Instructional Technology Research Online

Learning to Play; Playing to Learn: 
Lessons learned from computer games

Marshall G. Jones Northern Illinois University
This paper was originally presented at the annual conference of the Association for Educational Communications and Technology. Albuquerque, NM. February, 1997. This initial reporting of the data from an ongoing study is intended to raise issues, and stimulate discussions. If you have comments, please address them to Marshall Jones: Permission is freely granted to reproduce this article provided all credit and proper citations are included. Copyright for this paper is maintained by the author.


Saloway (1995) makes up a word, I think. The word is zorch, and it refers to the processing power of the personal computer. It is common knowledge that we have greater processing power today than we have ever had, and that the processing power continues to grow. According Saloway, an increase in zorch makes it possible to do greater things on the computer. When Jonassen (1988) began to postulate on the notion of generative learning environments, he was speculating that the power of the computer would one day match the power of the human mind. That learners would be able to act and learn in an environment that would provide them with the choices, tools, and constructs to help them learn, and not merely instruct them. While computer based tools are becoming more sophisticated, the general public is also gaining more facility and familiarity with the technology as well. The metaphor of personal computer interfaces has nudged its way into popular culture. Print advertisement uses the look of a web page, and commercials, news casts, and even Super Bowl coverage use familiar cascading menus and multiple windows.

In Instructional Technology, we have been focusing on computer-based learning tools for a long time. From mainframe to multi-media, we have held that computer based tools can and will help people master skills and become better learners. In research on computer based learning tools, we have built environments that test what features people like best, and what features manifested in the software will best aid people in their own personal learning goals. Additionally, we have been concerned with how the software looks (Hannafin & Hooper, 1989; Heines, 1984), how the program functions (Jones, Farquhar, & Surry, 1995; Laurel, Oren & Don, 1992, MacLean, Young, Belloti & Moran, 1991; Schneiderman, 1987), and whether or not people learn from it (Alessi & Trollip, 1991; Bork, 1987). One thing that we have found is that people can learn from computer-based learning tools. As both hardware and software become more powerful and sophisticated, we have begun to focus on designing and developing computer-based learning environments (Hannafin, 1992; Jonnasen, 1992; Reiber, 1996).

A computer-based learning environment is one where learners interact with information in a self regulated environment (Reiber, 1996). In a learning environment, users are free to define their own problems and work towards individual solutions. The problems, processes, and procedures employed within the learning environment may differ dramatically as they are initiated and implemented by the individual learner. Conversely, instructional environments hold the designer as primarily responsible for creating the regulatory structures of the environment. Both the problem, and solutions are determined by the designer, and all learners will likely take the same path towards the solution. If we set aside the arguments about which one is more effective for a moment, and assume that each has its place and purpose, then we can focus on the strengths and weaknesses that are inherent to each. Thispaper focuses on learning environments, and narrows its focus further to the concept of an environment.

A working definition of environment is: The complex of social and cultural conditions affecting the nature of an individual or a community. Applying this definition to computer-based learning environments, it becomes necessary for us to consider the gestalt of the environment. When thinking of a learning environment, I prefer to work with Reiber¹s notion of an endogenous learning environment (Reiber, 1996). In these environments, the content and its structure are so closely related that "one cannot tell where the content stops and the game begins" (Reiber, 1996, page 50). One place where this notion of endogenous environments is most notable is in the area of commercial computer games. The games themselves are motivating, and weave a fabric of content and fantasy so seamlessly that one can become lost in the game for hours. The purpose of this study was to examine if there are underlying constructs inherent in computer games which could be extrapolated and applied to the design and development of computer-based learning environments.

 Purpose of the Study

Why do people play computer games? Why is it that a virtual environment consisting of worlds, characters, places, names, and physical characteristics which have no counter part in the physical world can draw people in and engage them for hours? Games engage many people. Of this much we are sure. The question posed in this study is how do games engage people? And if we can ferret out how games engage people, can we then extrapolate and build upon these concepts to be used in computer-based learning environments? These were the original questions asked in a grant proposal. The purpose of the grant was to secure the artifacts needed to conduct the research, namely, access to a wide variety of popular game titles. The game titles selected were intended to be pure entertainment games. Educational games were not originally included in the study because it was desired to look at what entertainment games do to engage people.


