target of the activity and relevance in academic versus work-life needs.

The learning model is built to be flexible so it can accommodate different industries and types of projects, which may require adaptation and addition of new practices. Since the educational model is still under development, new practices are tried out in a limited scope and existing ones aer improved where a need is seen. The following sections cover three practices which specifically deal with bringing the work-life into the studies in more detail.

Practice: Source of project topics

In order to bring the work-life in to Oamk LABs, the student projects start from problems or phenomena related to real cases in the industry. Problems from partners come with a contact person in the industry, but importantly projects are not assignments, where the company or organization might already have an idea of the solution they think they need or have a list of requirements at the ready. It is critical for project-based learning that the outcomes of the project are not predetermined (Blumenfeld et al. 1991). The coaches prepare the problems together with the industry professionals and to make sure that the project enables deepening of student’s disciplinary knowledge.

Another key aspect for suitable problems is that they require an interdisciplinary team. This leads us often to either look for novel business opportunities or to wicked problems, in which no one can solve the problem alone. Understanding the problem behind the problem, the need of the client, and the development process to build a viable solution all require different types of expertise (Saavedra and Opfer 2012). A student team owns the rights to their solution after the LAB and have the ability and receives support to create a business based on the idea if they so wish, which can be highly engaging for entrepreneurially minded students.

With respect to the interests of the participating companies, this practice strikes a balance by both bringing partners to the LABs and allowing the solution to take shape rather freely. The value for a company in participating is the ability to influence the studies, look for new talent or new business opportunities. In cooperation with the student team, the partners can act as guides in the industry, as sources of information and provide access for user testing with end users. Companies who recognise the problem are also potentially the first customers for the solution and can provide valuable feedback for the student team. Partners who work closely with LABs get a chance to see the talent in the students and by offering problems also affect the content of the instruction in the LAB.

This practice naturally puts requirements to the coaches to be responsive to student needs during the LAB and also before the LAB starts in order to look for the problems in their networks. The IP rights agreement, the open doors policy and public nature of pitching sessions mean that some projects are not suitable for LABs. Overall, this practice is a benefit and an important cornerstone of running Oamk LABs since it enables new business opportunities, which may have initial demand in the market.

Practice: Project proposal presentations and selection, Gate 2

The Gate 2 event and pitch presentations are held at the end of the concept creation, LEAD-phase. The event is public and open to everyone. This is a key practice in bringing the competitiveness to the LAB and builds on the industry connection by having a panel of professionals in the jury, often from companies, industry associations and public organizations. A jury of outsiders is needed so we can get an unbiased view on projects, because at this point LAB Masters and coaches have been working with the teams for weeks and benefit from outside perspectives on the projects. Having new people listening to the presentations also raises the stakes and puts more emphasis on the delivery of the message. Coaches who know the story might fill in the gaps based on previous knowledge whereas fresh eyes and ears spot the inconsistencies. Judging is based on the framing of the problem and context, the business opportunity, viability of the solution and demo plan and the strength of the prototype.

Based on the jury’s feedback, projects are chosen for the LAB phase and the demo development. New team members join teams to create the final project teams. Gate 2 is a stressful event for most students, but creates a strong boost with an important deadline; do a good job or your project is dropped. The Gate 2 presentation should summarize all learning from several weeks of research, development and debate into one presentation. The team members need to work together to pick the right story to tell, find an interesting and compelling way to tell it, select the right person to present and support that person in preparing. This is not always easy and coaches need to facilitate this process in coaching sessions and by running a pre-Gate with presentations and feedback from coaches and peers.

Picture 2: Gate 2 event Spring 2016 was held on campus with high production to show students that their work is valuable and also to show the work to other students.
Picture 2: Gate 2 event Spring 2016 was held on campus with high production to show students that their work is valuable and also to show the work to other students.

The downside with Gate 2 is the potential loss of motivation if one’s’ project does not pass the gate. The jury and coaching feedback needs to be honest and open to offer a chance for reflection. We view this as an important learning moment as well. The project team might have done everything in their power and still get cut due to factors outside of their control. For example, the LAB can only support a certain number of project teams and thus some are cancelled. Similarly, companies have limited resources and some development projects have to be cut despite the great work and promise they may hold. Gates are connected to a practice called Bye old, hello new team in which we reflect on the Gate and show that there is value and things to learn from the projects that did not continue.

