Turning Experience into Experiential Learning: A Framework for Structuring Internships Page 94 - Developments in Business Simulation and Experiential Learning, Volume 46, 2019 ABSTRACT Internships have become a major feature of modern college education, especially in schools of business. They provide students with practical experience in an actual working environment as well as a useful entrée to future job opportunities. This is potential good news for proponents of experiential learning. Internships are by their very nature highly experiential. However, experience is not the same as experiential learning. This paper draws on prior work in experiential learning theory to suggest practical mechanisms for making internships more effective as learning experiences. INTRODUCTION In a paper presented at the 2017 ABSEL conference, Geddes, Cannon and Cannon argued that experiential learning should not be thought of as a type of educational design, but rather, as a learning process. This is consistent with Kolb’s (1984) conceptualization of experiential learning as a cycle of concrete experience, followed by reflection to determine (conceptualize) possible cause and effect, followed by experimentation to determine whether experience supports your conceptualization. The process is very much akin to what we know as the “scientific method,” or more specifically, what Kurt Lewin characterized as “action research” (Lewin, 1946). According to Lewin, action research is an application of the scientific method to social change, where the studies generally take the form of “field experiments.” According to Lewin: Field experiments are basically not different from laboratory experiments. An experiment as opposed to a mere descriptive analysis tries to study the effect of conditions by some way of measuring or bringing about certain changes under sufficiently controlled conditions. The objective is to understand the laws which govern the nature of the phenomena under study, in our case the nature of group life. ... This type of experiment, whether laboratory or field experiment, has as its objective the study of three situations or processes, namely: (a) the character of the beginning situation, (b) some happenings designed to bring about certain change, (c) a study of the end situation to see the actual effect of the happening on the beginning situation. A diagnosis of the before and after situation permits us to define the change or effect; studying the happening should be designed to characterize the factors which brought about this change. (1947, p. 151) Lewin’s formulation is particularly useful for conceptualizing business internships. Students are immersed in a social environment-- an organization in which they are required to address a complex system of interacting human beings, each performing complex, and often times, ill-defined and highly socially sensitive tasks. The students’ behavior, then, becomes a series of real-time experiments in which they engage in an on-going cycle of situational assessment, reflection, conceptualization, action, followed by another cycle based on what they learned from the previous cycle. While this kind of experience may seem intuitively useful, arguing that it is worth incorporating into a business school curriculum demands more than intuition. Indeed, intuition might also lead us to discount the value of internships because their complexity makes each one unique, and hence, unsuited to an education that must necessarily nurture a broad range of generalizable, rather than organizational job, and/or situation-specific skills. The resolution of the apparent conflict between generalizable and situation-specific learning rests in the humans’ natural ability to generalize. Humans naturally extract general patterns and relationships from unique examples. For instance, consider the concept of an organization. We understand what an organization is, even though every organization is different. In fact, even the same organization is different each time we encounter it. Problems, people, relationships, goals, plans, resources, are in continual flux, not to mention the fact that we never see the organization in its entirety, and yet we still recognize it. McDonalds is McDonalds, and we recognize it, not just because of its name and logo, but because it incorporates a host of products, patterns, and procedures that characterize the way it does business. Based on this insight, we might argue that our initial intuition was correct, that we are conditioned to learn from examples, and by extension, the mere completion of an internship would involve the learning of generalizable, and presumably, useful principles. However, if this were sufficient, we could also argue by extension that we don’t need education at all, but only experience. Of course, this makes no sense. The truth is that both idiosyncratic experience and the learning of general principles are useful in education. We naturally recognize patterns and relationships, but knowing what to look for (conveyed in the form of Turning Experience into Experiential Learning: A Framework for Structuring Internships Hugh Cannon Wayne State University hugh.cannon@wayne.edu Bryon Geddes Dixie State University bryongeddes22@gmail.com mailto:hugh.cannon@wayne.edu Page 95 - Developments in Business Simulation and Experiential Learning, Volume 46, 2019 generalizations) provides a powerful tool for accelerating the learning process. TOWARDS A GENERAL STRATEGY FOR MAKING INTERSHIPS MORE EFFECTIVE The first step in developing a strategy for making internships more effective would logically be to specify the nature of effectiveness. Implicit in our earlier discussion is the notion that effectiveness should be tied to learning, and specifically, learning to recognize and respond appropriately to a range of practical business situations. We have argued that, while the