COMPUTER SIMULATION, GAMES AND ROLEPLAY: DRAWING LINES OF DEMARCATION Developments in Business Simulation and Experiential Learning, Volume 29, 2002 COMPUTER SIMULATION, GAMES AND ROLEPLAY: DRAWING LINES OF DEMARCATION Andrew Hale Feinstein University of Nevada, Las Vegas andyf@unlv.edu Stuart Mann, Dean University of Nevada, Las Vegas shmann@ccmail.nevada.edu David L. Corsun University of Nevada, Las Vegas dcorsun@ccmail.nevada.edu Keywords: computer simulation, experiential learning, games, role-play ABSTRACT The literature around experiential learning is unclear regarding the similarities and differences among simulation, games, and role-play. In order to appropriately evaluate instructional processes, definitional clarity is necessary. In this article, we provide a definitional foundation and classification scheme for the topics of computer simulation, role-play, and games. The educational and training outcomes of each are discussed, providing readers the means to determine for themselves, the pedagogical appropriateness of simulation, games, or role-play to a given situation. INTRODUCTION This article rises out of frustration, the frustration from reading a wide variety of papers each using words like simulation, games, role-playing, gaming, and symbolic modeling either without definition or inconsistency from one work to another. In part, our intention in this paper is to provide a classification scheme, a taxonomy and nomenclature for simulation. We believe this is necessary for the purposes of assessment and evaluation of instructional processes. To do this, we focus our discussion on the uses of simulation as an experiential methodology for education and training. In the literature, authors waver on their definitions of role-playing, gaming, and computer simulation. Simulation modeling is a well-established technique that duplicates the “features, appearance, and characteristics” of a real business or management system through an iconic or symbolic model (Render & Stair, 1997, p. 692). Many tend to place role- playing and gaming within the context of some kind of general definition of simulation (see Butler, Markulis & Strang, 1988; Cherryholmes, 1966; Pierfy, 1977; and Zuckerman & Horn, 1973 for comprehensive examples of this problem). On the contrary, we argue that simulation cannot be viewed as a collection of methodologies for experiential learning environments if we expect to be able to effectively assess their value. Therefore, role-playing, gaming, and computer simulation are defined as separate activities in an effort to differentiate them for the purpose of evaluating their effectiveness as teaching methodologies. The basis for our arguments will be grounded in the management sciences. That is, we will view simulation as a tool to assist in decision-making, as it would be accomplished in the management of agencies and organizations. The remainder of this paper has the following organization. In the first section, we provide a discussion of experiential learning. We next discuss three types of experiential activities – computer simulation, gaming, and role-play – that repeatedly fall under the general auspices of simulation. We then provide definitions of these activities and give examples from the literature that form the foundation of our discussion. Finally, we explain the importance and effectiveness of simulation in education and training. EXPERIENTIAL LEARNING ACTIVITIES IN BUSINESS AND MANAGEMENT EDUCATION Experiential learning is a participatory method of learning that involves a variety of a person’s mental 58 mailto:andyf@unlv.edu mailto:shmann@ccmail.nevada.edu mailto:dcorsun@ccmail.nevada.edu Developments in Business Simulation and Experiential Learning, Volume 29, 2002 capabilities. It exists when a learner processes information in an active and immersive learning environment. Kolb (1984, p. 236) explained that participants involved in an experiential learning exercise "must be able to involve themselves fully, openly, and without bias in new experiences; they must be able to observe and reflect on these experiences from many perspectives; they must be able to create concepts that integrate their observations into logically sound theories; and they must be able to use these theories to make decisions and solve problems." A recent empirical study has shown that experiential learning activities can increase a learner’s dynamic knowledge (Feinstein, 2001). Findings demonstrate that experiential learning increases learners’ capacity to evoke higher-order cognitive abilities in terms of problem-solving skills and judgment. Grappling with the effective application of pedagogy that includes experiential learning activities, several authors have quoted an ancient statement by Confucius (Kolb, Rubin, & McIntyre, 1974; Specht & Sandlin, 1991): I hear and I forget I see and I remember I do and I understand Specht & Sandlin (1991) believe that "experiential learning focuses on 'doing' in addition to the 'hearing' and 'seeing' that occur in traditional lecture class" (p. 196). They also argue that experiential learning is a structured activity in which material and principles that are encountered are integrated