Educational games and simulations, unlike direct forms of instruction, are experiential exercises. That is, student teams may be racing each other to reach a pot of gold (game), sifting through an archeological site and analyzing the artifacts (simulation), or managing a financial institution for several months (simulation).
Games and simulations entered the broad educational scene in the late 1950s. Until the early 1970s, they were not part of the instructional design movement. Instead, these exercises were primarily developed by business and medical education faculty and sociologists who adapted instructional developments pioneered by the military services. Although popular in the public schools in the 1960s, games and simulations in United States classrooms declined with the advent of the basic-skills movement. Currently, the increased power and flexibility of computer technology is contributing to renewed interest in games and simulations. This development coincides with the current perspective of effective instruction in which meaningful learning depends on the construction of knowledge by the learner. Games and simulations, which can provide an environment for the learner’s construction of new knowledge, have the potential to become a major component of this focus.
The technology, however, faces two major problems at present. One is that comprehensive design paradigms derived from learning principles have not been available. Coupled with the variety of disciplines attempting to develop games and simulations, the result is a variety of truncated exercises often mislabeled as simulations. One study, for example, referred to a static computer graphic of a pegboard as a simulation. Another study that purported to be a simulation of decision making was a series of test questions about different situations in which the student was to assume that he or she was an administrator of special education. A third “simulation” simply provided preservice teachers practice in completing classroom inventory forms, supply requisition forms, and incident reports. These latter two examples are context-based problems, but they are not simulations.
These mislabeled exercises indicated the need for effective design models for games and simulations. Design models are the “soft technologies” that influence and activate the thought processes of the learners rather than the “hard technology” of the computer (Jonassen, 1988). Also, poorly developed exercises are not effective in achieving the objectives for which simulations are most appropriate—that of developing students’ problem-solving skills. Finally, poorly developed games and simulations often have negative effects on students, some of which are discussed later in the chapter.
The second major problem for developers and users of games and simulations is the lack of well-designed research studies. Much of the published literature consists of anecdotal reports and testimonials. These discussions typically provide a sketchy description of the game or simulation and report only perceived student reactions.
Further, as indicated by Pierfy (1977), most of the research is flawed by basic weaknesses in both design and measurement. Some studies implemented games or simulations that were brief treatments of 40 minutes or less and assessed effects weeks later on midterm or final examinations. Intervening instruction, however, contaminates the results.
Another major design weakness is that most studies compare simulations to regular classroom instruction (lecture and/ or classroom discussion). However, the instructional goals for which each can be most effective often differ. The lecture method is likely to be superior in transmitting items of information. In contrast, simulations have the potential to develop students’ mental models of complex situations as well as their problem-solving strategies. Not surprisingly, a meta-analysis of 27 research studies (for the period 1969— 1979) that met basic validity and reliability criteria found that simulations were not superior to lecture or discussion on information-oriented posttests (Dekkers & Donatti, 1981).
Among the measurement problems in reported studies is the failure to describe the nature of the posttests used to measure student learning. Some studies use essay questions, while others use some type of instructor-developed test with no reported validity or reliability information. In addition, some researchers provided the simulation group with additional problems to solve or information summaries that the other group did not receive.
Another problem is that comparison studies often are not sensitive to the student characteristics that interact with instruction to influence achievement. One study by Wentworth and Lewis (1973) identified three characteristics that mediated the instructional effects of a commercially developed simulation for junior college students in economics. Formulation of a stepwise regression model to identify the variables that predict achievement indicated that prior knowledge, ability, and the school attended were significant contributors to posttest achievement on a standardized economics test for students in the course-related simulation. In other words, like other forms of instruction, simulations and games are likely to be more effective with some students than with others.
Finally, the classroom research paradigm implemented in the 1960s and 1970s did not document the actual instructional processes associated with an innovation. Instead, the innovation was assumed to differ substantially from typical classroom instruction, and the innovation was compared with traditional practice. Subsequent analyses of the 1970s classroom research has indicated that, in many cases, instruction in the comparison classes shared key characteristics with the innovative classes (see House et al., 1978; Glass, 1979; Hall & Loucks, 1977). The result was a “no significant difference” finding in these comparisons. Like other classroom research, studies that addressed games and simulations did not document the ways that students interacted with the subject matter and each other during a game or simulation. For example, although simulations are described as enhancing decision making, key questions unasked by the research are: For which student and in what ways? What tradeoffs between increased decision making and information load? And so on. At present, a few studies are beginning to investigate the dynamics of student interactions with games and simulations, and this research and the implications for design are discussed in this chapter.
Given the issues facing the gaming and simulation field, the purpose of this chapter is threefold. The chapter first presents and discusses a definitive framework for games and simulations that addresses the essential features of each type of exercise. Then the chapter discusses the research studies that have implications for instructional design. The chapter concludes with a discussion of recommended guidelines for research on games and simulations.
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