Turbulence Ahead! – Engaging Students with Authentic, Collaborative Problem Solving Activities. Sami Nurmi Faculty of Education, University of Turku, Finland and Timo Lainema Turku Centre for Computer Science, and Turku School of Economics and Business Administration, Turku, Finland
Abstract: We briefly discuss about the challenges the modern business environment sets for business schools. We then introduce some argumentation for using learning tools, which provide realistic and complex models of reality, are authentic, facilitate continuous problem solving and meaningful learning, and embed learning in social experience. We also describe our current research based on the use of a dynamic, interactive business game and represent some preliminary findings. The main results from our study are that using dynamic learning tools like the one described in this paper can provide authentic, motivating and engaging environments, which can function as a shared frame of reference. We also conclude that realtime processing and interactivity of the learning tool is an important addition if we want to be able to represent realistically cross-functional business processes.
INTRODUCTION Too often knowledge acquired in schools lies inert. The biggest challenges in business education (as well as in other subject domains) are difficulties in applying theoretical subject knowledge in real life settings, inabilities to handle complex and ill-defined problems, and the lack of consistent and holistic conception of business processes. Graduate students of business management are not well prepared for the complex problems and situations they will face in real- life working contexts. This is partly due to the traditional teaching methods, which don’t
help students to face the comp lexity and cope with ambiguity and uncertainty of real business world they will inevitably face when taking positions in working organizations (Aram & Noble, 1999). These traditional forms of instruction (e.g. lectures) are often found to produce inert kno wledge, which cannot be applied in complex situations (Bransford et al., 1991), and even intermediate experts of economics may have enormous difficulties in applying their knowledge and skills in realistic problem-solving situations (Mandl et al., 1994). One of the main reasons for the inabilities of traditional teaching methods to facilitate the development of flexible and useful knowledge and skills is the lack of contextualizing or anchoring the content being learned. If content is separated from its authentic context where content knowledge and skills are used in real life, it will produce inert or impoverished knowledge. In such impoverished environments, learning becomes the memorization of seemingly abstract, self-contained entities, not useful tools for understanding and interacting with the world (Barab et al., 2000).
Furthermore, there exists a lack of integration between different functional areas of business studies (e.g. accounting, marketing, management), which makes it very difficult for students to develop coherent mental models about the business world and strategies in whole (Selen, 2001). This is a clear example of stripping content out of context and conditions in which it is used; separating different domain areas from each other and from their realistic intertwined existence. What is needed in business education is a process approach. Walter and Black (2000) state that the flexible and organizational understanding of the business world can only be accomplished by presenting the study of business as a series of integrated activities. However, we must not neglect the learning of formal knowledge and construction of abstract ideas (Lehtinen, 2002). On the basis of the issues discussed above we argue that changes are needed in the teaching me thods in the domain of business studies. The main reason for the use
of the simulation we describe here is to create an authentic and collaborative learning environment, where computer simulation is used as a tool for situating the business content being learned in its authentic contexts in challenging way.
THE CASE OF DYNAMIC BUSINESS GAME The simulation we are introducing, Dynamic Business Game (DBG), is a computer-based simulation, which creates a complex and authentic- like environment for learning of business studies. DBG models the managing of a manufacturing company with main decision-making functions, and it includes a market engine creating demand and supply. This construction is operated in real-time, which brings along some advantages not met in conventional, batchprocessed games. Decision- making and feedback from the decisions made takes place in interactive real-time mode. Decisions are made continuously whenever there are virtual market events, which need to be reacted to by the participants. These market events emerge as results of all the business decisions made by each participating company. In the interactive model decisions are made as soon as they are needed or at least as soon as the decision-maker notices that the market situation needs actions from him.
