AECT Handbook of Research

Table of Contents

17. Educational games and simulations: Technology in search of a research paradigm
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17.1 Introduction
17.2 A Definitive Framework
17.3 Academic Games
17.4 Experiential Simulations
17.5 Symbolic Simulations
17.6 Instructional Design Implications Derived from Research
17.7 Recommendations for Future Research
  References
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17.4 EXPERIENTIAL SIMULATIONS

Like the player in an academic game, the participant in a simulation also applies a knowledge base. However, the simulation participant is facing a complex situation in which he or she is one of the components. Further, the situation evolves and changes in part in response to the participant's decisions and actions.

Within the category of experiential simulations, exercises may differ in (1) the nature of the participants' roles, (2) the types of decisions and interactions in the exercise, and (3) the nature of the relationships among the variables. That is, experiential simulations may be individual or group exercises, the focus may vary from executing professional expertise to experiencing a different cultural reality, and the relationships among the variables may be quantitative or qualitative. Four major types of experiential simulations are data management, diagnostic, crisis management, and social-process simulations (Gredler, 1992a).

17.4. 1 Data Management Simulations

A participant in a data management simulation typically functions as a member of a team of financial managers or planners. Each team that is managing a company or institution allocates economic resources to any of several variables in order to achieve a particular goal. The long-range goal is to improve the status of the institution or company (Gredler, 1992a).

The simulation typically encompasses 12 to 18 business quarters (rounds) in which each team makes several short-and long-term investment and budgeting decisions. At the end of the business quarter (from 45 minutes to 2 to 3 hours), the decisions are analyzed by the computer, and each team receives an updated printout that indicates their institution's financial standing. The team analyzes the printout and makes the next set of decisions.

Although the team members interact in making decisions, the primary focus in data management simulations is on the interrelationships and trade-offs among quantifiable variables. In a bank management simulation, for example, participants are expected to address the relationships among profitability, liquidity, and solvency, and between profits and volume of business (Galitz, 1983).

Data management simulations are based on mathematical models that adjust parameter values as student inputs are made. The simulation designer specifies the set of equations that reflects the relationships among the variables. Depending on the complexity of the situation, the number of required equations may range from half a dozen to over 50.

17.4.2 Diagnostic Simulations

Originating in medical education, diagnostic simulations are currently found primarily in several health care fields, education, and psychology. Some diagnostic simulations are team exercises that require the discovery, evaluation, and interpretation of relevant data, as in an air accident investigation (Rolfe & Taylor, 1984). In the majority of examples, however, a student takes the role of a physician, nurse, psychologist, or teacher. The student selects and interprets data and selects corrective actions in the diagnosis and management of the patient's or client's problem.

The deep structure of diagnostic simulations consists of an evolving problem that requires sequential interrelated decisions. The sequential nature of the task links each decision to prior decisions and results. Therefore, as in real situations, errors may be compounded on top of errors as nonproductive diagnostic and solution procedures are pursued (Berven & Scofield, 1980).

Key components of diagnostic simulations are a sketchy description of a multifaceted problem, the prescribed role of the participant, and multiple plausible alternatives at each decision point (McGuire, Bashoot & Solomon, 1976). Also, the problems are those that involve the consideration of more than a simple cause. Thus, they are not textbook problems. In an air accident investigation, for example, contributing factors are both human and mechanical (Rolfe & Taylor, 1984).

Of major importance is that the student who is unsure of the appropriate course of action can find plausible choices. The only feedback received by the student during the exercise is either the data he or she requested or the effects of a selected action on the situation. Further, the complications that the student must address will vary depending on his or her unique pattern of decisions (McGuire et al., 1976). Thus, a major purpose of many diagnostic simulations is to obtain a record of the student's progress through the multiple possible paths so as to differentiate adequate problem solvers from the students using ineffective approaches.

Figure 17-1 illustrates the various paths through a simulation for the diagnosis and management of a patient. Each of the major strategy decisions, e.g., take history, obtain laboratory data, and so on, is represented by a box on the simulation map. Within the major strategy choices, students may select from a number of plausible specific decisions. The map indicates the decisions to be made and those to be avoided, according to a panel of experts. Solid arrows indicate the route recommended by a panel of experts. As indicated by the map, the student is not terminated from the simulation unless he or she takes action that causes the patient's death.