Which games should be studied?
The first step was to determine what games to study. The original plan was to study the ³best² games on the market as these would likely prove to be the most engaging. A literature search yielded several magazines on games and gaming, and while some did provide ³top ten² lists, such as Levy (1995), many of these lists had very different choices for their top ten.. A web search on game reviews yielded scores of sites on game reviews. And while many sites rated games (e.g. Gamer¹s zone review: www.worldvil, Bathaus Game Reviews: ews.htm, and, none presented a top game list. Surveys were posted to various listservs asking the question: ³What is your favorite game and why is it your favorite game?² Nearly 200 people responded to the question. The top vote getters for favorite games were: Myst, War Craft II, Doom II, and Civilization. However, no consensus was reached to determine conclusively what games are the ³best.² People seem to develop rabid attachments to the games that they play, and can give very eloquent arguments about why the game they like to play is the best. In the absence of a consensus on which games should be studied, it was decided that a variety of different games should be purchased for the collection. These games fit into three broad categories: Action (e.g. Doom II), Strategy (e.g. War Craft II), Fantasy (e.g. Myst). The actual games selected to be purchased for the grant were chosen because they represented a breadth of content. The games were divided as equally as possible between Mac and Windows platforms, although many of the games were hybrids, meaning they ran on either platform.

Analyzing the games.

An initial analysis was conducted to provide a familiarity with the games. While it would be impossible to play and master all 35 game titles, a basic familiarity with the titles selected was desired. A journal was kept to record basic purposes of the games, methods of navigation, and interesting features of the games. Particularly representative games were analyzed in detail to develop a listing of unique features and constructs in order to drive subsequent interviews.

Locating players for the games.

During the first stages of the research, chain sampling (Patton, 1990)was employed. Using constant comparative analysis (Patton, 1990), the concurrent data collection and analysis drove the focus of the study and the selection of participants. When gamers were identified, they were given the list of games to choose from. While many participants did choose from the list, others looked at the list with disdain. "I don¹t want to play any of those games. They suck." Was the comment from one participant. The games on my list were too "mainstream" for this gamer. Another participant stated, " I really don¹t want to play the games you have here, but I have been playing this really great gameŠ. Would you be interested in including it in your study?" This quickly became a recurring theme and comment. Which suggests once again that gamers develop radical attachments to the games they play. Consequently, games were included in the study that were not originally purchased as part of the grant.

Data Collection

Data was collected from an analysis of the games, from interviews with participants in the study, and through observations of people playing the game when possible. Participants here are defined as people who played the games. Games were loaned to the users from the set of games purchased by the grant, or were games owned by individual participants. The majority of the participants at this point are males, and their ages range from 22-56. Subesquent studies, not reported here, will be more gender inclusive. However it is important to note that many games are unabashedly marketed towards males, and the majority of game players are male. The majority of data was collected through the use of interviews either via electronic mail, phone, or face to face interviews. One participant, a 5 year old girl, was observed playing the games, and interviewed during and after playing the games. The following are issues learned from an analysis of this initial data collection. The headings used are representative comments taken from interviews with the participants. They are areas raised by participants as being important in understanding what games do to engage people. Each is discussed in terms of what it does in engaging people, and how it may be manifested in a computer-based learning environment.

