The design and use of simulation computer games in education




НазваниеThe design and use of simulation computer games in education
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Part of this can be addressed by differentiating the field by the use of terms like DGBL, which implies only computer or console games, but this does not go far enough, as computer games refers only to the medium of expression, and not the game itself. Card games, Jeopardy-style games, action games, and adventure games can all be digital in form, yet each will have it's own characteristics that make it more or less suited to different instructional uses. It follows, then, that depending on what kinds of skills one wants to foster in DGBL practice, different forms and styles of games will be required. This kind of analysis is one of the things instructional design has established models, heuristics, and procedures for doing.

In 1965, Robert Gagné (one of the founders of ID) published Conditions of Learning, in which he proposed five types (varieties) of learning: motor skills, attitudes, cognitive strategies, verbal information, and intellectual skills. Intellectual skills are further refined into five other categories, presented here in order of complexity from most to least: problem-solving, rules, defined concepts, concrete concepts, and discriminations (presented in order of complexity from most to least). Each of these varieties of learning require different types of instructional events and strategies. While this may seem to be common sense today, prior to this book all instruction was approached the same way, using the same activities and strategies for all types of learning (many still do!). By looking at the varieties of games and the varieties of learning at the same time, we can begin to see that there is a potential to developed blended game and learning taxonomies (e.g., see Van Eck, 2006a).

Another of Gagné's contributions to instructional design is in his Nine Events of Instruction (Gagné, 1965). Gagné examined the psychology literature on models of learning and both studied the educational literature on instruction and observed the best practices of teachers in the classroom. From these activities, he derived a series of internal events necessary for information processing, and a series of external events in instructional delivery that, when aligned with those internal events, produced the most effective teaching.

It is important to recognize that these events are not a new model for designing or delivering instruction as much as they are an instantiation of what the best learning and instructional practices have been since humans began the practice of instruction (formal and informal). Many people mis-characterize instructional design as a strictly linear, prescriptive process, with these principles serving as templates rather than models and heuristics. In fact, ID codifies those things that ALL effective instruction does, whether designed by an instructional designer or not. The purpose of these principles and models is to allow us to think about them while designing and developing instruction, NOT to apply each concept or element one after the other with no thought to creativity, engagement, etc. These are core principles of effective instruction, not templates for creating instruction. To represent them as the latter is to mistake the forest for the trees.

Gaining attention need not be the result of asking for attention (although that IS one way to do it). Another might be to walk up to the front of the room and throw money into the garbage can (a friend of mine did this prior to a speech on coin collecting). Both serve to gain attention, but one is more dramatic and effective than the other, and ALSO serves to set the stage for the second event (informing of the objective, which in this case is learning about money in a new way). The teacher in the movie Dead Poets Society tore pages out of books and threw them around the room as a way of gaining attention. The point is, there are many subtle ways to employ each of these events, sometimes at the same time, and sometimes repeated in different order (imagine only gaining attention once during an instructional activity that encompasses reading some text just after returning from lunch, and you'll see why some of these events need to be revisited many times!).Games are a perfect illustration of this point; few would argue that games use a linear, lock-step approach to teaching what it is they teach. Table 4 illustrates both the nine events and examples of the actual way they are employed in effective instruction such as commercial video games.


Table 4. Oil & Water, or Peaches and Cream?

Nine Events

Examples of Nine Events from Games

Gain Attention

Motion, cut scenes, noise, music, character speech, health meters, attacks, death

Inform of Objective

Documentation for the game, introductory movies, cut scenes, character speech, obstacles that limit movement or interaction

Recall Prior Knowledge

Environmental cues (e.g., in Laura Croft: Tomb Raider, ledges that look like those trained on in the earlier tutorial), obstacles (search for solutions involves recalling solutions and events from earlier in the game)

Present Instruction

All of the above (characters, environment, objects, puzzles and obstacles, conversation) arranged according to goals of game

Provide Guidance

Cut scenes, non-player character (NPC) or player character (PC) speech, hint books, cheats and walkthroughs, friends, partial solutions to puzzles (pressing on the wall makes it rumble, but it does not open). Also, much comes from the learner themselves as they process what has occurred in the game, but the arrangement of the actors and objects in the environment and the structure of the story itself also provide implicit guidance

Provide Practice

Players cannot progress through the game without demonstrating what they know or think they know—all knowledge is demonstrated within the confines of the game narrative and structure.