and applied to new situations. There are many types of learning activities currently being used to train or educate students about the theories, principles, and processes of business and management. Of these, three are closely tied types that allow for the immersion of students in a game-like environment and rely heavily on experiential activities as a mode of instruction: role-playing, gaming, and computer simulation. However, many authors group these activities under the general umbrella of simulation. And, as stated earlier, they utilize the term simulation without definition or are inconsistent in its application. FOUNDATION FOR DEFINITIONS The basis for the definition of simulation must begin with its foundation, the model. We use the classic definition of model as a representation of the reality it is constructed to depict. The representation of reality is most often seen as the modeling of a real world phenomenon usually termed “the system.” We recognize that models can take a variety of forms. We intend for our definitions to be equally applicable to verbal models, graphic models, physical or iconic models, and symbolic or mathematical models. Accepting that the model is a representation of reality, simulation can be defined then as the behavior of the model. With a foundation being built in the management sciences, the model will have entities that can be described as a performance measure, decision variables (control variables), parameters (uncontrolled variables), and functional expressions describing the interaction of system components that limit the values of the decision variables (constraints). The behavior we observe, that is defined as a simulation, is the change in any of these entities as one or more of them are allowed to assume different values or constructs. Often, time is involved as we allow different values or attributes to be assumed over a change in time. The above representation is most often illustrated through the use of mathematical symbolism and mathematical models. However, this representation is equally applicable to other models as well. In mathematical models, because we are creating the model with variables, it is quite clear how value changes can occur and the observation of system behavior is obvious. However, in the case of a verbal, physical, or graphic model describing a system, we need to take a different approach to describing its behavior. If we think of the verbal model as a set of statements describing a system, then the observed behavior of this model would be to see if those statements would change as the system moves either over time or space. It should be clear that words would be used to describe the system elements that in the mathematical model would be described via symbols. So, as the system changes over time, different words are used to describe the constructs and variables. A graphic model using artistic elements to depict a system could be redrawn as the system changes. Visible differences would then be described as the change occurred. These differences could be depicted using color differences, size differences, shape differences, etc. A physical model could be observed as it was put through its intended use. One could think of an airframe in a wind tunnel for example. Changes in performance of the airframe would be recorded as the behavior of this model. With these constructs in mind as our basic definitions, we are now ready to tackle defining the terms role-playing, games, and computer simulation. Our basic belief, and one that we will use in the following definitions, is that each is a form of simulation as it has just been defined. We will not use the word simulation unless we intend the totality of role- playing, gaming and computer simulation as we have just presented. ROLE-PLAYING Role-playing allows participants to immerse themselves in a learning environment by acting out the role of a character or part in a particular situation. The participant follows a set of rules that defines the situation and then interacts with others who are also role-playing. This learning activity allows participants to get an in-depth understanding of many of the social interactions that arise when evaluating or solving a problem. An example of a role-play was described by the director of Steps Role Play: 59 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 “A company briefs on its difficulties, such as poor internal communication, and we can act them out in the form of a simple play….The client is then forced to confront the trouble” (Curtis, 2000). For more examples of role-play, see: Thorsteinson & Balzer, 1999 and Yukl, Kim & Chavez, 1999. Problems with role-playing include the fact that participants receive feedback from other participants in the role-playing, regardless if this feedback is congruent with outcomes that would exist in the real world. Concurrently, enforcement of rules of the role-playing can be extremely subjective because the dynamic component of the learning environment relies on other participants' interactions. These other participants can be novices in the subject matter, or poorly equipped to respond in a manner that is congruent with the objectives