Practice: Events as learning opportunities

Event participation can take many forms and provides opportunities both to connect to work-life and to build competences. Students can participate in industry events, like seminars or networking events as a part of the public. Non-formal connections with work-life are emphasised by also organising common events or seminars. All event participation promotes social interaction, networking, non-formal peer-coaching, critique and constructive feedback. Students can also take part in organizing events or volunteering at large events. Some student teams with very promising products can even pitch at startup events already during their studies in LAB. This brings the student team under the same level of scrutiny as the already established companies pitching for the same judges. For example, at the Midnight Pitchfest (2016) in Oulu, Finland one of our student teams was in the top 5 in the general category among over 20 companies. Pitch opportunities create extra goals to boost motivation among students.

Volunteering at events creates opportunities for networking and builds appreciation of the industry. In the spring of 2016, the LAB Master of DevLAB decided to send all of the students to volunteer at a startup pitching event titled Polar Bear Pitching (2016) in Oulu. They helped to build up and tear down the stage area, served food and drinks, drove people and gear from place to place. Through this experience, students reported to have gained more understanding and respect for the various skills and the hard work needed to put on a successful event. They highlighted the need for communication and collaboration during the event and the need for organization and planning. While the time spent at events naturally takes away from advancing the student projects, LAB Masters need to ensure that goals are reached.

Practical considerations for running LABs

Maintaining bridging and alignment

Oamk LABs curricula and cooperation methods are developed together with the recognised stakeholders in LAB focus industries. For guiding the practical development work, Oamk LABs has established two steering groups (SG), one external and one internal. The internal SG is for the development of interdisciplinary and interfaculty practices and curricula within the university. The external SG is for adjusting the model to address industry needs better as well as helping to find suitable problems from the industry. This arrangement of SGs prepares the model to be closely aligned with the needs of the industries and with Oamk internal practices and structures.

Environment for Studios

The premises and location of a studio have an important role in studio model education, and thus require special attention. Based on our experience and according studio model research (Bull et al. 2013, Lee et al. 2015), the environment represents and promotes different ways of learning. The ownership of the premises enhances a feeling of trust and safety among the participants, and helps build the working culture. In addition, the visual representations of the projects are important for professional awareness (Bull et al. 2013) and reflective practice (Schön 1983).

With this in mind, Oamk LABs operates in three different locations; two in the downtown area, one on the university campus. Students, who all have 24 hours a day / 7 days a week access to the space, generate common rules for the premises. Premises include a kitchen area with a chill-out lounge, common spaces for lectures, working spaces for project teams and meeting rooms. Student teams are allowed and encouraged to modify their own space according to their needs. This action has the goal of enhancing the students feeling of control and ownership of the space to allow them to channel their motivation and follow their passion in creating their future. In addition, LABs premises are surrounded by supportive structures for creating new businesses. Usually new startup companies established from the LABs, LAB alumni, stay in close contact with the LABs. These relationships are benefitting from each other as LAB-newbies and alumni can support each other’s learning and product development.

Oulu Game Campus is a practical example of the industry’s interest to collaborate with the Oamk LABs and its ability to respond with the education bridging work-life. During the year 2016, Oulu Game LAB together with Fingersoft and other game companies in Oulu established a game industry pre-incubator initiative and facility in the Oulu City Centre (Kaleva 2016). This new campus brings together students, coaches, startups and more advanced companies, as well as companies giving supportive services for the industry, such as legal, accounting and financing services.

Renewing the role of the teacher

Studio based pedagogy drives renewal of teaching in vocational higher education. The LAB studio model sets new and challenging demands for the role of a teacher as educator, since the traditional teacher-student setup is turned upside down. With inspired, talented, well-connected, interdisciplinary and experienced personnel the learning is enhanced by using multiple methods inside the studio (Oamk LABs 2016). Teachers become more like coaches and consultants advising for the student teams in their projects, guiding learning, stimulating peer-learning and facilitating connections to work-life. Coaching is a new way of teaching and poses challenges to teachers, but is also something unfamiliar to students as well as demonstrated by one student:

”… I totally support this equality between teacher and student cause in my experience the learning effect was higher. Sometimes I wished that the coaches just tell me what was the right thing to do, which decision we should make, what direction we need to go with the project but they just asked question to push ourselves through our individual way. This was frustrating, interesting, annoying, challenging, helpful and very efficient” (Perka 2016).

Because of being full time studies, Oamk LABs give coaches the opportunity to act as a mirror reflecting the professional development of the student by giving constant feedback. Based on program experiences and trials, the suitable size of a LAB student group has been defined as between 30 to 40 students. In our experience the minimum amount of students ensures the forming of a multidimensional LAB community, thus enabling the learning community. On the other hand, the student group should be small enough to create a comfortable environment where students are familiar with each other. The studio education period should also be long enough to provide sufficient time for building a trustful relationship between coaches and students.