Provide Feedback

Character speech, sounds, motion, etc., Player gets past the obstacle or achieves the goal, or does not. Every action has immediate feedback, even if that feedback is that nothing happens.

Assess Performance

Movement through the game IS assessment. Nothing is learned that is not also demonstrated.

Enhance Retention & Transfer

Things learned early in games are brought back in different, often more complex forms later. Players know that what they learn will be relevant in the short and long term.

Developing Tools for Design and Evaluation

The two examples from the field of ID described above have direct bearing on both the theory and practice in DGBL, and show how our models can lead to heuristic tools for both research and practice, for analysis and evaluation. Without these models, theories, and practical guidelines, we cannot hope to answer the big questions that will face us in the next 5 years. The point is not to arrive at a set of prescriptive tools that will allow us to "connect the dots" and build great DGBL. Rather, we need these tools so that we can help scaffold the practice of generating DGBL in terms of critical attributes and characteristics. For instance, an heuristic for game strategies and learning outcomes does preclude the development of creative games that incorporate the art and creativity that characterize commercial game development today, but it WOULD help avoid the use of strategies that support verbal information (e.g., stating a rule) rather than problem-solving (demonstrating rules to generate solutions to problems).

We need, for example, to develop operational definitions of theories and models within games. What are the critical features of engagement, cognitive disequilibrium, and models of problem solving in games? I have argued that engagement may be a function of cognitive disequilibrium in games; how do we validate and measure these constructs? Can we develop tools and methods to support or even automate this process during design of new games or analysis of existing games? Can we create tools that are aware of these features and distinctions in ways that will facilitate communication with LMSs for instance? What are the implications for game design?

These are questions that can only be answered AFTER we have developed models and theories of DGBL, built the analysis and evaluation tools we need to study them within games, and conducted the research we need to validate and refine our models and theories.

As an example of how these theories and models may guide development and implementation of DGBL:

  • IF we know the extent to which content is situated in games (situated cognition and learning), THEN we can make and test predictions about engagement and efficacy

  • IF we understand how challenge and support are structured in games (ZPD & Intrinsic motivation) THEN we can predict and test if and how learners will stay in the ZPD, be engaged, etc.

  • IF we know how often games generate cognitive disequilibrium (Piaget) THEN we can make predictions about whether those games will promote problem solving

  • IF we know how content & prior knowledge are aligned (assimilation/accommodation & instructional design) THEN we can implement and test different support and strategies (scaffolding) for accommodation and assimilation

  • IF we know how learning and game taxonomies align, THEN we can develop and test DGBL that should address appropriate learning levels

This is the kind of focused, theoretically driven base we need to develop in order to generate guidelines for DGBL, which is the focus of the second challenge facing DGBL.


Challenge Two: Generating guidelines for practice in DGBL

Part of this second challenge is a continuation of the first challenge, in that the models and theories we propose should be used to design studies to validate those same models and theories, and to refine and extend them where and when necessary. Likewise, we cannot develop guidelines for practice without conducting research on the effects of various principles and constructs like cognitive disequilibrium on learning, and on the interaction among these principles and game and learning taxonomies. In this sense, practice and research must proceed at the same time and in such a way that they constantly inform each other. The results of this process must then also inform our theories and models of DGBL as outlined in challenge one. In addition, questions regarding cultural, age, gender, and other individual differences in game preference, interaction, and learning will need to be vigorously pursued if we are to develop practical guidelines for where, when, how, and with whom DGBL is appropriate.

Studies of Games and Cognition

We should conduct studies of games and cognition, with engagement, cognitive disequilibrium, scaffolding, endogenous fantasy, game taxonomy, and challenge as independent variables, and learning taxonomy, motivation, and attitude as dependent variables. We should vary cognitive disequilibrium and endogenous fantasy and measure the effect on engagement and problem-solving, for instance, and should follow up with studies to measure the interactions of these independent variables. We should develop DGBL that is designed to address individual learning taxonomic levels and measure their effectiveness for learning and compare them to other forms of instruction. Does DGBL promote deeper learning, faster learning, and promote transfer? Under what conditions, and with whom? We MUST have studies to point to for each of these questions (even if they are too few to be anything but preliminary evidence). We need to be able to at lest point to one study for each of these questions to say "here is how we believe DGBL works in this regard, so work with this while we continue to refine and extend our knowledge." A focused research agenda could generate such studies for these questions in a year or two, but not if we are all working individually in a haphazard fashion.