THEORETICAL BACKGROUND OF DESIGNING DYNAMIC BUSINESS GAME The most important theoretical principles that have guided our efforts to design DBG can be justified as follows:
• PROVIDE REALISTIC AND COMPLEX MODEL OF BUSINESS FUNCTIONS. The authenticity of learning situations and tasks is assumed to be very important factor in facilitating higher order learning (Brown et al., 1989). The basic idea is to anchor learning of knowledge and skills into meaningful situations and activities of everyday life
(Goldman et al. 1996; Barab et al. 2000). In DBG simulation the problems and situations students are facing are designed to be very alike that those in real- life working contexts and students can apply their schooled knowledge and skills to them. • USE AUTHENTIC TOOLS AND MULTIPLE REPRESENTATIONS. The use of technology has been found to improve problem-based learning (Hoffman & Ritchie, 1997), enhance the motivation of students and allow active criss-crossing through content being learned (Edelson et al. 1999). In short, computer-supported learning environments can make the learning activities and situations more meaningful for students. Technology can play a valuable role in allowing the students to practice the use of these tools by representing tools artificially (Kozma, 2000). • FACILITATE
CONTINUOUS
PROBLEM
SOLVING
AN D
MEANINGFUL
LEARNING. One of the biggest challenges of education is to overcome the problem of inert knowledge. Technology-based learning environments can engage students in complex thinking about learning topics, which, in turn, can lead to better comprehension about the topics and development of useful learning skills (Jonassen, 2000). The main pedagogical basis behind DBG is the idea of “learning with technology” (Jonassen et al., 1999), which is congruent with constructivist perspective as seeing learning as an active meaning making and knowledge building in an interaction between learner, available tools and his/her social and physical environment. • EMBED LEARNING IN SOCIAL EXPERIENCE. Learning is an inherently socialdialogical activity (Cunningham & Duffy, 1996). Collaborative working fits well with constructivist approach, and group work is used to share alternative viewpoints and challenge as well as help develop each alternative points of view. The essential feature of DBG environment is the use of simulation in small groups (or teams), in such a way that every small group manages their own company and, thus, collaborative action becomes
very important. In short, the environment aims to promote dialogical interchange and reflexivity among group members. • SUPPORT STUDENTS LEARNING. In addition to specific opportunities that simulation offers to situate learning in realistic settings, it also offers possibilities to adapt reality to support learning (de Jong, 2001). In DBG it’s possible to, e.g., change the speed of game clock, or modify the supply and demand of the market according to the needs of the students. Another way to adjust the simulation is model progression (e.g. White & Frederiksen, 1990; Swaak, van Joolingen & de Jong, 1998) method, which means that the complexity of simulation can gradually be increased during working. It is also possible to arrange additional instructional supporting activities besides mere simulation working in order to overcome the difficulties in simulation environments found in previous studies (de Jong & van Joolingen, 1998). Our own approach was to arrange home assignments between simulation sessions.
OVERVIEW OF THE CURRENT RESEARCH At the moment we have conducted two separate studies with DBG. The first one was arranged with 19 students of business administration, and the course lasted 24 hours in addition to several home assignments. The second one was given to 28 students of business studies and educational sciences (14 of both). In this 20 hours course we were able to compare the working and learning of intermediate experts and novices. We have now collected a large amount of both quantitative and qualitative data. The purpose of the researchers was to understand the actual collaborative learning and working processes when using the simulation, and to find out what are the effects of simulation course on students substance knowledge and attitudes towards ICT, team work and business studies.
PRELIMINARY RESULTS AND DISCUSSION These preliminary results are based only on the effects of simulation working and feedback and experiences from the students. When reviewing students’ scores on pre- and posttest questions in study 1, the effects of playing were significant, but the overall increase in score was quite modest, average scores increased only from 12.7 to 13.9 points (max. 21)(table 1). [Table 1 here] We were not quite satisfied with our first test questions, which dealt too much with fact knowledge, and the content of our problem solving tasks didn’t match well with the issues students had to face during simulation working. It seems to be the case that by its very nature the results of simulation working are so qualitatively different from just acquisition of new factual knowledge that those effects cannot be detected by traditional knowledge tests (c.f. Swaak & de Jong, 1996). Swaak et al. (1998) conclude that it is not clear how the effects of learning from simulation are to be measured. Further they infer that simulation working produces intuitive (or implicit or tacit) knowledge, which tends to be difficult to verbalize and to measure. As a consequence in study 2 we changed our test questions more towards problem solving and knowledge applying tasks as well as concept mapping assignments.
In study 2 the simulation working has greater and statistically more significant impact on test scores (see table 2). The overall mean scores increased from 8.8 to 11.1 points (max. 16). When reviewing the differences between novices and intermediate experts it can be seen that simulation working had different effects on their test scores, although both groups improved significantly. In short, the interaction effect of the level of expertise and simulation working was significant in MANOVA (table 3). Students of economics had much higher scores on pretest than novices, but as a consequence of simulation working the mean development of
scores were greater with novices (see figure1). However, intermediate experts still outperformed novices, but the gap was narrowed. [Table 2 here] [Table 3 here] [Figure 1 here] We also asked participating students to reflect their experiences and give feedback from simulation working. According to these comments several conclusio n can be made. First of all, all the respondents regarded DBG as authentic. They thought that the questions and problems they were dealing with during the game could also be faced in real working- life context of any manufacturing company. Participating students evaluated that DBG represent authentic and complex business processes in a realistic way. For example students said, that “What made this playing feel so real was that you had to take care of so many things simultaneously to get the firm do well” and “I realized that enterprise is always a risk. You can’t be sure that even reasoned decisions will lead to anything but a loss.” Secondly, the simulation was valued as very engaging and working with it was experienced as meaningful and interesting. Especia lly the real- time element of the game was seen as a very important feature which affects on authenticity and engagement, because real- time processing “makes it possible to see the consequences of own decisions and actions”, “…shows how important it is to make your decisions as quick as possible and before your competitors”, and “…forces to observe the market situation, analyze the actions of other companies and revise your strategy”. Thirdly, especially participants assessed the collaboration around simulation as very fruitful and useful. They said that the simulation could function as a shared frame of reference, which allows talking about difficult issues even without correct concepts: “Our team work succeeded well, and we were all aiming to get our company to show a profit. I could say that the working was very intensive during the whole course, and the game inspired
our discussion”. Students also saw DBG as very motivating teaching and learning method for business education, and based on their opinions it can be said that simulation could maintain task related orientation during the whole course. When asking students to reflect, what the most important thing they have learned during the simulation course was, the majority stated that it was acquiring the consistent conception of business processes as whole. They said that they could now understand how many different factors are affecting to the success of a business company: “…the most important thing that I have learned is how different parts of a company interact and what kind of things you have to take into consideration in such a company as this… you could see the flow of the whole process of the product from the raw materials to the end product and the different procedures in between”. In all, the overall responses about the whole course were very positive without any exception.
