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Article Excerpt
Introduction and Background
Computer-based simulations are an interactive means of teaching business strategy to students in university business schools. The potential benefits of the approach include greater levels of student participation in study and a fuller appreciation of the dynamic complexities involved in running a business. However, attaining positive learning outcomes for a participating student cohort is far from guaranteed when adopting this approach. Previous research shows that games are not self-teaching and some students can become caught in a single- or even zero loop mode of learning (Moizer et al., 2006). This article seeks to explore the causal feedback mechanisms at work when a computer-based business strategy simulation game is used as a vehicle for promoting learning.
Moizer et al. (2006) argue that when teaching business strategy using a computer-based simulation game, its integration within the broader module design is critical. An effective module design is an important determinant of whether students follow a zero, single or double-loop learning mode (see Argyris and Schon, 1974 and Snell and Man-Kuen Chak, 1998 for an exposition of loop learning concepts). A number of issues relating to the integration of business strategy simulation games into module design are highlighted. These findings are supported within the broader simulation and gaming literature. For instance, the selection of an appropriate game, in terms of both the type of technology and the complexity of the simulation is important. A number of authors indicate that whilst high levels of complexity and verisimilitude can be achieved for a simulation game, simple games that students can master easily are often more appropriate for many student groups (Lane, 1995; Low, 1980; Burns and Gentry, 1998). Other issues identified by Moizer et al. as being potentially central include whether assessment is used formatively or summatively, how students are encouraged to learn on reflection, and how teaching is orientated towards the development of strategic thinking capabilities amongst students. Whilst all of these factors are important, and are widely referred to in the literature, there is arguably less understanding of the full causal relationships between module design and learning. In particular, there is a need to recognize that there are intervening variables captured within this relationship. Furthermore, these variables are embedded within causal feedback loops. Causal loop diagrams are an established means of mapping out these feedback mechanisms and tracing through the consequences of decisions and actions (see Sterman, 2000 for an overview of causal loop diagramming).
Through using causal loop diagramming, the intention of this study is to extend the authors' earlier work in order to gain a more complete picture of how the variables associated with student learning are interrelated. Readers interested in the literature relating to learning in the context of simulation games are referred to these earlier studies (see Moizer et al. 2004; 2006).
In the next section of the paper, the context within which the study was undertaken is described. Following this the research objectives and methods used to conduct the research are outlined. Results are then presented and discussed with reference to relevant literature. From these results a causal loop diagram is developed and explained. The final section of the paper discusses the benefits and limitations of both the study results and the method of enquiry used. Possible avenues for further research are also outlined.
Study Context
The Business Strategy Game (BSG), developed by Thompson and Stappenbeck (1998) is used to support the learning of business strategy within the University of Plymouth Business School. It is the student's use of this game that provides the focus for this study. The BSG is a total enterprise management game which simulates the high level decisions of businesses serving the global marketplace for athletic footwear. The simulation takes the form of a game which is interactive and allows participants to take on the role of Directors who manage this global concern. Participants form individual businesses and compete against each other for market share.
Decisions are made by the respective businesses over a sustained playing period which equates to several simulated years. Participants are required to submit a series of business decisions which cover activities such as the production, marketing and distribution of athletic footwear to worldwide markets. Decisions are high-level and strategic, and have a simulated timeframe of one year. The decisions are processed on an administrator's spreadsheet, and the simulation game then rolls on to another year's play. A score based on a number of performance metrics (profit, market share, capitalization, sales volume, etc) is determined. This results in the groups moving up or down a business league table. For this study, the BSG was run over eight decision periods with final year undergraduates reading for either marketing or business degrees.
Research Objectives and Methodology
The intention of this study is to extend previous research, in order to explore the causal feedback mechanisms associated with learning from playing a computer-based business strategy simulation. The supporting objectives are to:
* identify the key variables associated with learning in this gaming domain; and
* structure the cause-effect relationships between variables using feedback loops.
The broad research approach adopted was inductive in nature. The purpose was to allow a conceptual feedback model to emerge from qualitative insights gained from business simulation game users. Hence, the study does not aim to fully validate and empirically test a model. Rather, the emphasis is on presenting a model to stimulate discussion about the interaction of learning variables. This work will enable future deductive research investigation to be undertaken employing quantitative measurement.
In order to achieve the objectives of the research, a study was designed which consisted of three major phases:
1. Learning input phase
During this phase, students were introduced to the BSG through a briefing session. They were informed of the intended learning outcomes of the exercise, how the game functioned and how to play it. They were provided with a player's manual to enable them to begin using the game. Prior to, and during the gaming period students also attended a series of lectures on corporate strategy. Earlier lectures were used to ground the students in the subject of strategy, with later course lectures focusing more upon contextual issues in strategy. Interim feedback on the progress made by the playing teams was available after each 'yearly' gaming round.
2. Data collection phase
Data was collected through a series of debriefing sessions which were run at the game's completion. These sessions took the form of meetings with each of the twelve teams of students that took part in the simulation. The purpose of these meetings was to stimulate a student-led discussion which focused on the learning efforts that took place through playing the simulation, and the key factors influencing that learning. The data collection approach was qualitative in nature, and utilized a semi-structured interviewing approach (see Thorpe et al., 2002). Discussions were up to 30 minutes in length, and were recorded and transcribed for full analysis. The approach adopted for data analysis broadly followed the guidelines of Marshall and Rossman (1989) and Miles and Huberman (1994).
3. Model building phase
The output from the data collection phase was a set of 12 interview transcripts which were coded and reduced to produce a meta matrix (Miles and Huberman, 1994) summarizing the key issues highlighted during each of the interviews. By comparing and contrasting the themes emerging from the reduced interview data it was possible to identify important variables that appeared to be linked to learning within the student groups. An understanding of how these key variables were interrelated also emerged. Hence, the data gathered facilitated the development of a conceptual model representing the key causal elements of the learning process. Particular emphasis was placed on representing how these elements reside within causal feedback mechanisms.
Results and Discussion
Key learning variables
Analysis of the debriefing interviews indicated that approaches to planning and team decision-making processes used were key drivers associated with learning. There was strong evidence that the planning process of five of the six groups that had demonstrated more effective learning involved 'purposeful change'. In four cases, the groups had developed formal plans and/or objectives during the early stages of the game but later switched to a more emergent approach, developing well considered responses to the evolving gaming environment. In one case, an initial emergent approach was discarded in favor of a more formal planning approach. In the case of all other groups (none of which exhibited evidence of significant learning), planning and purposeful change were far less evident. In most cases, groups adopted an experimental or responsive approach. Overall, this evidence appears to support the view that an association exists between learning and purposeful change in the strategies adopted. Evidence also exists to suggest an association between learning and an attempt by groups to strategize and apply formal planning (at least in the initial phases of the game). This lends some support to the findings of other researchers. Hornaday and Curran (1996) (who identify an association between formal planning and the performance of business simulation teams), argue that learning plays a key role in this relationship. They propose that the planning process forces the team to learn...
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