We need to conduct longitudinal studies of games and cognition. One-shot, short term studies with small n’s are valuable and necessary, but they are not sufficient to answer some of these questions. We know that problem-solving and transfer, two of the hottest areas in the learning sciences right now and two that many of us believe games can promote, cannot be taught directly as sets of rules or principles, but instead require multiple exposures in multiple domains over long periods of time if they are not to remain context-bound (e.g., Black & Schell, 1995; Bransford, Franks, Vye, & Sherwood, 1989; Bransford, Sherwood, Vye, & Rieser, 1986; Brown, Collins, & Duguid, 1989; Gagné, Wager, Goals, & Keller, 2005; Perkins & Salomon, 1989). Would playing certain kinds of games (e.g., adventure/strategy games) for a school year be enough to increase problem-solving? For how many hours per week? Could this be done outside of normal class time? Only longitudinal studies can answer these kinds of questions. Likewise, for the less labor intensive forms of DGBL (games at the lower learning taxonomic levels) it should be possible to conduct studies with large enough ns to warrant more confident conclusions, and in fact SOME researchers should have it in their power to conduct such large scale studies for even higher order cognitive skills. Carrie Heeter and Brian Winn (in press) have recently completed a study of a game they developed to teach about evolution, in which 292 students participated online, for instance.

We should also study action games to see what kinds of practical applications there are for games in different professions. Kirkpatrick's four levels of evaluation (1994) lists the highest levels as transfer (level 3) and results (level 4). Just as with most learning taxonomies and instruction, typical evaluation rarely reaches these highest levels. This is also true of many of the studies we do generate; we have little evidence for the generalizability (transfer) of results to real world settings, and little ability to state the strength of the effects (results). For example, one of the most compelling and rigorous studies of games in the last 5 years was conducted by Shawn Green and Daphne Bavalier at the University of Rochester (2003).

This study showed that video game players had better visual processing skills (they could keep track of more objects at a time, could track moving objects better, were more accurate in their counting of objects, and had faster reaction times throughout) than non-video game players. What made their study so much more compelling, however, was that they then trained non-video game players on an action video game for ten hours (one hour per day) over two weeks, and found nearly identical performance among these players, thus indicating both a causal link for action games and visual processing, and that these were skills that could be improved rather than abilities that explain why some people play games and others do not.

Yet even this study falls short of the kind of research we need to support DGBL. What people are going to want to know for implementation is where, when, and with whom these things will make a difference. We need to extend these studies and build on each other's research to find the answer to these questions. For example, we have just completed a study of air traffic control tower students and video game play at the University of North Dakota's John D. Odegard School or Aerospace Sciences that builds upon the findings of the Green and Bavalier study. It occurred to us that if 10 hours of video game play could improve people's ability to count and track stationary and moving objects, and to do so faster than otherwise possible, air traffic control tower operators might benefit in meaningful (applied) ways both in tower and radar operations.

It also occurred to us that if what appeared to be more abilities than skills could actually be improved this dramatically, other "stable" abilities like the cognitive style of field-dependence field-independence (visual processing of figures) might be similarly impacted, so we included the Group Embedded Figures Test (GEFT, Witkin, Oltman, Raskin, and Karp, 1971), which has been shown to be related to a variety of academic performance measures, as a dependent variable. The results of this study are not available at this writing, but have practical implications for the training of aviation students and perhaps for all students. We need to conduct studies of the effect of different games and game strategies on different performance outcomes, but we also need to take the next step and determine what difference in the real world (professional and educational) these outcomes will make.

Studies of Individual Differences in DGBL

One of the biggest challenges facing instructional design right now is that the increased global presence of companies and the trend toward outsourcing and online training requires that we be able to develop training for multiple cultures within a single company. The best we have been able to do is to develop "cultural value-free" training that is then "localized" by instructional designers living and working within the different cultures the training is to be delivered.14 This is because we don't really KNOW what those cultural differences might be, having not made such studies a priority despite repeated calls by many to do so over the last 10 years.

