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date: 16 January 2018

Computer Simulations in the Classroom

Summary and Keywords

Computer simulations can be defined in three categories: computational modeling simulations, human-computer simulations, and computer-mediated simulations. These categories of simulations are defined primarily by the role computers take and by the role humans take in the implementation of the simulation. The literature on the use of simulations in the international studies classroom considers under what circumstances and in what ways the use of simulations creates pedagogical benefits when compared with other teaching methods. But another issue to consider is under what circumstances and in what ways the use of computers can add (or subtract) pedagogical value when compared to other methods for implementing simulations. There are six alleged benefits of using simulation: encouraging cognitive and affective learning, enhancing student motivation, creating opportunities for longer-term learning, increasing personal efficiency, and promoting student-teacher relations. Moreover, in regard to the use of computer simulations, there are a set of good practices to consider. The first good practice emerges out of a realization of the unequal level of access to technology. The second good practice emerges from a clear understanding of the strengths and weaknesses of a computer-assisted simulation. The final and perhaps most fundamental good practice emerges from the idea that computers and technology more generally are not ends in themselves, but a means to help instructors reach a set of pedagogical goals.

Keywords: computer simulations, computer-mediated simulations, human-computer simulations, computational modeling simulations, pedagogical value, computer simulation in international studies

Introduction

Since the very early days of computing, computer games and simulations have been used in academic environments. And as computer technology developed along with the Cold War, these simulations were naturally used to help students learn about the development and dynamics of the international system. Despite this history, there is not a rich literature on the use of computer simulations to teach international studies. This essay will review the literature that does exist, but also draw lessons from related literatures. The essay will first present a simple typology of three categories of computer simulations. It will then give an overview of the six pedagogical benefits that it is claimed computer simulations can provide. In the following section, the literature on each category of computer simulations will be reviewed in order to assess the evidence regarding if and how simulations provide these pedagogical benefits. Finally, the evidence from the literature will be summarized in order to identify gaps in the literature.

Definitions

A review of the literature of simulations in general, and computer simulations in particular, makes clear that terms are not used consistently either in the literature or by instructors using simulations. Most relevant here is that different vocabularies which the computer and technology fields bring to the field of educational simulations have caused terminology to be used slightly differently in the case of computer simulations. Therefore, the definitions that follow vary from the definitions put forth in the Compendium essay entitled “Designing and Using Simulations and Role-Play Exercises.”

This essay will use as its starting point three categories of simulations: computational modeling simulations, human-computer simulations, and computer-mediated simulations. These categories of simulations are defined primarily by the role computers take and by the role humans take in the implementation of the simulation.

The term “computer simulation” originally referred to a simulation that computers would run using a model or models programmed by the researcher. Classic examples include simulations that model weather patterns or airflow over an airplane wing. These simulations take inputs provided by the researcher that represent the initial conditions, run them through the model, and provide outputs defining the conditions at a given time interval later. In this essay, these simulations will be referred to as “computational modeling simulations,” hereafter modeling simulations. With the widespread use of powerful computers, the use of modeling simulations expanded beyond research applications and became more widely used by instructors as educational tools in the classroom. With modern laptops, it is easy to run models that simulate virtually any system, including weather (www.ciconline.org/windward), bee populations (http://gears.tucson.ars.ag.gov/beepop), species extinction (www.bethedinosaur.com/floor_plan_components.html), and many, many others.

Modeling simulations involve no role playing by the students. In order to provide the educational benefits of role playing, a second type of computer simulation allows students to interact in a role with the computer model. This can be done by individual students, for instance in the role of a foreign minister, or by a group of students. In this type of computer simulation, instead of providing a series of inputs prior to the beginning of the simulation, students provide ongoing inputs through their interaction with the computer based on their assigned roles as well as on outputs the computer provides as the simulation unfolds. A simple example of this genre is the online version of Prisoner's Dilemma at www.gametheory.net. At the other end of the complexity spectrum is the classic computer game SimCity. In this simulation, players of the game, in the role of mayor, provide ongoing inputs. The computer, using a complex urban planning model, provides a series of outputs that appear on the screen as developments in the simulated city.

More straightforward examples of this type of simulation have become popular as supplementary materials for textbooks. The suite of simulations developed by Carolyn Shaw to support International Relations, by Joshua Goldstein and Jon Pevehouse are an example (see Goldstein and Pevehouse, 2008 and www.MyPoliSciKit.com). In this essay, this type of simulation will be referred to as “human-computer simulations.”