of the learning activity. Thus, for role- play to be maximally effective, it is incumbent on the instructor to ensure that participants all possess some pre- determined, baseline level of understanding and proficiency. Inherent in role-playing is some measure of interpersonal improvisation. Such improvisation, not unlike the improvisations that are part of a manager’s daily life, requires that participants attend to all forms of feedback available in the environment (Corsun & Enz, 1995). The sources of these data in the context of a role-play may emanate from the self in the form of emotional, cognitive, and physiological reactions to the context, the activity around which the role-play is structured, or to other participants. These data may also derive directly from other participants as one observes the verbal and non-verbal cues others provide. Thus, we contend that regardless of what the explicit purpose of a role-play may be—whether negotiation, promoting cross-cultural understanding, or some other stated, usually skill-centered objective—implicit in any role-play is the secondary purpose of interpersonal skill-building. GAMES AND GAMING Gaming consists of "interactions among players placed in a prescribed setting and constrained by a set of rules and procedures" (Hsu, 1989, p. 409). This interaction that excludes acting, can also include "competition, cooperation, conflict, even collusion" (Hsu, 1989, p. 409). Games of this type are thought to have originated in China around 3000 BC from Wei Chi, the precursor of chess (Hsu, 1989) or from Wie-Hai, a Hindu game (Wilson, 1968). These games were militarily oriented. Winning occurred when one's opponent was defeated through the eradication of his or her armies. The American Management Association created one of the first business management games in 1956 (Miles, Biggs & Schubert, 1986). Current management games are typically centered on an organization, or a functional area of that organization, within a particular industry. Teams are usually formed and are provided with financial, demographic, and other related information on their company. These teams then make managerial decisions on topics such as allocation of resources, marketing strategies, research and development, fee and price structures. These games are typically turn-based or round-based, where teams first make a set of decisions after reviewing preliminary external or competitor variables. Next, the decisions are used to adjust these variables and to evaluate teams' decisions. A new round, based on the adjusted variables, is conducted until a new set of decisions has been made. The process normally repeats itself for a predetermined number of rounds. Teams compete against each other for a limited amount of resources, against a facilitator who is manipulating the external variables, or a combination of the two. Outcomes are typically rewarded for maximizing profitability and creating innovative managerial strategies. Business and management games of this nature have been around for decades (for an in-depth review of these games and their effectiveness as instructional systems, see: Greenlaw & Wyman, 1973; Horn & Cleaves, 1980; Wolfe, 1985, 1993). The greatest weakness of these games is their inability to provide the learner with a dynamic environment. Time, in essence, stands still while the teams are implementing their decision strategies. Then, time jumps forward at the end of each round. Although players are under a time deadline and decision time might be included in the adjustment of variables, players cannot observe the impact or interactions of their decisions with external and competitor variables until the round is complete. Further, creating what-if scenarios is extremely difficult. Decisions are made based upon what happened in the last round, not what is happening at the time. There is an element of role-playing in management games (at least for those involving team play) in that team members interact with one another in producing decisions. By necessity, team members must apply their interpersonal skills in determining courses of action. As a function of their interpersonal elements, role-play and team games provide learning opportunities at a minimum of two levels, content and process. The benefits of players’ application and practice of interpersonal skills, whether in role-play or games, are maximized, possibly even realized, only when the instructor makes this secondary goal explicit when processing the “play”. In essence, if the post-play discussion is focused only around content, and process is ignored, a learning opportunity is squandered. COMPUTER SIMULATION Using a symbolic model, computer simulation attempts to replicate the characteristics of the system through the use of mathematics or simple object representations. The interaction of the functional entities of the system is described with symbols, words, and mathematics. An excellent book on computer simulation modeling is the recent publication by Law and Kelton, 2000. An example of a mathematical technique used to mimic a probabilistic 60 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 process within computer simulation is the