Since LABs curricula is designed to be flexible based on the needs of work-life and focuses around the needs of the student project, individual teachers’ traditional lesson plans cannot be utilized. Instead, teaching is principally based on the emergent needs of a student team project, referred to as impromptu teaching. Interdisciplinary teams and different student backgrounds force teachers to be open to new ideas and agile in guiding students. These Oamk LABs working methods challenge teachers to support 21st Century Skills and tap into their T-shaped skills. To succeed, teachers are well connected and have the latest knowledge from their field of expertise.

At Oamk LABs, staff form and operate in an interdisciplinary team of LAB coaches. The teacher’s ability to utilise the team of LAB coaches for needed expertise and introduce new external experts is necessary to advise student projects successfully. The working method also clashes with the traditional way of resourcing and planning teachers work time, since teachers are working as part time and have also other responsibilities outside of LABs. The needed coach might not be available for an impromptu session when it is needed. LAB Masters are responsible for resourcing and must anticipate the needs in projects. Over time the same issues emerge at the same phases of the projects and therefore resourcing can be matched more closely.

Training the LAB coaches for the model is essential to the successful delivery of a studio type of education (Schön 1983; Bull and Whittle 2014). The Oamk LABs staff has been educated for the LSM through a specific training program which includes intensive, practical and theoretical coverage of learning practices in the model. In fact, commonly at the beginning of the training program, coaches experience the concept development components of the LAB as a student. By experiencing the model first, coaches are able to better align their own teaching later on to the needs of a student team and individual students. Overall, teachers in studios need to be living according the values and act as future professional role models. Interestingly, the majority of the teachers participating in LABs have entrepreneurial or private sector background, which provides them with a strong understanding about business.

Discussion and future developments

So far studio based education has been utilised mainly in creative disciplines, such as architecture, design and arts for bridging academic and work-life practices. However, the nature of problems that future professionals are facing demands developing skills such as creativity and collaboration, – 21st Century Skills. This suggests why interest towards studio based pedagogy has increased in recent years among other areas of professional education (Heikkinen et. al. 2016). The studio based environment encourages the learning of work life skills in a climate that tolerates failure, which is essential before moving into work life. Project and problem based learning with methods using reflection are also widely used in studios. While current studio education typically includes students from only one discipline, the experience from the Oamk LABs studio environment calls for including students and teachers from different areas of expertise.

Based on experience from Oamk LABs, studio pedagogy can be highly demanding for students and teachers. The environment at LABs may be confusing for students because of the working methods and the interdisciplinary, international and intergenerational group of students. Communication between the different professions in a language that might not be your native language is challenging. Often extra effort is needed to make yourself and your ideas understood. Many of the students are undertaking concept development for the first time in their life and LABs offer a safe environment to make their first real designs for real problems provided by real customers. More advanced students provide an opportunity for Master-Apprentice-type learning since they can act as role models for younger students. After the ‘cultural shock’ at the beginning of the program, students recover and start to perform in a company-like environment as young professionals and eventually gain new knowledge for the task at hand.

The Oamk LABs future development continues through trials and evidence based development of methods. When the LSM is applied to other industries and countries and more degree programs are involved, the growth sets increasing challenges for the model definition, and external and internal communications as well. The Oamk LABs were created and continue to be developed through agile methods to be a dynamic education program with substantial freedom of operation to address changing needs of the industries and society at large. Creating interdisciplinary programs in higher education requires courage and a willingness for cooperation from within the different degree programs and a common recognized need, which can be formed only through co-creation and discussion. External pull for new types of expertise or a crisis can jumpstart the development of these new forms teaching and learning.

Oamk LABs enables learning of 21st Century Skills in higher education by educating self-directed learners who are active and concerned citizens. They are persons with an opportunity mindset and the confidence and tools for co-creation of innovations. The LAB studio model includes several additional components compared to many of the existing models of studio based learning. Since it is designed to be international, interdisciplinary, intergenerational and industry focused, it brings new opportunities for learning 21th Century Skills. In our opinion, bridging work-life and higher education happens through the renewal of teaching and teachers should act as role models for the new skills required. Oamk LABs is a dynamic and open environment which offers a platform to renew teaching practices and invites all participants to learn and develop together.


Janne Karjalainen, Oulu University of Applied Sciences, M.Sc. (Tech.), Lecturer, LAB Master, janne.karjalainen(at)
Ulla-Maija Seppänen, Oulu University of Applied Sciences, M.Sc.(Health, Occupational Therapy), Senior Lecturer, LAB Master, ulla-maija.seppanen(at)
Kari-Pekka Heikkinen, Oulu University of Applied Sciences, M.Sc. (Tech.), Senior Lecturer, Creator of Creations, kari-pekka.heikkinen(at)

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‘Do I Have It in Me to Be an Entrepreneur?’ – Entrepreneurial Coaching for Master Level Students


Entrepreneurship education has been high on the European agenda for many years as an effective mean of embedding an entrepreneurial culture in higher education institutions (HEI). Higher education has not traditionally prepared students for self-employment as HEIs’ primary mission has been to prepare students for employment (Fenton & Barry, 2014). Higher education is facing challenges in the definition of its purpose, role, and scope in society and the economy, and therefore universities have been recommended to expand their entrepreneurship education (OECD, 2012). Entrepreneurship education has evolved considerably in recent decades and it has gained both academic and political credibility (Henry, 2013).