 

 

Early examples of diagnostic simulations for individual students were multiple-branching exercises in booklet form. They have since been replaced by computer-delivered exercises, some of which accept voice input (see Distlehorst & Barrows, 1982; Pickell et al., 1986).

17.4.3 Crisis Management Simulations

A crisis management simulation begins with an unexpected event that threatens the welfare of an individual or a group and which must be quickly resolved. Key components of crisis-management simulations are the rapidly increasing time pressure and the need to prevent a major disaster of some sort.

Both political-crisis exercises, in which a country's security or welfare is threatened, and combat simulations are examples. Political-crisis exercises involve a small team of decision makers representing each country and interacting in a compressed time frame. Combat simulations used for training are either individual or team exercises, and these simulations have been revolutionized by advanced computer technology. Large-scale field maneuvers used to educate commanders and their staffs and some weapons systems training are currently conducted with discrete and networked computer simulations (Oswalt, 1993). A current project is creating a simulated environment that will permit military personnel to view the battlefield in three dimensions, including the capability to reconnoiter the terrain (Oswalt, 1993, p. 154).

17.4.4 Social-Process Simulations

The focus of data management, diagnostic, and crisis management simulations is on a complex task or problem in which human interactions play minor roles, if at all. The student behaviors of primary interest are the decisions made to address a complex cognitive problem. In contrast, the deep structure of social-process simulations is the interactions among the participants and the ways that one's beliefs, assumptions, goals, and actions may be questioned, hindered, or supported in interactions with others (Gredler, 1992a). Goals of social-process simulations are (1) to develop an understanding of a particular social organization or culture, (2) to help develop abilities to think and communicate in an unfamiliar situation (Jones, 1982), or (3) to help develop empathy for others by experiencing an aversive situation as others would, followed by reviewing and discussing one's beliefs and assumptions (Thatcher, 1983; Thatcher & Robinson, 1990).

Participants typically take roles with different interests, priorities, and responsibilities in one of the groups faced with conflicting issues or tasks. Among the examples of social-process simulations are (1) an economically deprived region that must address a proposed tourism development that will also have some negative effects, and (2) the writing, editing, and broadcasting of a radio news program as items continue to come in until air time.

Key components of social-process simulations are (a) a precipitating event or key task, (b) well-defined participant roles, (c) complicating factors, and (d) context (Gredler, 1992a). All of these components interact with each other to set in motion the interactions among participants that are the core of the simulation. Of major importance is that each role (1) must have a stake in the outcome of the exercise and (2) be one to which the participant can commit his or her thoughts and feelings; that is, the role must generate "reality of function."

17.4.5 Discussion: Experiential Simulations

Experiential simulations vary widely in the type of experience established for the learner and the type of causal model underlying the exercise. Data management simulations are most often team exercises in which the relationships among the variables to be manipulated are specified by sets of mathematical equations-a quantitative causal model (see Table 17-2).

In contrast, diagnostic, crisis management, and social process simulations are based on qualitative causal models. That is, cause-effect contingencies are drawn from actual cases, and the optimal route through the simulation is verified by experts who are asked to work through the exercise. Social-process exercises, however, depend on the interactions of individuals as they react to different situations. Unless contingencies for different actions have been carefully embedded in the context and various roles, the exercise can take unexpected directions.

Of the four types, only the diagnostic simulation can be computer based. Decisions in the other types typically require team decision making, and computers cannot replicate social situations (Crookall, Coleman & Oxford, 1992).

However, computer analyses of data generated by team members often serves as input to participant decisions.

Experiential simulations share several key characteristics. First, the learner is a functional component of the situation and experiences it from the inside. Second, the learner takes on serious responsibilities as a participant in an ongoing fluid situation. Third, the intent is for the participant to experience the effects of his or her decisions; i.e., the student's discipline problem becomes worse, a proposed compromise is repealed, and so on. Finally, experiential simulations also can provide opportunities for students to develop their cognitive strategies because the exercises require that they organize and manage their own thinking and learning.


Updated August 3, 2001
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