Monte Carlo method (for a discussion of Monte Carlo simulation and some of its applications, see: Atkinson, Kelliher, & Lebruto, 1997; Field, Mcknew, & Kiessler 1997; Sheel, 1995). Some symbolic simulations also utilize alphanumeric data for representation (Race & Brook, 1980). Computer simulation can be further defined by describing its underlying model as discrete event, continuous event, or combined event. A discrete event computer simulation uses "blocks of time during which no changes to the system state occur" to simulate variables within the model (McHaney & White, 1998, p. 193). This type of computer simulation uses the arrival of entities or the completion of an event as a cue to adjust the computer simulation time clock. Each movement in time takes place instantaneously, or "in discrete steps" (McHaney & White, 1998, p. 193). An example of a discrete event computer simulation is to observe the behavior of a model of the customer flow in a quick service restaurant. Events such as the arrival of a customer, the completion of cooking a hamburger, and the exiting of a customer from the restaurant all allow for the adjustment of the time clock and the manipulation of variables that are affected by each event. Continuous event computer simulations allow variables within the model to be continuously changing. These models are "based on a defined relationship for the state of the system over time" (Pegden, Shannon, & Sadowski, 1995, p. 433). An example of a continuous event computer simulation is to observe the behavior of the model of the oil temperature in a deep fryer at a quick service restaurant. Suppose a restaurant manager wanted to determine how many deep fryers were needed to perform optimally during the lunch rush. One would first need to determine the maximum capacity of the current fryers. To do this, a manager could first analyze the types and intervals of frozen food being dropped into and removed from the fry oil and their effect on oil temperature. This analysis is useful because as each food item is dropped into and removed from the deep fryer, its associated temperature, size and density affects the oil temperature. The collection of observational data on the usage of the deep fryers could be used to determine the effect of each food item on the temperature of the fry oil. Then, a model could be created representing the fry oil temperature fluctuation during the lunch rush. A determination could be made to see if the fry oil temperature were to go below a critical level for the proper cooking of a particular food item. Because it would be important to know if the oil temperature ever goes below a critical level, continuous event computer simulation methods would need to be implemented. SIMULATORS VS. SIMULATION Several authors have made a distinction between simulation and simulators. Hays and Singer (1989, p. 13) believe that “a simulator is a complex device that provides a highly realistic simulation of the operational situation and provides a situation adequate for practicing and maintaining previously acquired skills”, whereas simulation is the act of immersing the trainee in the simulator. Morris and Thomas (1976, p. 66), assert that simulators are “the media through which a trainee may experience the simulation ” and simulation is “the ongoing representation of certain features of a real situation to achieve some specific training objective.” Hays and Singer (1989), and Kinkade and Wheaton (1972), refer to simulators as training devices. These devices are either part-task trainers or whole-task trainers. Part-task trainers “provide instruction on a small segment of the total operational task, called a sub-task". Whole-task trainers “are used to teach the task as an integrated unit" (Hays & Singer, 1989, p. 13). Iconic models are sometimes called simulators because of their visual, auditory, and kinesthetic representations of a real system. An example of an iconic model is a flight simulator. Typically, these iconic models “are used primarily for training purposes” (Pegden, et al., 1995, p. 5). They may, however, be used for other purposes. For example, some firms, rather than employing random drug or alcohol testing, use computer or mechanical simulators as behavioral tests of workers’ fitness to perform their jobs (Jex, 1987). A notable difference between computer simulations and either role-play or team games, is the absence of an interpersonal element in computer simulations. In contrast to these two other types of experiential learning activities, computer simulation is primarily focused on content. The interpersonal learning associated with a secondary, process focus is typically absent. THE IMPORTANCE AND EFFECTIVENESS OF SIMULATION IN EDUCATION AND TRAINING EDUCATION VERSUS TRAINING Today, simulation methods are used more for training personnel than educating them. Typically, education places the emphasis of learning on factual information whereas training places the emphasis on “the practical, on decision- making, on communication skills, and on doing the job”— dynamic information (Jones, 1995, p. 44). Jones stated, “A general distinction is that training is particularly concerned with the