Entrepreneurship education in higher education has shown to have a positive impact on the entrepreneurial mindset of students, their intention towards entrepreneurship, their employability and finally on their role in the society and the economy (European Commission 2012). At the global level entrepreneurship education is portrayed as critical to employment generation, innovation and economic growth and, therefore, it is promoted as a necessary core rather than an optional peripheral aspect of higher education curricula (Henry, 2013). The expectations for entrepreneurship education are high and e.g. Henry (2013) suggests that policy makers’ expectations may even have spiralled beyond what is both realistic and possible.

The entrepreneurial intentions of students at Finnish Universities of Applied Sciences (UAS) and in secondary education have been studied in a longitudinal research (Joensuu et al. 2014). In that study it was found that the entrepreneurial intentions of UAS students decrease during their studies. One reason for this seems to be that at the beginning of the studies students have more positive attitudes towards entrepreneurship as the time to actually make the decision to start a business after graduation seems to be far in the future. As they near graduation, their opinions towards entrepreneurship become more realistic and cautious. Furthermore, it was found that taking general entrepreneurship studies does not have an effect on entrepreneurial intention. However, entrepreneurial pedagogy requiring active participation of the students has a positive effect on the students’ confidence in their entrepreneurial capabilities and this in turn has a positive effect on entrepreneurial intentions (Joensuu et al. 2014).

A relevant policy-oriented question whether it would make more sense for a certain group of students to take more comprehensive entrepreneurship education rather than all students taking only basic entrepreneurship education has been raised (Søren, 2014). Entrepreneurship-specific education may provide students with an opportunity to accumulate transferable skills that can be employed in any organizational context, not only in business start-ups (Solesvik, Westhead, Matlay & Parsyak, 2013). This view supports the idea of offering entrepreneurship education widely in HEIs. On the other hand, if we think that entrepreneurship education should enhance students’ business start-ups, we should give more specific coaching for those students who already have entrepreneurial intention. As Fenton and Barry (2014) state, it is a fallacy to assume that more entrepreneurship education provision will lead to immediate graduate entrepreneurship as the route to self-employment is influenced by personal circumstances.

Another critical question raised within entrepreneurship education research is what we are really doing when we provide teaching and training in entrepreneurship. According to Fayolle (2015), we should think more critically about the appropriateness, relevance, coherence, social usefulness and efficiency of practices in entrepreneurship education. Entrepreneurship education is at the crossroads of entrepreneurship and education and, therefore, it should have a solid theoretical and conceptual foundation drawing from these both fields.

Keeping these two relevant and critical questions in mind, in this paper’s theoretical background the theoretical foundation behind our decision to concentrate on students with entrepreneurial intention is described firstly. Secondly, the educational foundation for our entrepreneurial coaching model is discussed.

Terms Related to Entrepreneurial Coaching

In research and political reports terms entrepreneurship education, enterprise education and entrepreneurial education seem to be used as related terms. However,  these terms are slightly different and e.g. UK’s Quality Assurance Agency for Higher Education QAA (2012) has defined enterprise education as follows: ’Enterprise education aims to produce graduates with the mindset and skills to come up with original ideas in response to identified needs and shortfalls, and the ability to act on them. In short, having an idea and making it happen’. Whereas entrepreneurship education ‘focuses on the development and application of an enterprising mindset and skills in the specific contexts of setting up a new venture, developing and growing an existing business, or designing an entrepreneurial organisation.’ (QAA, 2012, 8). The ultimate goal of enterprise and entrepreneurship education is to develop entrepreneurial effectiveness which can be defined as ‘the ability to behave in enterprising and entrepreneurial ways. This is achieved through the development of enhanced awareness, mindset and capabilities to enable learners to perform effectively in taking up opportunities and achieving desired results’ (QAA, 2012, 10-11).

This study describes one model of entrepreneurship education called entrepreneurial coaching which is offered to master level students at Savonia University of Applied Sciences. In this study the term entrepreneurship education is used when discussing entrepreneurial, enterprise and entrepreneurship education in general, and when discussing the entrepreneurship education model of our university the term entrepreneurial coaching is used. Coaching as a term describes well our model which has a personalized approach focusing not only on the business idea but on the student as an individual. This model creates a context of learning that equips the students to find answers themselves through a creative process. The coach plays the role of a facilitator or catalyst but does not provide ready-made answers (see e.g. Audet & Couteret, 2012; International Coaching Federation, 2016).