This issue will be critical to DGBL as well, for three reasons. First, and most obviously, education and learning are global endeavors now, and the increase in online learning alone is enough to justify studies of cultural differences in game preference, interaction, and learning. Second, our classes and training rooms are comprised of people from multiple cultures15, so if we are to implement DGBL anywhere, we will have to consider these cultural differences. Third, just as game players are likely to differ in game play and preference, so are game researchers and practitioners likely to differ in the games they create, implement, and study. Some of the most interesting findings and approaches are likely to come from different countries as a result, just as multiple disciplines generate powerful synergies in DGBL research. I was an invited speaker in the U.K. Open University (July, 2006), and during one recent conversation on definitions of games, a student posted the link to Jesper Juul's keynote defining games (2003) a version of which also appears in the Waldrip and Fruin (2004) text. During this same conversation, someone mentioned an "eLearning" course provided at the Pädagogiche Hochschule Zürich, Switzerland (a university for applied sciences in teaching) that was called 'gender for beginners & eLearning'. The idea was for participants to take on different identities and roles within an online environment. While not a game, the implications for research in DGBL are obvious, yet I would never had come across it if not for cross-cultural communication, and the idea itself may have been partly a product of the cultural views of gender and technology.

A good place to begin these studies, it seems to me, is to examine the sales of different games in different countries. Are the same games popular? Where do popularity of games diverge by country? What games are popular? Once we find this information, we could conduct analyses of these individual games to see what the features and characteristics are, compare that to the literature on cultural differences in general, and begin to formulate (and validate) models and theories for cultural differences in DGBL. It is the individual features of game play that are most critical in this regard rather than the larger question of "what kinds of games do [people from country x] prefer?"

The need for the study of individual differences in DGBL is not just limited to culture, either. Age and gender are two other potential sources of individual differences in game play and preference. In particular, I believe we need to re-examine sex differences in game and strategy preference. Much of the research in this area is out of date, and while people are re-examining these questions (e.g., Heeter, 2003; Van Eck et al., 2006d, and the upcoming Beyond Barbie and Mortal Kombat edited by Jasmin Kafai, Carrie Heeter, Jill Denner, and Jen Sun), much of what can be found today repeats what has become conventional wisdom regarding girls and games. Yet if digital natives are different, then aren't more girls now digital natives than were so in the 90s when much of the research on girls and games was conducted? How much of what was true then is true now? There is some evidence that at least some things have changed.

For example, we conducted a year-long study of DGBL both in terms of game play and game design with 5th and 6th grade students. For half a year, they came in and played a different computer game for one hour each week (games were chosen to equalize exposure to the full range of game types). For the second half of the year, they designed their own games. They worked in groups of 5 (all boy, all girls, 3 boy/2 girl, and 3 girl/2 boy), and we collected data on the games they preferred and on their attitudes toward technology, math, and science. Conventional wisdom led us to believe that girls would do best in the all-girl groups, that girls would in general not like games or would prefer "girl" games (e.g., Rockett's New School), and that girls and boys would think technology was not equally appropriate for boys and girls.

Interestingly, the first thing we found was the most girls (and boys) believe technology was appropriate for both sexes, which immediately contradicted one expectation. Further, we found that girls attitudes remained unchanged in this regard, whether they were in all girl groups, boy majority groups, or boy minority groups, thus negating a second expectation based on conventional wisdom and prior research. Boys in the girl majority group, however, came to believe technology was less appropriate for girls than they had initially! Both boys and girls, incidentally, came to believe that science, math, and technology were both not as related or difficult as they had at the start of the study, indicating that game play and game design can improve attitude toward technology. Finally, while we found that there were sex differences in game preference (girls did and boys did not like Rockett's New School, and boys did and girls did not like Battlezone), boys and girls liked adventure games equally, even to the point that boys liked Nancy Drew (after they had stopped groaning and started actually playing it!).

And even in the games they both reported liking, the way they chose to play those games differed dramatically. With the game Sim Safari, for instance, which both boys and girls rated highly, girls focused on building houses with plumbing, Jacuzzis, etc., validating Maslow's hierarchy of needs in terms of shelter and safety. Boys, in turn, built swamps and immediately overpopulated them with alligators and jaguars!