There is a third type of computer simulation in which students have roles, but interact with each other in a computer-mediated environment. This type of simulation is the same as the various kinds of role-play simulations that instructors use in the classroom, with the difference that the students are not face-to-face, but interacting through computers in some way. The simulations developed by the ICONS Project (www.icons.umd.edu), James Stover’s Conflict Resolution Simulation (www.scu.edu/crs/), and Project IDEELS (www.ideels.uni-bremen.de/about.html) are prominent examples of this type of simulation. In the ICONS simulations, students interact in what amounts to a text-based, online model United Nations. At a much higher level of complexity, online environments such as “Second Life” similarly allow for interaction between participants in which the computer simply provides a platform for the interaction. This type of simulation will be referred to in this essay as “computer-mediated simulations.”

As a final note on terminology, it is becoming more difficult to maintain the distinction between simulation and game. On the one hand, the term “serious game” has emerged, particularly in the military community, to refer to complex education simulations. On the other hand, many games played for entertainment are evolving toward a more open-ended, simulation-type play in which there is no clear way to win or lose. The bestselling “The Sims” and “Spore” are the most prominent examples of this type of open-ended computer game. These developments have further undermined the often strained attempts within the literature to distinguish games from simulations.

Computers and Simulations: Good Practices

Much of the discussion below regarding the added value of computer simulations in the classroom will assume that the simulations have been implemented with some basic good practices in mind. While there has been no systematic articulation of these good practices, in talking with simulation developers and implementers, a relatively common set of practices emerges to which successful instructors adhere. It should be emphasized here that these are good practices in regard to the use of computers in implementing simulations. There is a distinct, and much broader, set of good practices regarding the implementation of simulations more generally.

In regard to the use of computer simulations, the first good practice emerges out of a realization of the unequal level of access to technology. It is good practice to ensure that every participant in the simulation has relatively equal access to, and a relatively similar comfort level with, the technology necessary to conduct the simulation. Instructors should do everything they can to not handicap certain participants in a simulation by placing technological demands upon them that they cannot meet. This good practice is very much taken for granted among instructors, to the point where it is rarely discussed (for an exception, see Linser 2004). However, it is worth noting that guaranteeing equal access and comfort level with a technology is more complicated than simply ensuring that all students have internet access, for instance. Rehberger (2006) partially captures this idea with her concept of “readiness,” but more research needs to be done regarding how students from different backgrounds interact with technology when participating in simulations.

The second good practice emerges from a clear understanding of the strengths and weaknesses of a computer-assisted simulation (see Lay and Smarick 2006). As is often noted in discussions of simulations, the simulation itself is normally part of a three-part process that begins with preparation for the simulation and ends with debriefing and reflection. It is good practice to build into this process activities that counter the weaknesses of the computer-assisted simulation environment. For instance, the relatively slow pace of internet-mediated communication can be countered by allowing more time for the simulation, adding a face-to-face element of the simulation, or by fast-forwarding time between rounds of a simulation (see Asakawa and Gilbert 2003). Similarly, the lack of face-to-face interaction in a computer-mediated environment can be countered by having students play roles in groups, thereby creating an environment where they have to interact, negotiate, make decisions, and so on, in a face-to-face environment (see Kaufman 1998; DeGarmo 2006).

The final and perhaps most fundamental good practice emerges from the idea that computers and technology more generally are not ends in themselves, but a means to help instructors reach a set of pedagogical goals (Kaufman 1998; Lay and Smarick 2006; Rehberger 2006). These goals can relate to issues that do not relate to the subject material of the simulation narrowly defined. There may be goals, for instance, related to the engagement of students through an exciting technology or related to improving the management of the simulation processes (see Portney et al. 2006). Nonetheless, it should be clear how a given technology is supporting an identified learning objective.

Given this focus on learning objectives, as well as the other good practices enumerated above, it is generally good practice to use the simplest level of technology that will allow an instructor's specific objectives to be met (Portney and Cohen 2006:20). A simulation of a treaty negotiation, for instance, would likely meet its objectives in a text-based simulation environment. A sophisticated, graphic interface such as a “Second Life” type would add a great deal of complexity, but would add little pedagogical value to the simulation.

Simulations and Computers: Added Value?

The literature on the use of simulations in the international studies classroom focuses on a central question: Under what circumstances and in what ways does the use of simulations create pedagogical benefits when compared with other teaching methods? This essay is forced to ask a second-order question, namely: Under what circumstances and in what ways does the use of computers add (or subtract) pedagogical value when compared to other methods for implementing simulations?

To answer this question it will be useful to review the alleged benefits of simulations identified in the “Designing and Using Simulations and Role-Play Exercises” essay in the Compendium. This essay is built around six alleged benefits of using simulation originally identified by Cathy Greenblat. These benefits are described as follows:

  1. 1 Cognitive learning : “participants gain factual information, concrete examples of abstract concepts, analytical skills, procedural experience and decisionmaking skills.”

  2. 2 Affective learning : “Such learning could include changed perspectives and orientations.”

  3. 3 Student motivation: “simulations can enhance student motivation and interest in the issue area.”