Objectives, Approach and Methods

This study describes the foundations, model and methods of entrepreneurial coaching which is offered to the master level students of Savonia University of Applied Sciences. The students’ expectations for the coaching and how they utilize it to develop their business ideas are examined. An earlier version of this paper was presented in the RENT-conference in Zagreb, Croatia in November 2015 (Laukkanen & Iire, 2015).

In this study the students and their views are placed into focus, and it is examined how entrepreneurial coaching may enhance their personal development as entrepreneurs. Our entrepreneurial coaching model is presented as one way to enhance master level students’ capabilities and courage to start and develop their own businesses. The aim of the paper is to strengthen the entrepreneurship education research by analysing openly the educational foundations of our entrepreneurial coaching model. As Jones et al. (2014) state,  in order to promote the development of entrepreneurship education it is important that the educators ‘reflect upon their practice, identify their teaching orientation and question their emphasis upon certain contents, processes and outcomes’ (Jones et al. 2014, 773).

This study adopted a qualitative research approach and a theme-based survey was conducted among 17 students who participated in entrepreneurial coaching. This data was used to describe the expectations of the students and the ways they utilize the coaching to develop their business ideas. We also arranged a kick-off seminar for these students and there we discussed their expectations and challenges concerning entrepreneurship. These discussions gave more depth to the themes which rose from the survey.

Furthermore, a more detailed look was taken into the coaching processes of four students with very different starting points, and short case stories of these students are told. Two of the students develop together a business idea which is based on their new product and service innovation. The third student is already an entrepreneur, but his business lacks all formal business planning, business model and formal strategy. The fourth student has a business idea based on her knowledge and skills which have developed during her long working experience. By these case stories it is depicted how this kind of flexible entrepreneurial coaching model can benefit students in their personal circumstances. These particular students were chosen as they have so different starting points.

Entrepreneurial Coaching Model – to Whom, What, How and Why?

In this chapter two critical perspectives related to whom and how entrepreneurship education should be implemented are discussed. Firstly, the theoretical foundation behind our decision to concentrate on master students with entrepreneurial intention is described. Secondly, the educational foundation of our entrepreneurial coaching model is discussed.

Entrepreneurship Education and Coaching for All or Only for Those with Entrepreneurial Intention

In entrepreneurship education research there is a lot of discussion around the question whether it would make more sense in higher education institutes to offer some students more comprehensive entrepreneurship education rather than some entrepreneurship education for a large group of students or even all students. The view which supports offering entrepreneurship education widely in HEIs states that  entrepreneurship-specific education may provide students with an opportunity to accumulate transferable skills that can be employed in any organizational context, not only in business start-ups (Solesvik et al., 2013). Entrepreneurship-specific education has stated to accumulate the human capital assets required for entrepreneurial careers in new, established, small, large, public and private organizations (Solesvik, Westhead & Matlay, 2014).

Entrepreneurship education is booming worldwide, and entrepreneurship is becoming increasingly popular in business schools, engineering schools, universities and educational institutions (Fayolle, 2015). European Commission has adopted a very wide description of EE in a recent report saying that entrepreneurship education is taken to cover all educational activities that seek to prepare people to be responsible, enterprising individuals who have the skills, knowledge and attitudes needed to prepare themselves to achieve the goals they set for themselves to live a fulfilled life (European Commission, 2015). Offering entrepreneurship education widely in educational institutions has an important role producing skills to future entrepreneurs so that they are capable of thinking, acting and making decisions in a wide range of situations and contexts (Fayolle, 2015).

On the other hand, if we think that entrepreneurship education should enhance students’ business start-ups, it demands more specific education and coaching for those students who already have entrepreneurial intentions. Donellon et al. (2014) argue that while demand for entrepreneurial competence has led to constant growth of entrepreneurship education, few programmes provide robust outcomes such as actual new ventures or entrepreneurial behaviour in real contexts. They emphasize that beyond acquiring knowledge and skills, entrepreneurial learning also involves the development of an entrepreneurial identity (Donellon, Ollila & Williams Middleton, 2014). Furthermore, the route to self-employment is highly influenced by personal circumstances (Fenton & Barry, 2014).