human brain naturally looks for and recognizes patterns, we can accelerate the process if students know what to look for. Indeed, much of what we do in education is to provide theories and concepts to help students recognize effective patterns from their experience. Ironically, searching the literature on internships, we found relatively little discussion of how theories and concepts might be useful to enhance the experience of student interns. Rather, they have tended to focus on outcomes rather than the processes by which outcomes are achieved (Gault, Redington, & Schlager, 2000; Narayanan, Olk, & Fukami, 2010 ). D’Abate, Youndt, and Wenzel (2009) address this problem by arguing that the problems with internships is that they are rarely linked to the business school curriculum and pedagogy that precedes them. They argue that “the inclusion of cases, exercises, and simulations … has allowed professors to help their students see connections between classroom knowledge and the realities of the business world. But these in-class activities cannot provide a complete replication of the complexities involved in real world problem analysis and solving (p. 528). They go on to study the relationship between factors related to the internship experience (job characteristics, work environment characteristics, and contextual factors) and internship satisfaction, using internship satisfaction as a proxy for effectiveness. While these job characteristics do no tell us much about what is happening inside the minds of the interns, the study did find that having a supportive mentor in the organization who provides useful information exchange, dialogue, and feedback was strongly related in internship success. This suggests that the satisfaction might have resulted from the internal processes portrayed in the Lewin and Kolb models. Again, using intern satisfaction as a criterion, Narayanan et al. (2010) address the effectiveness of internships more directly by developing a process model in which they link the preparation and effectiveness of interactions among the university, employer, and student to internship effectiveness. They argue, as do D’Abate et al. (2009), that successful internships require careful coordination among the three key participants in the internship experience. Narayanan et al.’s approach is similar to the more general approach taken by Geddes et al. (2017) in characterizing co- creative strategies of experiential education. Drawing on an earlier paper in which they argue that education is actually a Marketing problem (Geddes, Cannon, Cannon, & Feinstein, 2015), Geddes et al. (2015) draw on the concept of service-dominant logic (SDL), FIGURE 1 EXPERIENTIAL LEARNING FROM THE PERSPECTIVE OF SERVICE-DOMINANT LOGIC Source: Bryon C. Geddes, Hugh M. Cannon, and James N. Cannon (2017). Conceptualizing Co-Creative Strategies in Experiential Education: Individual versus Group Approaches.” Developments in Business Simulation and Experiential Learning, 44, p. 60. Page 96 - Developments in Business Simulation and Experiential Learning, Volume 46, 2019 originally drawn from Marketing theory, to describe how teachers (or mentors) interact with students in the experiential learning process. SDL maintains that any service relationship can be reduced to the interaction among operant and operand resources. Operant resources provide a facilitating role to operand resources in process of creating value added to the beneficiaries of the service interaction (in our case, the student). Teachers provide operant resources to students in the form of guidance regarding what to study and assistance in understanding its nature and relevance. These are the general patterns and relationships we referred to earlier that teachers provide -- what D’Abate et al. (2009) call “classroom knowledge” -- to help students identify the relevant patterns in the working environment to which they must respond. Figure 1 portrays Geddes et al.’s conceptualization of the experiential learning process in the context of service-dominant logic. While Geddes et al.’s (2017) framework is supportive of D’Abate et al.’s (2009) and Narayanan et al.’s (2010) approaches it is more robust in that it does not presume the active participation of all three actors – the university, the employer, and the student. This is important in that, as both D’Abate et al. and Narayanan et al. point out, the active participation of all three actors is rarely present to the degree needed for an effective internship. And this is not to mention the host of non-university sponsored internships, or simply the random employment students often engage in, either for experience and/or to keep bread on the table. Is there any reason a student flipping burgers at McDonald’s couldn’t learn from working on the ground level from the most effective fast-food franchise in the history of the world? The question is, where do the necessary operand resources come from in this situation? And how do they interact with the student’s operant resources, or vice versa when the student engages in the experiential learning cycle and begins asking probing questions or having insights that serve as operant resources to other participants in the McDonalds’ organizational system? We will again draw on the stream of work by Geddes, Cannon, Cannon, and Feinstein (2015) to address this question. ADDRESSING THE PROBLEM OF MISSING ACTORS In 2018, Geddes, Cannon, and Cannon presented a paper entitled, “Addressing the Crisis in Higher Education.” Drawing on Buckminster Fuller’s (1982) concept of the knowledge doubling curve, they cited a 2013 study in which knowledge was estimated to be doubling every 13 months, and was projected to soon be doubling every 12 hours (Schilling, 2013)! In this kind of environment, how can students hope to even keep up, much less get ahead of the knowledge curve? Their answer was drawn from the