  4. 4 Longer-term learning : “simulations create ‘memorable events’ and create more enduring and easily recalled memories.”

  5. 5 Personal efficacy: “participants […] may gain increased self-awareness and personal efficacy.”

  6. 6 Student–teacher relations: “simulations may promote better student-teacher relations, where students learn in a more relaxed environment.”

Again, the question that will be put to the literature is how the use of computers in the implementation of simulations promotes or detracts from these pedagogical benefits. Each of the following three sections will focus on one type of simulation. Each section will review what the literature has said regarding that type of simulation vis-à-vis the benefits identified in “Designing and Using Simulations and Role-Play Exercises.”

Three Types of Simulations

In the review of the literature, there were certain consistencies that held across all three types of simulations. The first was that, although there are exceptions, anecdotal reporting on the implementation of simulations was much more common than systematic research on the learning benefits of different kinds of simulations. In the review below, this anecdotal evidence is included because it makes up the bulk of the literature. This issue will be returned to below when gaps in the literature are discussed.

Second, throughout the literature on all three kinds of simulations, there is almost no mention of the longer-term learning benefit. This is perhaps unsurprising as instructors have little practical way of measuring the long-term impact of their teaching strategies. There is also little mention of student–teacher relations. When this learning benefit is mentioned, it is normally discussed as the result of student motivation. Therefore, the analysis below will focus on the four remaining pedagogical benefits: cognitive learning, affective learning, student motivation, and personal efficacy.

Computational Modeling Simulations

At this point in time, the case of modeling simulations and their potential to provide benefits within the international studies classroom is difficult to assess. Although some have recognized the potential of using modeling simulations to teach topics within international studies (Wilkenfeld 2008), there has been very little use of modeling simulations within the international studies classroom to date.

One exception is the International Futures simulation developed by Barry Hughes at the University of Denver (www.ifs.du.edu). International Futures is a database-driven computer simulation of various global issues, including energy, the environment, food production and so on. Although this simulation has been used in the classroom, no secondary literature evaluating the use of the simulation in the classroom could be found.

The reasons for the relative lack of use of computational modeling simulations are complex. First, historical origins of the international studies field can be found in the disciplines of law, history, and diplomacy. These fields have traditionally been slow to adopt new technology. Second, students who gravitate to the field of international studies are often not the most technologically oriented students. Unlike in a life sciences course, for instance, professors can make no assumptions in international studies classes about a minimum comfort level with technology. Finally, there is a division within the international studies field (as well as other fields) between professors who are primarily focused on teaching and those who are primarily focused on research. As a result, some of the more cutting-edge modeling that has been done by research-oriented professors (examples include Bruce Buena de Mesquita, Lars-Erik Cederman, and the work being done at the Center for Social Complexity, George Mason University) has not been adapted to be used as a pedagogical tool. Given this dearth of use, there is naturally a lack of literature that discusses modeling simulation in regard to international studies.

The use of modeling simulations is more common in the economics classroom, and some lessons can be learned from assessing the pedagogical literature from that field. Within the economics field, the goal of using modeling simulation appears largely focused on the benefits of cognitive learning and student motivation. Several authors claim an increase in students’ ability to grasp basic economic dynamics (Millerd and Robertson 1987; Santos 2002; Lengwiler 2004). The focus on cognitive learning is unsurprising. Modeling simulations are an inherently cognitive exercise in which the computer becomes an extension of the analytic capacities of the student.

One possible drawback, identified by Portney and Cohen (2006), occurs when the modeling tool is very complicated to use. They argue that, when the simulation tool is difficult to use, students can use too much cognitive energy on figuring out how to use the simulation, thereby drawing away from the energy they have to interact with the content of the simulation. Although Portney and Cohen are not specifically discussing modeling simulations here, their point seems especially relevant to this type of simulation, which can be quite complex.

Economics as a field is less concerned with affective learning than international studies, which is reflected in the lack of discussion in the literature. It is possible that, if modeling simulations are developed for the international studies classroom, these simulations might have affective learning benefits. However, because there is no role play involved in modeling simulations, this will always be more difficult than with other types of simulations.

Several authors have claimed an increase in student motivation as a result of the use of simulation (Millerd and Robertson 1987; Motahar 1994). However, this benefit appeared to vary more depending on the nature of the simulation. Key issues cited include: an interesting interface, particularly a switch from text- and spreadsheet-based simulations to simulations with a graphical interface; ease of use; ability for simulations to produce complex, unpredictable results; and transparency, that is, the ability for students to see how the model is producing its outcomes.

There were no references in the economic literature reviewed to personal efficacy as a potential pedagogical benefit. It is not possible to draw implications from this. It is possible that the simulations produced increased personal efficacy, but that the authors simply were not focused on assessing this type of benefit.