There seems to be a gap between entrepreneurial intention and action (Van Gelderen, Kautonen & Fink, 2015; Gielnik et al., 2014). Many people form intentions to start their own businesses but do little to translate those intentions into action. Acting upon intentions may be postponed or abandoned for several reasons; new constraints emerge, a person’s preferences change, or feelings of fear, doubt or aversion rise. Van Gelderen et al. (2015) show that self-control positively moderates the relationship between intention and action. It seems that supporting only the development of entrepreneurial knowledge does not necessarily lead to action, whereas factors of entrepreneurial goal intentions, positive fantasies, and action planning have combined effects on new venture creation (Gielnik et al. 2014).

At our university entrepreneurship is considered an important thing to promote since we see it as one way to develop the economy and well-being of the region. Therefore, at our business school we offer all students general entrepreneurial skills which are useful in all organizational contexts and may lead to business start-ups in future. All bachelor level business students get general knowledge and skills of entrepreneurship since these issues are taught in academic courses. They all also practice entrepreneurship skills during their first year in a virtual enterprise which they establish in teams of ten students. After this, all business students also at the bachelor’s level have an opportunity to choose entrepreneurial coaching courses if they have a preliminary business idea and/or entrepreneurial intentions.

The master’s level entrepreneurial studies are aimed at those students who already have entrepreneurial intentions. They choose these studies knowing that the goal is to develop their own business ideas and business models. We have named these studies entrepreneurial coaching to separate them from more general entrepreneurship education. In addition, we think that the term ‘coaching’ describes  our model very well as coaching discussions are an essential part of the process. These entrepreneurial coaching studies are offered also to students from other fields than only business. At the master’s level we have had students from the business, tourism, engineering and healthcare sectors. Several previous studies have also emphasized that entrepreneurship education should move beyond the traditional business school context and offer entrepreneurial learning pathways also to students from other faculties or schools (Jones, Matlay and Maritz, 2012; Crayford et al. 2012).

Educational Foundation for Entrepreneurial Coaching

Fayolle (2015) emphasizes that entrepreneurship education should have a strong intellectual and conceptual founding drawing from the fields of entrepreneurship and education. Similarly Jones et al. (2014) call for stronger pedagogical content knowledge for entrepreneurship education. In his article Fayolle (2013) presents a good generic teaching model for entrepreneurship education. In this paper his model is used as a basis to give a comprehensive description of the educational founding for our entrepreneurial coaching (figure 1).

Figure 1. Educational model of entrepreneurial coaching
Figure 1. Educational model of entrepreneurial coaching

The entrepreneurial coaching studies for master’s level students at our university consist of three courses (5 ECTS each). Students can include these studies in their curricula as elective studies, and they can choose one, two or three of these courses. In the following the studies are described in more detail.

For whom?
The students are studying at Savonia University of Applied Sciences in order to get a master’s level degree. They already have a bachelor’s level degree and at least three years of working experience after completing the bachelor’s degree. They have preliminary business ideas, and/or entrepreneurial intentions. The students’ reasons for participating in these studies vary. Some of them already have quite clear business ideas which they want to develop into solid business models. Some students have the entrepreneurial intentions, but not any clear business ideas. Some of them are already entrepreneurs, but they feel that their business ideas and models need to be clarified.

One clear objective for offering these studies is to increase the number of master’s level students’ business start-ups. However, achieving this goal takes time and the actual starting up may happen years after completing the degree. Another important goal is to give master students an opportunity to take time to ponder their entrepreneurial and personal goals and find versatile information about the industry, markets, competition, etc. which helps them to make decisions.

We also tell our students that these studies give them an opportunity to gather information to make the right decision whether to proceed with the business idea towards a start-up, or to postpone or abandon the commercial use of the idea. This is an ethical issue; we should also help the students to make a no-go decision if, after wide and versatile information gathering and analysis, it seems that the business idea has no commercial potential.

In our entrepreneurial coaching model we mix theoretical knowledge and practice-oriented approaches. The theoretical knowledge contains issues such as opportunity recognition, business model generation, business environment analysis and entrepreneurial skills. These issues are discussed in a kick-off workshop and in on-line materials. The students are expected to find more information about these issues focusing on their own business ideas. Otherwise the studies are very practice-oriented as the students work on their own ideas. The students’ information gathering and individual pondering is supported by coaching discussions when needed.

The coaching teachers also have skills that mix theoretical and practical knowledge. There are two ‘main coaches’, one of them has a doctoral degree in entrepreneurship and has been an entrepreneur herself, the other has a master’s degree in administrative sciences and a long and profound experience in developing business models in organizations. In addition, other professionals at our university can be employed as coaches when their special knowledge is needed (for example innovation management or financial management issues).

The entrepreneurial coaching process starts with a kick-off workshop for the whole group. In this workshop the students are offered short lectures on essential entrepreneurship knowledge. After that the students brainstorm and jointly develop the ideas. They also study how to use business model generation tools.