In conclusion we state that simulation working can be regarded as authentic and very engaging as well as meaningful and motivating for students, and it could facilitate the development of deeper understanding about realistic business processes as a whole. However, our qualitative analyses about small groups’ working processes are not done yet, and they will shed new light on many of our research questions and conclusions in future.
REFERENCES Aram, E. and Noble, D. (1999). Educating prospective managers in the complexity of organizational life. Management Learning, 30(3), 321-342. Bransford, J., Goldman, S. & Vye, N. (1991). Making a difference in people’s ability to think: Reflections on a decade of work and some hopes for the future. In R. Stenberg & L. Okagaki (eds.) Influences on children. Hillsdale, NJ: Lawrence Erlbaum. Barab, S., Hay, K. & Duffy, T. (2000). Grounded constructions and how technology can help. CRLT technical report.
Brown, J., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational researcher, 18(1), 32-41. de Jong, T. (2001). Highly interactive learning environments: Simulations, games, and adventures. Abstracts of the 9th European conference for research on learning and instruction (EARLI). Fribourg, Switzerland. Aachen: Verlag Mainz. de Jong, T. & van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179-201. Edelson, D., Gordin, D. & Pea, R. (1999). Addressing the challenges of inquiry-based learning through technology and curriculum design. The journal of the learning sciences, 8(3&4), 391-450. Goldman, S., Petrosino, A., Sherwood, R., Garrison, S., Hickey, D., Bransford, J. & Pellegrino, J. (1996). Anchoring science instruction in multimedia learning environments. In S. Vosniadou, E. De Corte, R. Glaser & H. Mandl (eds.) International perspectives on the design of technology-supported learning environments. Mahwah, NJ: Lawrence Erlbaum. Hoffman, B. & Ritchie, R. (1997). Using multimedia to overcome the problems with problem based learning. Instructional science, 25, 97-115. Jonassen, D., Peck, K. & Wilson, B. (1999). Learning with technology. A constructivist perspective. New Jersey: Prentice Hall. Jonassen, D. (2000). Computers as mindtools for schools. Engaging critical thinking. 2nd edition. Mahwah, NJ: Lawrence Erlbaum. Kozma, R. (2000). The use of multiple representations and the social construction of understanding in chemistry. In M. Jacobson & R. Kozma (eds.) Innovations in science and mathematics education. Advanced designs for technologies of learning. Mahwah, NJ: Lawrence Erlbaum. Lehtinen, E. (2002). Developing models for distributed problem-based learning: Theoretical and methodological reflection. Distance education, 23(1), 109-117. Mandl, H., Gruber, H. & Renkl, A. (1994). Knowledge application in complex systems. In S. Vosniadou, E. De Corte & H. Mandl (eds.) Technology-based learning environments. Psychological and educational foundations. Berlin: Springer. Selen, W. (2001). Learning in the new business school setting: A collaborative model. The Learning Organization, 8(3), 106-113.
Swaak, J. & de Jong, T. (1996). Measuring intuitive knowledge in science: The development of the what-if test. Studies in Educational Evaluation, 22(4), 341-362. Swaak, J., van Joolingen, W. R. & de Jong, T. (1998). Supporting simulation-based learning; The effects of model progression and assignments on definitional and intuitive knowledge. Learning and instruction, 8(3), 235-252 Walker, K. & Black, L. (2000). Reengineering the Undergraduate Business Core Curriculum: Aligning Business Schools with Business for Improved Performance. Business Process Management Journal, 6(3), 194-213. White, B. & Frederiksen, J. (1990). Causal model progressions as a foundation for intelligent learning environments. Artificial Intelligence, 42, 99-157.
ABOUT THE AUTHORS Sami Nurmi Researcher Faculty of Education, University of Turku, Finland Tel. +358 2 333 8747
[email protected] Sami (M.Ed.) works as a researcher and prepares his PhD on collaborative learning using dynamic business game simulations. He has specialized on technology based learning environments and learning. Timo Lainema Researcher Turku Centre for Computer Science and Turku School of Economics and Business Administration, Department of Information Systems P.O. Box 110, Turku, FIN-20520, Finland Tel. +358 400 445 913
[email protected]
Timo (M.Sc. & Lic.Sc. in Economics and Business Administration) is finishing his PhD on learning through using real-time processed business games. He is the author of Dynamic Business Game (also called as Realgame) described in this paper.
Repeated measures T-Test test scores
mean
N
st. dev.
pretest score
12.69
16
3.301
posttest score
13.88
16
3.243
*** p