Finally, it is important to note, as mentioned above, that the benefits claimed from using modeling simulations are based either on the author's observations or on surveys of students. A useful review of the use of modeling simulations in the economics classroom concludes that “there have been very few controlled studies of the effectiveness of simulations” (Porter et al. 2004:426). It is reasonably safe to assume that, if these studies have not been conducted within the economics field, they have not been conducted elsewhere in the social sciences.

Human-Computer Simulations

As noted above, the key difference between modeling simulations and human-computer simulations is that, in the latter, students play a role when interacting with the computer. This inclusion of role play in the process has some significant, and perhaps surprising, implications. Most importantly, in this type of simulation, the focus switches from the outputs the computer provides to the experience of the participants. In practice, this allows simpler, more evocative computer models to be used. There is less focus on the validity of the computer model to produce “accurate” results as defined by research standards. Instead, the question asked of the model is: Does the simulation provide an accurate representation of what it feels like to be in the given role? This allows instructors to use a broader range of simulations and to seek a broader range of pedagogical benefits.

The expanded use and utility of this type of simulation is reflected in the fact that there is more in the international studies literature, and closely related literatures, on this type of simulation than there is on modeling simulations. Nonetheless, the literature remains limited. First, many human-computer simulations are very simple mini-games that students play for a few minutes. “Darfur is Dying” (www.darfurisdying.com), which is one of the most widely distributed, provides a good example. In this game, you play the role of a child or young adult trying to fetch water while being hunted by militia members who are trying to kill you. While these simulations may set the tone for a course, introduce certain topics, or provide a fun change of pace, they are often not considered serious course materials. Looking forward, as these small simulation exercises become more closely integrated with other course materials – the simulations mentioned above that were developed by Carolyn Shaw are one example – there will likely be more of an impetus to evaluate them systematically.

At the other end of the spectrum are very sophisticated games that are expensive to develop and require a large amount of class time for the students to learn and play. Because of the financial cost, the cost in class time, and perhaps because of preconceptions that sophisticated human-computer simulations are mere “video games,” not many of these simulations are being used. This, of course, reduces the secondary literature as well.

Regarding the literature that does exist, there is some consensus that simulations can deliver important pedagogical benefits vis-à-vis cognitive learning. Cohen (2006) focuses on the ability of simulations to teach about the complex nature of social interactions, particularly decisionmaking. Similarly, Asal (2006) emphasizes the ability of simulations to force students to confront ambiguity and complexity. Finally, Cavalier (2006) reports that students who participated in a human-computer simulation showed increased ability to use conflict-resolution skills.

Interestingly though, there may be limits to what can be accomplished in this regard with human-computer simulations. Dempsey et al. (2002:166), citing a study of the use of 40 computer games, conclude that in order to create engagement by students “Gaming for educational purposes should not be overly complex. […] Providing examples of winning prototypes, of how to play a game can facilitate engagement in a game.” Of course, providing a winning prototype would seem to undermine the goals of forcing students to make decisions and problem solve under conditions of complexity and ambiguity. Portney et al. (2006:106) compared computer simulations with paper-based simulations and conclude that “the data reveal striking similarities between paper and multimedia simulations.” In the end, their study makes a stronger argument for computer simulations on the basis of pragmatic concerns than on the basis of pedagogical benefits. These included the ability to easily vary elements of the simulation and the ability to quickly tabulate results for a large number of students.

Traditionally, interaction with a computer has not been seen as a useful tool to instill affective learning. There are some references, in the literature, however, to this aspect of learning. Cavalier (2006) reports that students who participated in a human-computer simulation outperformed controls in their ability to appreciate the perspective of the other party, even three to four years removed from the simulation.

Crookall et al. (1986) note that one advantage of using a computer for simulations is that the computer can take care of much of the analytic work – the “number-crunching” – involved in a simulation. This allows students to focus on the human interaction involved in the simulation. This benefit comes into play if students are interacting with the computer as a group, which is often the case in human-computer simulations.

Holsbring-Engels (1997) cites other advantages that the computer offers as a tool for building interpersonal skills, one element of affective learning. In particular, she discusses the ability of students to start alone with the computer to build confidence and the ability of the computer to slow interactions down in a way that allows for more reflective learning.

Regarding student motivation, references to the need to motivate a new generation of digital/wired/networked students are common in the literature about human-computer simulations. Perhaps surprisingly then, there is little analysis in the literature regarding whether or not students are actually motivated by these simulations. The pedagogical benefit of student efficacy was not mentioned in the literature reviewed for this essay.