This latter aspect highlights an important aspect of these studies. We should look not just to game genre preference, but to differences in gameplay and feature or strategy preference within games, as this is likely to be most informative for individual differences in DGBL as a whole. Finally, we must examine differences in all aspects of DGBL, including styles of problem solving, differences in the roles or features engagement and cognitive disequilibrium, support and scaffolding, etc. If we don't do this, we have little hope of meeting challenge three.

Challenge Three: Generating a body of high-quality DGBL


Clearly, the long-term success of DGBL will rely on implementation that is guided by validated interdisciplinary models and theories, the research that springs from them. Our practice is also likely to be most successful if we use the outputs of the first two challenges to develop DGBL practices within a framework of the learning sciences. In particular, I believe instructional design has a lot to offer, whether we are talking about integrating commercial games into the curriculum, developing instructional games from the ground up, or having students develop games.

Much of how I believe instructional design can contribute to this process can be found in earlier work (integrating commercial games: Van Eck, 2006c; designing learning games: Van Eck & Dempsey, 2002; Van Eck, 2006a). Just as theory has to guide our analysis, evaluation, and research with games, so must it guide our implementation of games in learning environments for instructional purposes. It is important to make a distinction here between instructional uses of games, and the use of games to promote non-specific skills and abilities. Some of our early research will undoubtedly point the way toward the use of games to promote certain non-domain specific abilities. Put another way, we will find that games promote implicit or enabling skills that in turn support the development of expertise in specific domains of practice.

So while games have the ability to promote all varieties of learning, some learning will be accomplished as general training (e.g., improving reaction times, visual processing, dexterity, attitude toward content) and others will be the result of specific instructional designs within different content areas (e.g., using Civilization to teach problem-solving and concepts in history, developing games to teach problem-solving, transfer, rules, and concepts in mathematics, or using jeopardy style games to teach verbal information).

As I alluded to at the beginning of this section, there are three ways to implement DGBL in school and corporate settings. We can have learners design and develop games, we can integrate commercial games into the curriculum, or we can build games to teach from the ground up. Each of these approaches has its strengths and weaknesses, and each has its place in the practice of DGBL. Having learners design games is of primary use in educational settings, and is largely non-instructional as I have defined earlier, so I will not spend much time on this approach except to say that we should continue both the practice and the study of this approach to DGBL.

The other two approaches, integrating commercial games into the curriculum and building instructional games, have a far shorter history and one characterized by much more inconsistent success. As a result of this, and because they are both designed to directly address domain-specific instructional content, instructional design can play a critical role in guiding our practice in both approaches. I have described this process for both approaches elsewhere in far more detail than is possible or necessary here (Van Eck, 2006a; Van Eck, 2006c). Instead, I will briefly describe these approaches and discuss the particular advantages and challenges of each in establishing a rich body of practice in DGBL.

Integrating Commercial Off-the-Shelf (COTS) DGBL

COTS DGBL has been shown to be effective (e.g., McFarlane, Sparrowhawk, & Heald, 2002), which is one of the reasons that the NESTA FutureLab & Entertainment Arts game company have partnered to study the use of games in classrooms in the U.K. (2005). It is, in my opinion, among the most practical approaches for quickly building a body of practice in DGBL, for two reasons. First, the costs of developing games preclude this use by most educators; commercial games are much more practical to use from an economic standpoint. Certainly, the open-source game engines like Neverwinter Nights and other inexpensive engines and game development platforms are beginning to change this, but cost is not the only issue. The learning curve and development time required for building games are prohibitive for widespread adoption and implementation by teachers, and while this too is changing, there is a limited number of people who will avail themselves of this approach for the next few years, which in turn constrains the number of games (and thus DGBL examples) available to us. To be sure, COTS DGBL is not an effortless process, and teachers need instructional support initially as they learn how games work, how they can be tied to curriculum goals, standards, and objectives, and how to design instructional and assessment activities around them, but the essential skills sets are within their reach in ways that is not true for other forms of DGBL.