process, whereas education in more concerned with the ‘product’.” One of the challenges of using simulation methods for training is in the evaluation of the process. Product learning tends to be easier to evaluate because it “tends to be clearly defined and measurable so that success and failure can be reflected in statistics” (Jones, 1995, p. 45). Corsun (2000) distinguished between training and education by thinking about scope: 61 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 Training is targeted at the accomplishment of a finite set of tasks, duties, and responsibilities associated with a given organizational role. The knowledge, skills, and abilities required to be a successful role-performer are transferred from the trainer to the trainee by a variety of means. In contrast, education is more general and is not targeted at successful organizational role performance. Education goes beyond knowledge acquisition…developing critical thinking skills, the ability to formulate good questions, and the wherewithal to know how to find answers (p. 10). Although some authors in the 1970’s contended “much evidence has accrued to suggest that elements of simulation play can be transferred or adapted and used consciously as an approach to learning -- both in school and in adult learning,” most researchers were not convinced (Taylor & Walford, 1978, p. 2). These authors explained that many researchers believed it was difficult to evaluate a simulation model’s effectiveness as a learning tool. COGNITIVE IMPLICATIONS Cognitive research over the last few years has begun to reinforce the early indications of the educational benefits of simulation. Researchers believe that they are beginning to understand how the mind stores, retrieves, and utilizes information (McTear, 1988; Wagman, 1993, 1995). Researchers in instructional simulation have thought that this method of learning was effective because “people learn to act by acting; they learn to live by living; they learn to do, by doing; and they learn to understand their ‘spirits’ when they reflect on their interactive activity” (Hyman, 1978, p. 153). Much of case-based reasoning is grounded in this principle. In the view of Bruner (1960) and Schank (1990), a human mind learns through the development of stories. A story is a sequential order of events, occurrences, or interpretations that are taken in and stored, retrieved, and possibly even “told.” Schank believed that people take these stories and develop a script on which to base their actions. People are constantly trying to apply these scripts to new situations and evaluate their similarities. Humans' ability to create, store, retrieve, and modify these scripts to a new situation can be viewed as intelligence. Although the aim of the simulation researcher is not to develop intelligence per se, by providing managers with an opportunity to develop these situated scripts, learners could become better equipped to deal with situations in which similar events occur. MOTIVATION Other benefits to utilizing simulation techniques include learner motivation (Hannafin & Peck, 1988; Loftus & Loftus, 1983; Malone, 1980; Towne, Jong, & Spada, 1993). Motivational interest in simulation stems from the game- like atmosphere that it presents, its competitive components for trying to find the right answer, its ability to immerse the user’s mind, and its “contrast with traditional procedures for teaching and learning” (Hyman, 1978, p. 154). Reich and DeFranco (1994, p. 13) also state that "the tactics of delivery style and goal oriented activities form the basis for a teacher's success in being able to interest students in the topic, then guide them through meaningful exercises that lead to a competent grasp of the subject." Further, simulation allows students to “practice their skills of decision making and skills of planning alternative strategies” and evaluate the outcome of their decisions (Hyman, 1978, p. 155). Loftus and Loftus (1983) state that simulation also allows for a variable reinforcement ratio (a variable ratio changes the time between, or number of, responses for a learner to acquire a reinforcement). This reinforcement technique “typically produces the highest and steadiest rates of responding” (Driscoll, 1994, p. 48). Finally, many authors have contended that an effective learning environment is one that allows learners to explore and learn independently (Collins & Brown, 1988; Shute, Glaser, & Raghavan, 1989; White & Horowitz, 1987). Simulation seems to fall into this category in particular because of its inherent ability to allow learners to evaluate and manipulate an object system. SITUATED LEARNING Research into situated learning, a philosophy that combines cognitive theories with situated activity, shows that people might view knowledge as a “relation between an individual and a social or physical situation rather than as a property of an individual” (Greeno, 1989, p. 286). Some researchers contend that knowledge is “situation specific and context dependent” (Kintsch, 1988, p. 165). It has also been stated that “researchers have argued against the existence of general context-free cognitive skills and for learning in highly contextualized