Computer-Mediated Simulations

The use of face-to-face role-play simulations has a long history in the international studies classroom. Model League of Nations simulations, for instance, were taking place as early as the 1920s. The field's traditional foci – international organizations, summits, treaty negotiations, peace talks, and so on – lend themselves well to this type of simulation. It is unsurprising, therefore, that the most popular type of computer simulation in the international studies field takes this model of face-to-face simulation and recreates it within a computer-mediated environment. As a result, there is a more significant literature assessing this type of simulation.

In regard to cognitive learning, one obvious benefit pointed out in the literature is that once participants are in an online environment they have access to an enormous amount of information and multimedia content (Garson 1994; Kaufman 1998; Starkey and Blake 2001; Martin 2003). The multimedia content from the internet can be integrated into the simulation by the simulation facilitators or the participants themselves (Martin 2003). In addition to the generalized benefits, this also allows different types of interactive content – text, audio, video, graphics, and so on – to be rapidly delivered to students with different learning styles, e.g., visual learners, audio learners, and so on (Portney and Cohen 2006). Instructors can use various types of content either to create a comfort level for a student or to challenge them to work on skills that are outside their comfort zone. Croson (1999) noted that, in some cases, the simple fact that the simulation is taking place electronically allows students who are not as “fast on their feet” or as extroverted to process information more successfully.

On more substantive cognitive learning issues, there is a consensus within the field that computer-mediated simulations are best suited to help students wrestle with complex, ambiguous social and political processes. This idea is summarized nicely by a student's comment on an evaluation form, that a simulation created “three-dimensional learning” (Asal 2005:362). This refers to the immersive nature of simulations, the best of which place you inside the problem. This can be compared to two-dimensional learning where you are outside the problem, looking at it by looking at the words on a page or perhaps video on a screen. Roni Linser (2004:4) makes a similar point when she argues that the learning in simulations “moves away from linear organization of issues toward centrifugal organization.”

Several authors (Wilkenfeld 1984; Starkey and Blake 2001; Asal 2006; Cohen 2006; Lay and Smarick 2006) emphasize the ability of simulations to force students to confront ambiguity and complexity. Unfortunately, although these authors are discussing computer-mediated simulations, there is little discussion of how the computer-mediated aspect in particular contributes to this result.

Lay and Smarick (2006) represent one of the few studies in the literature that attempted to measure the impact of simulations using a quasi-experimental, control case methodology. They conducted a pre-class and post-class survey of 329 students, 149 of whom had taken a course with no simulation (control group) and 180 of whom had taken a course with a simulation (test group). The items in the survey focused on both political knowledge – e.g., “Who has the final responsibility to decide if a law is constitutional?” – and political attitudes – e.g., “Agree or disagree: Most public officials are dishonest.” They found that, with a few exceptions, students in the test group, that is, the students who participated in the simulation, did have a more accurate understanding of the legislative process than those in the control group. The question of political beliefs will be addressed below.

As mentioned above, one possible drawback to this type of simulation is the danger of students spending too much cognitive energy learning how to use the tool, and therefore spending less cognitive energy on content (Portney and Cohen 2006). This is a particular danger in regard to this type of simulation because it is the only type of simulation reviewed here that can often be conducted face-to-face or with more familiar technologies such as IM or email. Students become frustrated more easily with a system that they do not see as essential.

In regard to affective learning Cohen (2006:50) notes that “social science is taught from the outside looking in. Walking a mile in the shoes of a decision-maker is not a standard part of the social science curriculum.” He claims that computer-mediated simulations can change this for the better.

First, while it is now often taken for granted, especially by students, it is worth remembering that a central benefit of communicating through computers is the ability to instantly connect with anyone around the world without any marginal cost (Martin 2003). This naturally leads to the possibility for a more diverse set of participants in any given simulation. As Martin (2003) notes, “Where international or intercultural comparison is part of the learning objective or the content, the ability to work across national boundaries is a strategic advantage” (see also Crookall and Landis 1992; Saunders and Powell 1998; Starkey and Blake 2001). It should be added that participating across distance and culture is possible within national boundaries as well. Clearly, this does not guarantee increased understanding on the part of the participants, but it at least provides a platform that creates this opportunity.

A key driver of affective learning is how engaging the simulation is for the students. The term often used for successful simulations is “immersive.” In immersive simulations, students forget that they are in a simulation and simply play their role (Cavalier 2006). Kaufman (1998) argues that the anonymity of the computer screen allows students to imagine that they are negotiating with their counterparts in other countries. It is sometimes very difficult for students to suspend disbelief enough to role play with their friends and classmates in a face-to-face environment. The counterintuitive result, according to Kaufman, is that the artificiality of the computer environment creates a more realistic, engaging interaction than if students were face-to-face. A second benefit, mentioned above but relevant here as well, is that computers can do the “number-crunching” and other information processing in a simulation, thereby allowing the participants to focus more energy on the social interactions (Crookall et al. 1986).