So why does it matter how many people are involved in this, and why should we care how many educators we can get involved? We need to show game development companies and textbook publishers that there is widespread use and interest for games in the classroom. Until we show there is an economic base for games in learning environments, we will have limited success in convincing both industries to pursue the development of serious games. While we may argue until we are blue in the face that the failure of the edutainment industry in the 80s was caused in equal parts by bad business models and marketing, and by poor integration (if that word can even be used) of content within games, but the fact remains that a lot of people lost a lot of money in edutainment, and they are understandable gun-shy about anything that even smells like education. We have to build a critical mass of DGBL practice in the classroom to encourage a re-investment in the process. Game developers are the engines for this development, and textbook publishers will be the vehicle for aligning games with content (with the help of instructional design).

To effectively support this kind of DGBL, we must do three things. First, we need to build collections of examples of DGBL organized in databases that are searchable by standards, grade level, game, etc. There are a limited number of early adopters who will build lesson plans around games. There are more who, if given examples and ways to search for examples appropriate to their needs, will then implement DGBL. There is a third group who, upon seeing respected peers within their institutions implementing COTS DGBL successfully, will seek out support from these people to find out how to do the same thing. As these second two groups become comfortable implementing previously designed COTS DGBL, many will consider developing their own examples, which can in turn serve as examples to others. Such databases will expand the reach of COTS DGBL beyond the innovators and early adopters.

Integrating commercial off-the-shelf involves re-purposing and integrating commercial games within a given class, lesson, unit, or curriculum. There are several challenges to doing this effectively which are not immediately apparent to many at first glance. Instructional design takes a systems view of instruction, including the environment, learner, content, resources, strategies, and technology. This systems approach is manifested in instructional design models, all of which share the same essential characteristics despite being designed for different purposes and philosophies. These characteristics are Analysis (of the learner, content, outcomes, environment, etc.), Design (of the instruction, including objectives, assessment, strategies, media), Development (of the instruction, based on the design specifications), Implementation, and Evaluation. This process is often called ADDIE (add-ee) for short. While the ADDIE process is not specifically designed to support the re-purposing of media (like games), the principles are useful in developing curriculum that makes use of games as an instructional medium or strategy. I have outlined the process needed to integrate (COTS) games into the curriculum elsewhere (Van Eck, 2006c) and in much more detail than space permits here. Suffice it to say that while COTS DGBL requires effort and resources to do well, instructional design provides a useful set of tools and processes to support this process, which is well within the capabilities of teachers working within the constraints of the existing curriculum and school system.

Building Games from the Ground Up

The second way of establishing a body of DGBL is to build games to teach different subjects. The advent of several new game development tools and engines, the decreasing learning curve for these tools, and the increasing skills of those interested in building learning games have all converged to make this a much more viable option than even 3 years ago. There is also a growing interest among individual game developers, if not companies, in Serious Games, and I suspect that we will see a significant increase in the number of learning games available. Once again, the design of these games must be guided by both the science of learning and the theories, models, and tools I have described earlier in the discussion about challenge one. These games will also benefit from the use of instructional design models and principles, in that ID will safeguard the still significant investment of time and effort it takes to build serious games.

There are hundreds of researchers and game developers who are working on building these Serious Games, and the body of DGBL created is both advancing the field through practice and providing good examples for study. One particular way of building DGBL16 that holds a great deal of potential lies in what I call intelligent learning games (Van Eck, 2006a). This approach relies on interdisciplinary theory and tools from, among others, artificial intelligence, narrative psychology, pedagogical agents, authoring tools, and discourse studies. ILGs are a concrete example of the synergy and efficiencies that exist by taking an interdisciplinary approach to DGBL: validated tools and models, a rich base of research studies to draw from, and a convergence of several compatible approaches to generate powerful learning tools in a short period of time. ILGs are what account for three of the 10 areas for research I postulated at the beginning of this chapter, artificial intelligence, new models of discourse & distributed learning, and authoring tools & EPSSs for content integration, and they will all be addressed within the context of building ILGs.

Integrating Content in Games without Killing the Game.

This has been one of the most significant challenges we have faced in designing serious games, and it still dominates most of our professional and personal discussions in this regard. Traditional approaches have been more about combining games and content rather than integrating them. Yet we know that a strength of games is that content is seamlessly integrated within the game, with progress toward achieving the learning objectives being continually assessed as learners are required to demonstrate mastery. We know that putting a "book" in a game to deliver large amounts of text-based instruction is NOT integration, yet such are the approaches that have characterized our early attempts at building educational games. We need to find ways to make the content a part of the game world.