management literature on absorptive capacity (Cohen & Leventhal, 1990). Absorptive capacity (AC) emerged out of the need to understand how organizations adapted to accelerating rates of technological change. As the literature developed, it took on a more generalized approach, addressing how organizations adapted to the accelerating growth of knowledge in general, where any type of knowledge FIGURE 2 VISUALIZING INDIVIDUAL ABSORPTIVE CAPACITY Source: Hugh M. Cannon, Bryon C. Geddes, and Andrew Hale Feinstein (2014). “Experiential Strategies for Building Individual Absorptive Capacity.” Developments in Business Simulation and Experiential Learning, 41 (March), 378-389. Page 97 - Developments in Business Simulation and Experiential Learning, Volume 46, 2019 might trigger changing market conditions that would cause one company to fail while another succeeded. Cohen and Leventhal dedicate a section of their seminal article to a discussion of individual absorptive capacity (IAC). Burns and Gentry (1998) draw on this concept, suggesting that it might provide a means of increasing the effectiveness of simulation games. Cannon, Feinstein, Friesen, and Yaprak (2013) expound the theory, discussing simulation games might be used to develop IAC (as opposed to the other way around). In 2014, Cannon, Geddes, and Feinstein developed a comprehensive model of IAC, breaking down its various components and showing it might provide students with a key to rapid adaptation in a new working environment. This, of course, is precisely what students encounter in an internship. It doesn’t preclude drawing upon mentor support (operant resources) from teachers and/or company supervisors and colleagues. Indeed, it addresses how to use them. However, it provides a prepackaged operant resource – a set of guidelines for quickly recognizing, absorbing, and transforming the knowledge needed to address the needs of a new working situation. Figure 2 presents the model. Figure 2 provides a general template for helping students navigate a new educational experience, or in our case, a new internship. It allows for the use of mentors (interpersonal sources portrayed in box d). However, this failing, it also suggests impersonal, such as Google and related search tools. Consider our student who ends up flipping burgers at McDonalds. Direct experience will tell her how she feels, the challenges she faces, and the things she likes about the job. Direct observation and talking with her colleagues will tell her how her colleagues feel about the same issues. She need only put herself in the manager’s shoes and ask how she might do things differently. Talking to the manager provides a good start (interpersonal knowledge). She can then consult Google to find out what problems McDonalds (or other fast food franchisees) face to reality check her perceptions and get ideas about what is being done in other locations to solve the problems (acquisitive solutions, box g), broaden the search to see how other companies have addressed analogous problems (adaptive solutions, box h), and then begin thinking creatively in search of radical solutions (inventive solutions, box i). Here she would focus on manipulating a much broader range of knowledge, drawing on a full panoply of knowledge and thinking skills (j, m, and n, with special emphasis on n). For instance, she might draw on her knowledge of social media, or her experience with neighborhood involvement and conceptualize a way of involving fellow employees in community activities that would not only mobilize customer interest, but also be intrinsically fulfilling and motivating to the employees. In conjunction with this, she might work on ways of linking these activities to a sense of identity and pride as a member of the McDonalds team. Obviously, the model in itself will not prepare a student to jump into an internship unassisted and emerge with a whole new understanding of every level at which the organization operates. Cannon et al. (2014) suggest specific activities that might be incorporated into an experiential curriculum to develop both the skills and instincts required to use the model. These include the repetitive use of exercises involving the use of interpersonal and impersonal sources of information, drawing on and seeking relevance from one’s own collection of knowledge and experience, reflective discussion of the thinking skills and discipline used in the problem-solving exercises (cases, etc.) addressed in class, working on self-insight to understand and harness personal motivation and interpersonal skills. The repetition is important to ensure that the skills are practiced and internalized, along with the instinctive habit of applying them. Again, the purpose is to provide a stimulus to the student’s ongoing participation in the experiential learning cycle described in Exhibit 1, recognizing that operant resources can be packaged and/or discovered in any number of locations, from personal interactions with mentors or just knowledgeable friends, impersonal sources such as the Internet, or simply by delving deeply into one’s own memory and experience. Figure 3 casts the IAC model in the three-stage process framework suggested by Narayanan et al. (2010). Their framework addresses the actions taken by the university prior to the student internship, the activities carried on during the internship itself, and the outcomes of the internship program. The Exhibit highlights the preparatory activities incorporated into the curriculum as antecedent conditions, followed by the internship activities themselves, then summarizing the outcomes expected when the IAC FIGURE 3 THE IAC MODEL FROM THE PERSPECTIVE OF NARAYANAN ET AL.’S “PROCESS PERSPECTIVE” Page 98 - Developments in Business Simulation and Experiential Learning, Volume 46, 2019 approach proves effective. Once again, the key benefits relate to the