Lay and Smarick (2006) addressed one aspect of affective learning by looking at how the simulation affected student beliefs about politics, as opposed to their knowledge of politics. On this question, they found little difference between the control group and the test group. They attributed this in part to the fact that the assessment was given directly after the course, while changing political beliefs is a long-term process. This illustrates one of the central weaknesses in the literature on simulations. Even the most rigorous research conducted on simulations normally evaluates the impact of a single simulation or, at best, the impact of multiple simulations in a single class. There is no assessment done at the curriculum level. Therefore, it becomes impossible to assess the impact of simulations on longer-term processes such as attitudinal change.

In regard to student motivation, Rehberger (2006) notes that computer-mediated simulations provide the four relevant factors of motivation as laid out by Malone and Lepper (1987). These are challenge, curiosity, control, and fantasy (see also Mosely 2001). There is little further discussion of these elements by Rehberger, however, and no evidence given to support this assertion.

DeGarmo (2006) reported success using a computer-mediated simulation to engage “resistant populations” of students with international studies subject matter. DeGarmo defines resistant populations as students that, as the result of various social, cultural, and economic factors, have little knowledge of or interest in international relations (2006:4–5). She identifies these students through class surveys.

DeGarmo does not reflect on the role the computer played in her simulation, so it is difficult to assess the impact of the computer-mediation in particular versus the impact of the simulation more generally. Nonetheless, DeGarmo's findings are important. In research methodology, one of the methods by which a single case study can produce more credible research results is for the study to be of a “hard case.” On the issue of participation, “resistant populations” are by definition a hard case.

Finally, many of the issues discussed above in regard to cognitive learning are relevant here. The ability to create student engagement with complex, ambiguous material – material that can often turn students off (Starkey and Blake 2001; Lay and Smarick 2006) – is important to keep students motivated, as is the ability to provide different types of materials to students (Portney and Cohen 2006). In particular, a computer-mediated simulation also allows the delivery of content in various forms – audio, visual, text-based – to match the learning styles of different students.

There is less in the literature on the issue of personal efficacy. DeGarmo (2006:5), however, does report that the simulation allowed students to “overcome feelings of inadequacy.” Her paper is useful in that it has student surveys which make it possible to trace the increasing level of confidence among her students as the simulation proceeds.

There are also references in the literature to the way in which simulations move the focus of the learning process away from the instructor to the students. Judith Torney-Purta (1998), for instance, notes that the intense interaction within the simulation “moves participants from referencing to adults to referencing the opinions of peer team members,” and that students begin to “search for their own judgment criteria to satisfy themselves and their peers” (see also Linser 2004). These observations do not demonstrate that an increase in efficacy took place, but they do identify a mechanism by which such a shift could take place.

In summary, there is evidence in the literature to indicate that computer-mediated simulations produce some pedagogical benefits. But it is worth including a final note of caution. Carr et al. (2004) report on the inclusion of online chats in their trade bargaining simulation. Their results are nuanced, but in many ways the online interactions that they report mirror face-to-face simulation interaction (see also Croson 1999). They report, for instance, that a small number of students tended to dominate the chat, and that power hierarchies emerged in the chat, particularly between female and male students. This alerts us to the fact that, unlike in the other forms of computer simulations, in computer-mediated simulations, people are still communicating with people. Perhaps the most we can say is that communication patterns are shaped by computer mediation, but they are not determined by them (Rehberger 2006). Moreover, there is nothing static about these processes. As students who grew up relentlessly texting each other move into computer-mediated simulations, we should not expect their patterns of communication to be shaped in the same way as those of earlier generations of students.

Gaps in the Literature

The following table summarizes the review of the literature presented above.

Table 1 Summary of literature review

Computational modeling simulationsa

Human-computer simulations

Computer-mediated simulations

Cognitive learning

Positive impact

Mixed evidence

Positive impact, particularly for complex or ambiguous materials

Affective learning

No apparent impact

Weak evidence for positive impact

Potential positive impact, but difficult to measure due to long-term nature of impact

Student motivation

Positive impact, but only under certain conditions related to design of simulation

???

Positive impact

Longer-term learning

???

???

???

Personal efficacy

???

???

Weak evidence for positive impact

Student–teacher relations

???

???

Weak evidence for improvement of student–teacher relations as a result of increased student motivation

(a) All information in the “Computational modeling simulations” column relates to literature from the studies focused on the economics classroom.

The literature review points to two kinds of gaps in the literature. The first can be seen by looking at the table and noticing where question marks or weak evidence appears. This indicates that more research needs to be done in order to strongly link computer simulations to those pedagogical benefits.