ways” (Driscoll, 1994, p. 163). These concepts also parallel the hermeneutical position: knowledge is not innate; it is not tied to a particular object to which we all have access; it lies in our interaction with these objects. Arguably, with regard to knowledge pertaining to the interpersonal, knowledge lies in the interaction between individuals. A more effective instructional technique might be to allow learners to gain dynamic knowledge through their own discovery process in a simulated environment rather than just by analyzing inert factual data. By allowing learning to take place through practice, learners can be placed in a simulation where they acquire dynamic knowledge through object and situational interaction. SUMMARY Experiential learning involves immersing learners in an environment in which they actively participate in acquiring knowledge. Computer simulation is an experiential learning 62 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 Bruner, J. (1960). The process of education. Boston: Harvard University Press. activity that allows learners to visualize situations and see the results of manipulating variables in a dynamic environment. This type of learning environment is advantageous over role-play in that the level of subjectivity in instruction and assessment can be greatly reduced. Further, simulation can provide a dynamic visual environment that cannot be duplicated in typical turn-based strategies of gaming. Butler, R. J., Markulis, P. M., & Strang, D. R. (1988). Where are we? An analysis of the methods and focus of the research on simulation gaming. Simulation & Games, 19 (1), 3-26. Cherryholmes, C. (1966). Some current research on effectiveness of educational simulations: Implications for alternative strategies. American Behavioral Scientist, 10, 4-7. The above advantages notwithstanding, computer simulation is not an educational panacea. When the desired learning outcomes include the development of interpersonal and/or team skills, computer simulation is probably not the best experiential learning tool for the job. The environmental dynamism one sacrifices in choosing management games over computer simulation may be compensated for, at least in some measure, by the interpersonal elements associated with team-based games. Thus, we are not arguing for the inherent superiority of computer simulation. Such a view is too narrow. Rather, following Gist (1997), we propose that pedagogical choices—in this case the choice one makes from among role-playing, games, and computer simulation—should be driven by the desired learning outcomes. Collins, A., & Brown, J. S. (1988). The computer as a tool for learning through reflection. In H. Mandl & A. Lesgold (Eds.), Learning issues for intelligent tutoring systems (pp. 1-18). New York: Springer. Corsun, D. L. (2000). We sail the same ship: Response to “Shuffling deck chairs”. Journal of Hospitality & Tourism Education, 12 (3), 10-11. Corsun, D. L., & Enz, C. A. (1995). Don 't wait until you get whacked on the knees: An appreciation for reflexive management. Hospitality and Tourism Educator (now the Journal of Hospitality and Tourism Education), 7 (3), 58-60. Curtis J. (2000). Firms wage war on traditional training. Marketing; London. Mar 16, 29-30. Although simulation models need to imitate situations in such a manner that a learner can gain insight into the interaction of variables within that system, these situations do not need to be exact replicates. In fact, lower-fidelity simulation models can actually assist novice managers by focusing their attention on important variables. Driscoll, M. P. (1994). Psychology of learning for instruction. Boston: Allyn and Bacon. Feinstein, A. (2001). An assessment of the effectiveness of simulation as an instructional system. Journal of Hospitality and Tourism Research, 25 (4), 421-443. Field, A., McKnew, M., & Kiessler, P. (1997). A simulation comparison of buffet restaurants: Applying Monte Carlo modeling. Cornell Hotel and Restaurant Administration Quarterly, 38 (6), 68-79. Using experiential methods in education and training has many benefits beyond traditional forms of instruction. Student motivation has been shown to be a great asset when using simulation, which increases students' interest and participation in learning activities. Recent research in cognitive science and situated learning further supports the benefits of immersing learners in interactive environments that replicate situations that they might encounter on the job. Gist, M. E. (1997). Training design and pedagogy: Implications for skill acquisition, maintenance, and generalization. In M. A. Quiñones & A. Ehrenstein (Eds.), Training for a rapidly changing workplace: Applications of psychological research, (pp. 201-222). Washington, D. C.: American Psychological Association. This article contributes to the understanding and appropriate use of experiential learning activities in two important ways. First, by clearly defining and differentiating among computer simulation, role-play, and games, we have facilitated communication among users of these experiential learning activities through a common language. Second, we delineated the benefits and