After that the students start to work on their own business ideas independently and the development process is supported during coaching sessions with the teachers. The coaching teachers also provide ideas on how the students should and could develop the needed network. An on-line learning environment is formed to contribute to the learning process. In the learning environment the students find relevant material, links and they can also ask the coaches questions. The students report on their learning by producing written learning assignments.

The studies consist of three separate courses, and a student can choose only one or two, or all three of them. These three courses have different learning objectives. In the first course the students ponder their own entrepreneurial intentions and skills and form the first business model around their business ideas. In this phase the students critically analyse their own entrepreneurial motivation and skills. The students are advised to enhance their self-reflection with tests which measure entrepreneurial intentions and capabilities.

In the second course they choose and justify one specific part of their business model which needs further studying and gather information related to this. And finally in the third course the students should be able to present holistic and profound business models and plans to show how they are going to turn their ideas into business. At this stage the students should form action plans on how their entrepreneurial intentions will translate into action (see e.g. Van Gelderen et al. 2015). At all stages the students are expected to gather versatile theoretical and practical information.

For which results?
The students develop their business ideas and models and they report on the development processes in the learning assignments. These assignments are evaluated and the students get their grades on the basis of the evaluation criteria which include e.g. the following: setting and achieving the goals of the process, use of versatile and profound knowledge base (theoretical and practical), usefulness of the gained information, versatile and professional discussion and reporting and logical conclusions. The students also get feedback which helps them to move forward in the development of their business models.

We assess the entrepreneurship outcomes of the coaching by following the number of students who participate, the start-ups of the students and new business models developed for the existing firms of the students. However, it is difficult to report on these assessments yet since the processes of the students are long and the actual results often come about later.

Students’ Experiences of Entrepreneurial Coaching

As mentioned, master students’ reasons for participating in entrepreneurial studies vary. In a survey among the students their motives to participate were asked, and we also discussed these motives during a kick-off workshop and coaching discussions. Some of the students have strong entrepreneurial intentions and quite clear business ideas, while some have the intention, but the business idea is still very vague. There are also students who have clear business ideas, but they want to take time to ponder how they could match entrepreneurship with their personal circumstances. And finally, there are students who already are entrepreneurs, but whose business ideas and models need to be clarified. Therefore a flexible coaching model is good for master students as it takes into account the students’ personal circumstances. Here are some citations to describe these different motives:

My goal is to explore profoundly if my business idea has real potential and if I have it in me to be a successful entrepreneur.

I want to attain more knowledge about entrepreneurship. On the other hand, these studies ‘force’ me to reflect my entrepreneurial skills and explore the potential of my business idea.

I want to clarify our firm’s business model. We haven’t done what we should have done at the beginning stage of the firm… Now it is a good time to clarify these essential aspects of our business.

We have students from different sectors; business, tourism, engineering and health care. This gives us a challenge as the students have different educational backgrounds. Business and tourism students already have quite strong general business and entrepreneurship knowledge, whereas engineers and students with health care degrees have studied these subjects much less. Therefore, some of the students expected to have more lectures on general business themes such as forms of enterprise and financial issues.

The execution of the studies is good. However, I expected to get more general business information – I mean basic things about issues which entrepreneurs face when they start a business. Having an opportunity for coaching discussions is great.

The participating students have found it important to get the opportunity and support to develop their business ideas as part of their studies. This seems to be one good way to promote the business start-ups of graduates as well as to enhance the chances of success of their businesses. As Fenton and Barry (2014) also found, entrepreneurial coaching at the graduate level provides a welcome ‘breathing space’ to develop students’ business ideas.

I find entrepreneurial coaching very useful for me. It is great that I have this opportunity to explore the potential of my idea as a part of my studies.

It is extremely important to get support for developing my business idea and get more knowledge from entrepreneurship experts.

The best way to describe the versatile motives, situations and processes of the students might be to tell short case stories. Therefore the stories of four students are told here: Helen and Sarah (innovation based idea), John (existing firm with no formal business model), and Mary (knowledge based idea). The names of the students are changed to ensure their anonymity. The processes of these students are still going on, and therefore the final outcomes and decisions which they will make concerning their business ideas cannot yet be told. These stories describe their entrepreneurial processes so far.

Helen and Sarah are master students from two different fields; Sarah is a business student and Helen is a healthcare management student. They met in an innovation knowledge course where they worked in the same study team and developed Helen’s original innovation idea which is a mobile phone application for persons with a certain type of food allergy. During the first course of entrepreneurial coaching they defined the customer segments for their application, analysed competition and formed their first business model draft. Helen and Sarah concluded in their report that they now have a preliminary understanding of the earning logic of their business. However, they now need a more profound market survey, and they need to plan and design the application. They are planning to focus on these aspects in their second and third entrepreneurial coaching courses and utilize the know-how of our university’s other departments (technology and design management).