The second gap relates to the nature of the works in the literature as a whole. As was noted above, the majority of works reviewed were reports on the implementation of a simulation or provided anecdotal evidence for the success of a simulation based on the instructor's impressions or student surveys (see Ip and Linser 2001; Linser 2004). There is nothing wrong with this type of publication. The field needs to know about new types of simulations, strategies for implementation, student reactions to simulations, and so on. However, there does need to be more systematic research done on the impact of computer simulations if the field is to be able to make confident claims about their ability to produce pedagogical benefits.

Moreover, a review of the literature makes clear that the more rigorous the research project undertaken to assess the computer simulation is, the more nuanced, and in some cases muddled, the results of the research are (Carr et al. 2004; Lay and Smarick 2006; Portney et al. 2006). This points to a deeper weakness in the literature. The best research being done in this area is still asking the broadest, most fundamental questions, normally some variant of “Did the simulation create more learning among students?” Clearly, this is the most important question, but it is unlikely that any single study will be able to answer it. As with any broad, fundamental question, the normal academic strategy is to begin to answer a series of smaller questions. As these questions are answered a better understanding of the larger questions begins to emerge. Torney-Purta (1998) is one example of an evaluation that seeks to investigate more granular issues, but is hindered by the lack of a control group and, for current purposes, the fact it is looking at computer-technology circa 1993. Thus, the gaps in the literature can best be filled not by more macro-level studies, but by more focused studies, studies that ask questions such as “How do simulations create increased motivation on the part of students?” or “How do computer simulations change communication patterns in simulations if at all?” As these smaller questions get answered, the field will begin to be able to state more confidently not only whether computer simulations provide predictable pedagogical benefits, but also how they do so.

References

Asakawa, T., and Gilbert, N. (2003) Synthesizing Experiences: Lessons to be Learned from Internet-Mediated Simulation Games. Simulation and Gaming 34, 10–20.Find this resource:

Asal, V. (2005) Playing Games with International Relations. International Studies Perspectives 6 (3), 359–73.Find this resource:

Asal, V. (2006) The ICONS Suite of Negotiation Simulation. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 161–204.Find this resource:

Carr, T., Cox, I., Eden, A., and Hanslo, M. (2004) From Peripheral to Full Participation in a Blended Trade Bargaining Simulation. British Journal of Educational Technology 35, 1–15.Find this resource:

Cavalier, R. (2006) The Poetics of Simulation: An Analysis of Programs in Ethics and Conflict Resolution. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 115–36.Find this resource:

Cohen, S. (2006) The Curricular Role for Understanding Social Decisions. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 47–66.Find this resource:

Crookall, D., and Landis, P. (1992) Global Network Simulation: An Environment for Global Awareness. In D. Crookall and K. Aria (eds.) Global Interdependence: Simulation and Gaming Perspectives. Tokyo: Springer, pp. 106–11.Find this resource:

Crookall, D., Martin, A., Saunders, D., and Coote, A. (1986) Human and Computer Involvement in Simulation. Simulation and Gaming 17, 345–75.Find this resource:

Croson, R.T.A. (1999) Look at Me When You Say That: An Electronic Negotiation Simulation. Simulation and Gaming 30, 23–7.Find this resource:

DeGarmo, D. (2006) ICONS and “Resistant Populations”: Assessing the Impact of the International Communication and Simulations Project on Student Learning at Southern Illinois University Edwardsville. Paper prepared for the APSA Conference on Teaching and Learning. Washington, DC.Find this resource:

Dempsey, J.V., Haynes, L.L., Lucassen, B.A., and Casey, M.S. (2002) Forty Simple Computer Games and What They Could Mean to Educators. Simulation and Gaming 33, 157–68.Find this resource:

Garson, D. (1994) Computerized Simulation in Social Science: A Personal Perspective. Simulation and Gaming 25, 477–87.Find this resource:

Goldstein, J., and Pevehouse, J. (2008) International Relations. New York: Longman.Find this resource:

Holsbring-Engels, G.A. (1997) Computer-Based Role Plays for Interpersonal Skills Training. Simulation and Gaming 28, 164–80.Find this resource:

Ip, A., and Linser, R. (2001) Evaluation of a Role-Play Simulation in Political Science. The Technology Source Archives. At www.technologysource.org/article/evaluation_of_a_roleplay_simulation, accessed Jul. 2009.