drawbacks of each type of activity, thereby enabling users of these activities to make pedagogical choices consistent with desired learning outcomes. These contributions should serve to enhance the benefit academics and practitioners derive from using computer simulation, role-play, and games in management classrooms and organizations. Greenlaw, P. S., & Wyman, F. P. (1973). The teaching effectiveness of games in collegiate business courses. Simulation & Games, 4, 259-294. Greeno, J. G. (1989). Situations, mental models, and generative knowledge. In D. Klahr & K. Kotovsky (Eds.), Complex information processing: The impact of Herbert A. Simon (pp. 285-318). Hillsdale, NJ: Erlbaum. Hannafin, M. J., & Peck, K. L. (1988). The design, development, and evaluation of instructional software. New York: Macmillian Publishing Company. REFERENCES Hays, R. T., & Singer, M. J. (1989). Simulation fidelity in training system design: Bridging the gap between reality and training. New York: Springer-Verlag. Atkinson, S., Kelliher, C., & LeBruto, S. (1997). Capital- budgeting decisions using 'crystal-ball'. Cornell Hotel and Restaurant Administration Quarterly, 38 (5), 20- 27. Horn, R. E., & Cleaves, A. (1980). The guide to simulation/games for education and training. Beverly Hills, CA: Sage. 63 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 Render, B., & Stair, R. M. (1997). Quantitative analysis for management. (6th Ed.). Upper Saddle River, NJ: Prentice-Hall, Inc. Hsu, E. (1989). Role-event gaming simulation in management education: A conceptual framework and review. Simulation & Gaming, 20 (4), 409-438. Hyman, R. T. (1978). Simulation gaming for values education: The prisoner’s dilemma. New Brunswick, NJ: University Press of America. Reich, A. Z., & DeFranco, A. L. (1994). How to teach so students will learn: Part one. Hospitality & Tourism Educator, 6 (1), 47-51. Schank, R. C. (1990). Tell me a story. Evanston, IL: Northwestern University Press. Jex, H. R. 1987. The critical-instability tracking task: Its background, development and application. In W.B. Rouse (Ed.), Advances in man-machine systems research (Vol. 5, Mar., Paper No. 344). Hawthorne, CA.: Prepared for Advances in Man-Machine Systems Research. Shute, J. J., Glaser, R., & Raghavan, K. (1989). Inference and discovery in an exploratory laboratory. In R.E. Snow & D. Wiley (Eds.), Improving inquiry in social science: A volume in honor of Lee J. Cronbach (pp. 333-366). Hillsdale, NJ: Erlbaum. Jones, K. (1995). Simulations: A handbook for teachers and trainers. (3rd Ed.). East Brunswick, NJ: Nichols Publishing Company. Sheel, A. (1995). Monte Carlo simulation and scenario analysis: Decision-making tools for hoteliers. Cornell Hotel and Restaurant Administration Quarterly, 36, 18- 26. Kinkade, R., & Wheaton, G. (1972). Training devices design. In H. Vancoff & R. Kinkade (Eds.), Human engineering guide to equipment design. Washington, D.C.: American Institutes for Research. Specht, L. B., & Sandlin, P. K. (1991). The differential effects of experiential learning activities and traditional lecture classes in accounting. Simulation & Gaming, 22 (2), 196-210. Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review, 95, 163-182. Taylor, J., & Walford, R. (1978). Learning and the simulation game. Beverly Hills, CA: Sage Publications, Inc. Kolb D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice-Hall, Inc. Thorsteinson, T. J., & Balzer, W. K. (1999). Effects of coworker information on perceptions and ratings of performance. Journal of Organizational Behavior, 20 (7) 1157-1173. Kolb, D. A., Rubin, I. M., & McIntyre, J. M. (1974). Organizational psychology: An experiential approach (2nd Ed.). Englewood Cliffs, NJ: Prentice-Hall, Inc. Law, A. M., & Kelton, W. D. (2000). Simulation modeling and analysis (3rd Ed.). New York: McGraw-Hill. Towne, D. M., Jong, T., & Spada, H. (Eds.). (1993). Simulation-based experiential learning. Berlin; New York: Springer-Verlag. Loftus, G. R., & Loftus, R. E. (1983). Mind at play: The psychology of video games. New York: Basic Books. Wagman, M. (1993). Cognitive psychology and artificial intelligence: Theory and research in cognitive science. Westport, CT: Praeger Publishers. Malone, T. W. (1980). What makes things fun to learn? A study of intrinsically motivating computer games. Palo Alto, CA: Xerox, Cognitive and Instructional Sciences Series. Wagman, M. (1995). The sciences of cognition: Theory and research in psychology and artificial intelligence. Westport, CT: Praeger Publishers. McHaney, R., & White D. (1998). Discrete event simulation software selection: An empirical framework. Simulation & Gaming, 29 (2), 193-215. White, B.Y., & Horowitz, P. (1987). Thinker tools: Enabling children to understand physical laws (Report No. 6470). Cambridge, MA: Bolt, Beranek & Newman. McTear, M. F. (1988). Understanding cognitive science. West Sussex, England: Ellis Horwood, Ltd. Wilson, A. (1968). The bomb and the computer: Wargaming from ancient Chinese mapboard to atomic computer. New York: Delacorte. Miles, W. G., Biggs, W. D., & Schubert, J. N. (1986). Student perceptions of skill acquisition through cases and a general management simulation: A comparison. Simulation & Games, 17 (1), 7-24. Wolfe, J. (1985). The teaching effectiveness of games in collegiate business courses: A 1973-1983 update. Simulation & Games, 16 (3), 251-288. Morris, R., & Thomas, J. (1976). Simulation in training-part 5. Industrial Training International, 11 (3), 66-69. Wolfe, J. (1993). A history of business teaching games in English-speaking and post-socialist countries: The origination and diffusion of a management education and development technology. Simulation & Gaming, 24 (4), 446-463. Pegden, C. D., Shannon, R. E., & Sadowski, R. P. (1995). Introduction to simulation using SIMAN. (2nd Ed.). Hightstown, NJ: McGraw-Hill, Inc. Pierfy, D. A. (1977). Comparative simulation game research: Stumbling blocks and steppingstones. Simulation & Games, 8 (2), 255-268. Yukl, G., Kim, H., and Chavez, C. (1999). Task importance, feasibility, and agent influence behavior as determinants of target commitment. Journal of Applied Psychology, 81 (1) 137-143. Race, P., & Brook D. (1980). Perspectives on academic gaming & simulation 5: Simulation and gaming for the 1980’s. London: Kogan Page Limited. 64 Developments in Business Simulation and Experiential Learning, Volume 29, 2002 65 Zuckerman, D. W., & Horn, R. E. (1973). The guide to simulation games for education and training. Lexington, MA: Information-Resources, Inc. Table of Contents Volume 29, 2001 Threshold Marketer A Family Of Marketing Simulations: Basic Marketer And Advanced Marketer Team Mode And Solo Mode Globalization As An Extended Experiential Exercise The Benefits And Planning Considerations Of Short Term Study Abroad Programs How 2 Setup Your Office Computer To Run Linux For Teaching E-Commerce Without Messing Everything Else Up Incorporating Cosmopolitan-Related Focus-Group Research Into Global Advertising Simulations Demonstration Of Advanced Features In Computer-Assisted Gaming Of International Business A Comparison Of Discrimination-Based Versus Conventional Simulation Game Scoring A Universal Mathematical Law Criterion For Algorithmic Validity The Impact Of Public Policy On Innovation: A Simulation Project For Research And Teaching Participant Identification Of Competitors In A Marketing Simulation Competition Simulation Research In The Hospitality Industry "Computer Simulation, Games And Roleplay: Drawing Lines Of Demarcation" Simulation Distribution Alternatives: Author/User Considerations Managing The Curiosity Gap Does Matter: What Do We Need To Do About It? Use Of External Interventions In A Computer Based Simulation Putting Service Learning Into Orbit It's A Wonderful Life: Simulating The Golden Years Adventures In Creating An Outdoor Leadership Challenge Course For An Emba Program Vbotz: A Pedagogical Cross-Disciplinary, Multi-Academic Level Manufacturing Corporate Simulation Use Of Computer Modeling In Management Accounting Is Simulation Performance Related To Application? An Exploratory Study Learning Cooperatively May Not Be Learning Collaborately! Perception Is Reality: Sharing Frames International Management Virtual Teamwork: A Simulation Financial Plan For Your Life And Career Goals Using Project-Based Experiential Learning Groups In The Principles Of Marketing Course Futures Course: Learning How To Anticipate The Future Of Business Interactive Online Strategic Market Planning With The Web-Based Boston Consulting Group (BCG) Matrix Graphics Package Strategy Learning In A Total Enterprise Simulation Investigation Of The Impact Of Decision Parameters For A Dutch Auction Simulation For Ipo Issues Integrating In-Class Learning With Out-Of-Classroom Experiences Through A Managerial Competency Development Framework War And Peace: Managing Students Learning Experience In A Competitive Simulation Game Virtually Experiential Classrooms Exercise: Conducting Role Plays Using Student Generated Cases Procedural Justice And Acceptance In Group Decision Making The E-Commerce Game: A Strategic Business Board Game Does Student Preparation Matter In A Simulation? A Comparison Of Pedagogical Styles The Game Of Business - A Weekend MBA Course Volume-Dependent Money Exchange Model For Gaming Simulations Implementing Service Learning For Accountants: The Not For Profit Project To Teach Vikings To Behave Among Mandarins: Lessons From Teaching With A Simulation Model Of Applied Business Ethics In International Management Maze Bright Teachers In The Classroom The Validity Investigation Of A Test Assessing Total Enterprise Simulation Learning What Makes Strategy Possible: An Illustration Using Paper And Scissors Learning Micro-OB Skills While Making Top Management Decisions In A Multinational Industrial Firm The Absel Research Heritage And The Bkl: Leveraging Their Value For Future Research New Product Development (Npd) Simulations: Some Challenging Questions And Tough Modeling Issues The Biofeedback Stress Test The Power Circle Exercise Total Enterprise Simulation Learning Compared To Traditional Learning In The Business Policy Course A Business Game Distance Education Application: Learning Outcomes And Experiences Is the Tobin's Q a good Indicator of a Company's Performance? A Critical Examination of the "Experiential" Premise Underlying BUsines Simulation Usage