If we look at many immersive adventure, strategy, and role-playing games today, we find that it is typical to interact with several characters (either NPCs, non-player characters controlled by the game AI, or PCs, player characters controlled by other game players). There exists in psychology and instructional design a growing body of research on what are called pedagogical agents. Pedagogical agents are animated characters (real or fantastic) akin to NPCs. The computer-based instruction they are embedded in controls what they say and how they say it.

It is not much of a stretch to see how agents could be used in ILGs, then. They have the potential to become characters in game, adopting roles that are consistent with games (e.g., co-investigator, mentor, police experts, military commanders at command central, a team member like in the Mayo clinic model of healthcare, or simply a colleague or peer who has relevant content expertise.

PAs may offer potential for the integration of content in games, but they do little in the way of providing guidance. By combining them with another learning technology from cognitive psychology and AI called intelligent tutoring systems (ITS), we get not only a way of integrating content in games, but of structuring that content for effective learning. ITSs work by engaging the learner in a tutoring conversation to elicit from the learner as much as possible as they solve a problem within a given domain. The ITS, many of which now incorporate agents, uses a variety of sophisticated technologies (natural language generation, latent semantic analysis, speech act classification, algorithms to determine matches to expected responses and selection of suitable responses for those that are unexpected). It is possible, then, that they could be used to structure and deliver content through PAs as part of game environments as well, and in fact many researchers have called for the blending of ITSs with other technologies such as AI, agents, & games (Laird & van Lent, 1999), ITSs and immersive environments (Ravenscroft & Matheson, 2002; Regian, Shebilske, & Monk, 1992; Rickel, 2001; Shute & Psotka, 1996).

These ITSs have been shown, over the course of the last 30 years, to be nearly as effective as human tutors (Corbett et al., 1999) in many domains (Graesser et al., 1999; Anderson, Boyle, & Reiser, 1995; Schofield and Evans-Rhodes, 1989; Gertner & VanLehn, 2000; VanLehn, 1996; Stevens & Collins, 1977). Part of their success lies in the power of discourse, and the role in particular of questions, hints, and prompts.

Hints and prompts, of course, are used as scaffolding to keep the learner in the ZPD, which we have seen is one of the principles inherent in game design, so the potential for integrating ITSs with the game world exists. And in fact, games often make overt use of questions and hints, such as when a list of possible questions is presented when talking to an NPC, or when the game provides time reminders or even verbal communications from NPCs to keep the learner on track.

So pedagogical agents, ITSs, and discourse theory (all theories and learning technologies from multiple disciplines) can be synthesized to guide the development of DGBL. Obviously, this is a much more complex process than the brevity of this description implies. I describe this process in much more detail elsewhere (Van Eck, 2006a).

Summary

I set out to discuss ten areas that are critical to study in order to help establish DGBL as a discipline. Those ten areas are derived from what I see as three challenges facing DGBL in the next five years:

Challenge One: Generating & Validating DGBL Theories & Models

  1. Develop new interdisciplinary models

  2. Develop and evaluate tools for game analysis

  3. Blend taxonomies of games and learning


Challenge Two: Generating Guidelines for Practice

  1. Study games and problem-solving

  2. Study "twitch" games and visual processing in professional practice

  3. Reexamine and refine studies of sex differences in games

  4. Study cultural differences in gameplay & design


Challenge Three: Generating a Body of high-quality DGBL

  1. Extend research and design with artificial intelligence as a field and in games

  2. Develop new discourse models for distributed learning & cognition

  3. Develop authoring tools for content integration in intelligent learning games (ILGs)


By now I hope it is clear that each of these challenges relies, in the long-term, on our having met the preceding challenges. Obviously, we cannot literally wait until each is completely achieved. Be we must be aware of the interrelated nature of each challenge, and we must address the most pressing questions which I have attempted to outline here. If we can begin to answer these questions for ourselves and for those who will soon need the answers (even if they do not ask the questions), we will make the transition to a field and discipline. We have a window of opportunity here, and the need for real educational reform may never have been stronger, but that window will not stay open forever.

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Affiliation

Richard N. Van Eck

Instructional Design & Technology

University of North Dakota


Jamie Kirkley, Ph.D.

Sonny Kirkley, Ph.D.

Jerry Heneghan


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