Kaufman, J. (1998) Using Simulation as a Tool to Teach About International Negotiation. International Negotiation 3, 59–75.Find this resource:

Lay, J.C., and Smarick, K.J. (2006) Simulating a Senate Office: The Impact of Student Knowledge and Attitudes. Journal of Political Science Education 2, 131–46.Find this resource:

Lengwiler, Y. (2004) A Monetary Policy Simulation Game. Journal of Economic Education 35, 175–83.Find this resource:

Linser, R. (2004) Suppose You Were Someone Else…: The Learning Environment of a Web-Based Role-Play Simulation. Paper prepared for the Society for Information Technology & Teacher Education International Conference. Atlanta, GA.Find this resource:

Malone, T.W., and Lepper, M.R. (1987) Making Learning Fun: A Taxonomy of Intrinsic Motivations for Learning. In R.E. Snow and M.J. Farr (eds.) Aptitude, Learning, and Instruction III. Hillsdale, NJ: Lawrence Erlbaum, pp. 223–53.Find this resource:

Martin, A. (2003) Adding Value to Simulation/Games through Internet Mediation: The Medium and the Message. Simulation and Gaming 34, 23–37.Find this resource:

Millerd, F.W., and Roberston, A.R. (1987) Computer Simulations as an Integral Part of Intermediate Macroeconomics. Journal of Economic Education 18, 269–86.Find this resource:

Mosely, W.G. (2001) Computer Assisted Comprehension of Distant Worlds: Understanding Hunger Dynamics in Africa. Journal of Geography 100, 32–45.Find this resource:

Motahar, E. (1994) Teaching Modeling and Simulation in Economics: A Pleasant Surprise. Journal of Economic Education 25, 374–8.Find this resource:

Porter, T.S., Riley, T.M., and Ruffer, R.L. (2004) A Review of the Use of Simulations in Teaching Economics. Social Science Computer Review 22, 426–43.Find this resource:

Portney, K., and Cohen, S. (2006) Practical Contexts and Theoretical Frameworks for Teaching Complexity with Digital Role-Play Simulations. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 3–28.Find this resource:

Portney, K., Cohen, S., Goldman, J., and Simpson, S. (2006) Teaching About Criminal Sentencing Decisions: The Crime and Punishment Simulations. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 89–114.Find this resource:

Rehberger, D. (2006) Teaching with Digital Role-Play Simulations. In S. Cohen, K. Portney, D. Rehberger, and C. Thorsen (eds.) Virtual Decisions: Digital Simulations for Teaching Reasoning in the Social Sciences and the Humanities. Mahwah, NJ: Lawrence Erlbaum, pp. 29–46.Find this resource:

Santos, J. (2002) Developing and Implementing an Internet-Based Financial System Simulation Game. Journal of Economic Education 33, 31–40.Find this resource:

Saunders, D., and Powell, T. (1998) Developing a European Media Simulation through New Information and Communication Technologies: The TENSAL Project. In J. Rolfe, D. Saunders, and T. Powell (eds.) The International Simulation and Gaming Research Yearbook. London: Kogan Page, pp. 75–86.Find this resource:

Starkey, B., and Blake, E. (2001) Simulation in International Relations Education. Simulation and Gaming 32, 537–51.Find this resource:

Torney-Purta, J. (1998) Evaluating Programs Designed to Teach International Content and Negotiation Skills. International Negotiation 3, 77–97.Find this resource:

Wilkenfeld, J. (1984) Computer-Assisted International Studies. Teaching Political Science 10, 171–6.Find this resource:

Wilkenfeld, J. (2008) Personal conversation.Find this resource:

American Political Science Association: Simulations for Teaching Political Science. At www.apsanet.org/content_15404.cfm, accessed Jul. 2009. An annotated list of simulations for teaching political science. Many, but not all, are computer simulations.

Ars Regendi: The Art of Politics. At www.ars-regendi.com, accessed Jul. 2009. An example of a sophisticated, open-ended, role-play game with over 15,000 registered players. In the simulation, you are in charge of a fictional state and must make political and economic decisions, while interacting with other states in the fictional world.

EdTec670. At http://edweb.sdsu.edu/Courses/EDTEC670, accessed Jul. 2009. The website of EDTEC 670, Exploratory Learning through Educational Simulations and Games, course at San Diego State University. Includes a useful blog, resources, links, and summaries of various projects.

ICONS Project. At www.icons.umd.edu, accessed Jul. 2009. ICONS is a provider of online role-play simulations focusing on issues of international negotiation. ICONS simulations can be used in high school, university, or adult-learning environments.

PaxSims. At http://paxsims.wordpress.com/, accessed Jul. 2009. A useful blog devoted to the development and implementation of peace and conflict simulations.

Project IDEELS. At www.ideels.uni-bremen.de, accessed Jul. 2009. A European provider of online role-play simulations. Their annual simulation models key European political issues in the fictional region of Eutropia. It provides an interesting example of a detailed, multinational simulation.

SimPlay. At www.simplay.net/research.html, accessed Jul. 2009. SimPlay is a provider of a broad range of online simulations, focusing on interpersonal, intercultural, and international issues. Their simulation platform, Fablusi, is widely used to host instructor-developed simulations.

VirtualPeace. At www.virtualpeace.org/, accessed Jul. 2009. Virtual Peace simulates disaster relief and conflict environments in order to teach students about complex crisis response. A useful example of a high-budget, graphically sophisticated educational simulation.