John’s friends established a new firm in 2012 after recognizing a new import business opportunity. John started working for the company in autumn 2012 and bought his share of stocks in spring 2013. All three key persons had a technical education and background. Due to the strong demand, the business was good and the customers were found quite easily. The whole company adopted a culture of busy doing; there was no role for planning and foreseeing. John began to think about the future in the longer run. He started his master level business studies and soon realised that there is a huge need in their company to both increase efficiency and plan a proper business strategy for long term success. John took the entrepreneurial coaching studies because of the proper opportunity to take time to think about his own skills as an entrepreneur and also plan his business further. He is preparing the business model for their company. He thinks that the support from the tutoring professionals (coaching teachers) and the opportunity to think and plan by himself and reflect the results with the fellow students and tutors are the main reasons to participate in the entrepreneurial coaching studies.

Mary has a profound professional background as a controller, and she had an idea of starting her own business which would offer controlling and financial management services to entrepreneurs who lack these skills (firms which have been established leaning on the entrepreneurs’ professions). She developed the business model through versatile information gathering from both theory and practice. The practical information was gathered from managers in different sectors, and she also offered these services to one small company in the health care sector and tested the service there as a pilot case. During this process Mary found that there would be actual demand for her service business. However, she started to feel that this business would be too similar to the work she had done as an employee for a long time. Her interest started to focus more on the health care sector during her pilot process, and she now looks for new business opportunities in that sector. She also wants to be a part of a team instead of working as a consultant for a one- woman firm.

By telling these three case stories it is shown how different the starting points of students can be. Therefore we cannot offer some kind of one-size-fits-all solutions in entrepreneurial coaching. Instead, we need to appreciate the personal goals of the participants.

Conclusions and Implications

This study provides guiding principles for good practices in entrepreneurial coaching in higher education, and especially in practice-oriented universities such as universities of applied sciences. The findings of this study show that there is a need for a flexible entrepreneurial coaching model for master level students. On the basis of our experiences it can be said that entrepreneurial coaching should be student focused taking personal circumstances into account. Furthermore, the entrepreneurial studies should be compatible with the students’ curricula. This means that the curriculum is flexible enough and these entrepreneurial coaching studies can be included into the students’ personal study plans.

Using versatile learning methods seems to be good for developing entrepreneurial skills. A kick-off workshop where students become familiar with the business model development combined with e-learning environment and on-line material gives basis for the work which the students do independently. The students’ independent learning is supported in coaching discussions.

During this process the students also reflect and develop their own entrepreneurial identity. As Donellon et al. (2014) argue; if the educational objective is learning for the practice of entrepreneurship, then entrepreneurial identity construction is as important a goal as the development of knowledge and skills. The students are encouraged to critically evaluate their own skills and life goals and reflect them to attributes related to successful entrepreneurship. Context is an important contributor to entrepreneurial identity and the students need to confront their own internal dialogue about how the entrepreneurial identity fits with their social groups’ expectations and their own life expectations. We encourage our students to do this kind of reflection as part of their learning assignments.

Through the entrepreneurial coaching process master level students enforce their capabilities to develop their business ideas and business models. The process also enhances their courage to take their first steps (or new direction) as entrepreneurs. The students of our entrepreneurial coaching seem to have gained similar kind of immediate value as Kirkwood et al. (2014) also reported: confidence, entrepreneurship knowledge and skills, a sense of reality and practical solutions (Kirkwood, Dwyer and Gray, 2014). The coaching process forces the students to gather versatile information related to the planned business model. Therefore they will form stronger confidence in their skills. This and the coaching discussions enhance the courage to take the needed steps.

The entrepreneurial coaching process is an important learning experience also for those students who, after profound information gathering, decide to postpone or abandon the commercial use of their ideas. The process has offered them experimental learning opportunity which may in future give them better skills to recognize and analyse potential business opportunities, and gather versatile information to form solid business models.

This study contributes to entrepreneurship education research by presenting one model how entrepreneurial coaching can be organized in higher education. As Fayolle (2015) states, it is important that entrepreneurship education has a solid theoretical and conceptual foundation, drawing from both entrepreneurship and education. Therefore our model’s educational foundations are also clearly opened in this paper.

There are certain limits to this research, as it was undertaken at one university of applied sciences, and in a unique, regional environment. Therefore, it is influenced by policies, priorities and factors of the region and our university. However, by describing our model openly we hope to encourage entrepreneurship education professionals to develop practice-oriented coaching models using blended teaching methods.


Virpi Laukkanen, Savonia University of Applied Sciences, Principal Lecturer, Ph.D. (Econ.), Virpi.Laukkanen(at)

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