confidence, self-direction, insightfulness, and competence the program engenders in the students, along with the fact that the program does not depend on a high level of funding or industry support. Significantly, the kinds of activities we have outlined are not systematically incorporated into most business school curricula. Most courses are offered as stand-alone modules with little coordination with other courses, much less with the systematic incorporation of repetitive activities to build skills as opposed to simple understanding. This, however, creates an opportunity for programs that incorporate these features, enabling them to use internships and other outside learning experiences, even when employing companies are not disposed to cooperate. SUMMARY AND CONCLUSIONS The purpose of this paper was to present a robust model for increasing the effectiveness of student internships. Our criterion for effectiveness is that the model encourages students to consciously engage their internship as an experiential exercise, not just a job and potential entrée to future fulltime employment. We break this down into two supporting objectives. First, it should help interns recognize the relevance of prior learning to practical working situations – mapping the concepts they have learned onto the new situations encountered in their internship. This serves to validate the knowledge and skills they have learned, giving the students confidence in their ability to function in new, challenging work environments. The second objective is to provide the generalizable skill to “self-mentor,” exercising what we have referred to as individual absorptive capacity (IAC). In the end, this is the more important of the two objectives. This is because it encompasses the first objective. IAC enables a student to find, absorb, and utilize the resources needed to identify the relevant patterns and relationships underlying unfamiliar business problems, either by directly utilizing the tools they have acquired in school, by extracting them from interpersonal or impersonal sources, or by constructing new tools based on their ability to see analogies to other patterns they encountered in unrelated situations. From the perspective of a business school strategist, the robustness of the IAC approach is that it can be implemented at relatively low cost, thus providing a competitive opportunity to smaller or perhaps under-funded programs. The approach does not depend on the kind of industry support that is often more available to larger, more prestigious programs. Nor does the approach require exceptionally well-prepared students. It only requires time, practice, a high level of student involvement, and a coordinated supportive curriculum. While the approach may be applied in large, well-funded programs, these are often less flexible because of the potential intractability of the renowned scholars they have attracted who have a high degree of independence and value their own approaches over those proposed by a school’s strategic plan. The approach, then, promises to broaden the accessibility to effective internships, thus contributing to the overall competence of future business school graduates. Burns, A. C., & Gentry, J. W. (1998). Motivating Students to Engage in Experiential Learning: A Tension-to-Learn Theory. Simulation & Gaming, 29, 133–151. doi:10.1177/1046878198292001 Cannon, H. M., Feinstein, A. H., Friesen, D. P., & Yaprak, A. (2013). The Role of Simulations in Organizational Learning: Building Individual Absorptive Capacity. Developments in Business Simulation and Experiential Learning, 40, 333–343. Retrieved from http:// absel.org/ Cannon, H. M., Geddes, B. C., & Feinstein, A. H. (2014). Experiential Strategies for Building Individual Absorptive Capacity. Developments in Business Simulation and Experiential Learning, 41, 378–389. Retrieved from http://absel.org/ Cohen, W. M., & Levinthal, D. A. (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35, 128–152. doi:10.2307/2393553 D’abate, C. P., Youndt, M. A., & Wenzel, K. E. (2009). Making the Most of an Internship: An Empirical Study of Internship Satisfaction. Academy of Management Learning & Education, 8(4), 527–539. doi:10.5465/ amle.8.4.zqr527 Fuller, R. B. (1982). Critical Path. New York, NY: St. Martin’s Griffin. Gault, J., Redington, J., & Schlager, T. (2000). Undergraduate Business Internships and Career Success: Are They Related? Journal of Marketing Education, 22(1), 45– 53. doi:10.1177/0273475300221006 Geddes, B. C., Cannon, H. M., & Cannon, J. N. (2017). Conceptualizing Co-Creative Strategies in Experiential Education: Individual versus Group Approaches. Developments in Business Simulation and Experiential Learning, 44. Retrieved from http://absel.org/ Geddes, B. C., Cannon, H. M., & Cannon, J. N. (2018). Addressing the Crisis in Higher Education: An Experiential Analysis. Developments in Business Simulation and Experiential Learning, 45. Retrieved from http://absel.org/ Geddes, B., Cannon, H., Cannon, J., & Feinstein, A. (2015). Developing Educational Strategies for Experiential Learning: An Application of Service Dominant Logic from Marketing. Developments in Business Simulation & Experiential Learning, 42, 226–232. Retrieved from http://absel.org/ Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Prentice Hall. Englewood Cliffs, NJ. Lewin, K. (1946). Action Research and Minority Problems. Journal of Social Issues, 2(4), 34–46. doi:10.1111/ j.1540-4560.1946.tb02295 Narayanan, V. K., Olk, P. M., & Fukami, C. V. (2010). Determinants of internship effectiveness: An exploratory model. Academy of Management Learning & Education, 9, 61–80. doi.org/10.5465/ amle.9.1.zqr61 Schilling, D. R. (2013). Knowledge Doubling Every 12 Months, Soon to be Every 12 Hours. Retrieved September 30, 2017, from http://www.industrytap.com/knowledge- doubling-every-12-months-soon-to-be-every-12- hours/3950 REFERENCES