Production Value

One thing seems to be abundantly clear: neatness counts. Participants stated that an important piece of their enjoyment was linked to how good the game looked. The quality of the multi-media assets such as images, sounds, and animations, were a key factor in getting people interested in the game, and interested in playing the game. This is an important issue to be considered in the design and development of educational software. Rather that ³settling² for assets, we should be working to find appropriate and quality images and sounds to make learning environments richer, and ultimately more meaningful and enjoyable experiences. However, it is important to note that while attention to detail is important, they should have a purpose to them. As one participant stated, ³I don¹t know why they put those (video clips) in there. Probably because they could.² Some features were included in games that while technically impressive, had no real relationship to the environment created. This is true in many pieces of educational software as well. Pushing the envelope is a noble ambition (Jones, Farquhar, & Surry, 1995), but pushing the envelope should be done relative to the environment itself, and not simply because it is possible.

Mix of Strategy and Twitch

Strategy games are ones in which the user must employ higher order thinking skills and problem solving skills to continue playing and win the game. Twitch games are games in which the user must react quickly to circumstances, usually by killing someone, to continue playing and win the game. SimCity and War Craft II are immediate examples of strategy games, while games like Doom are consummate twitch games. The advantage to a twitch game is that the movement is quick, and the feedback immediate. This works to keep the user actively engaged. However the level of this engagement is often superficial. It does not typically engage one beyond the most basic level of seeing, pointing, and clicking. Strategy games require the user to look at the larger problem, and plan a strategy to solve the problem. In some games, such as SimCity, the results of your decisions are not immediately recognized. You must have a fair amount of internal motivation to stay with the game to realize the fruits of your labor. While twitch games offer immediate results of your work, strategy games appear to offer a greater feeling of accomplishment and satisfaction. One participant who was playing War Craft praised the combination of ³twitch and strategy.² While they ultimately liked working on complex problems in an environment, they also appreciated the sheer visceral rush of immediate feedback.

Consequently, when designing learning environments, it should be the goal to include ³fast action² along with a more unifying problem to be solved. One simple method of doing this is to include twitch type mini-games within a larger strategy game. Monty Python¹'s quest for the Holy Grail does this, as does 11th Hour. And while it is not seamless, and can appear a bit crude, it does at least provide some a faster element to the environment than many strategy games typically afford. Educational games such as Math Blaster offer the twitch with some elements of thinking, but these types of games are simple drill and practice activities in disguise. They are good for practicing certain skill sets, but do little to help develop higher order thinking skills. One possibility would be to use math skills to solve certain problems that relate to the larger problem. The difference is that the individual skills then become tools to solving the larger problems, which is ultimately the goal of education in the first place.

Thinking around corners

"The puzzles in 11th Hour really made me think around corners." Thinking around corners, as defined by one participant is the use of many different problem solving skills required to solve the larger problem. In 11th Hour this was engendered through the use of different puzzles, riddles, and competitive games that all aggregate to build an environment where you are collecting clues to solve the ultimate problem. To think around corners, one must ³Šlook at the problems sidewaysŠ.² This means answers are not necessarily obvious, but require you to accumulate information, assimilate information, and fit it into a pattern that is unfolding before you. This is a remarkable manifestation of the Piagetian theory of accommodation. While we may try to acquire new information to fit into existing schemes, in many games we are attempting to understand a new world through building new schemes. Juxtaposing the obvious with the indistinct is common in games.

Looking at this from the standpoint of building learning environments, it may suggest that we not make things obvious to learners. To learn one¹s way around a new city it is often necessary to get lost a few times. For it is only through getting lost that one can begin to understand the relationships of even numbered streets to odd numbered streets, and be able to navigate a new city.

Navigating a new city is much like navigating a new computer-based environment. While there may be some things in a computer-based environment which look familiar, many elements and controls are still very different. Dissonance can be a valuable learning tool.

Dissonance is easier in games because they are not constrained by content. In educational software it is more difficult to design for dissonance because ultimately we must answer to the content and its veracity. In games, if one needs a new element to make the game work, it can be created. While elements in learning environments may be manufactured, it could never be at the expense of the content.

Failure as Learning

Failure is valuable in gaming. Because of the modular organization of games, the user can make mistakes which halt play, but typically the user can begin that level again, or possibly return to a saved game. Failure is also valuable in learning. One can be told countless times, but making the mistake and the proper adjustment creates deeper connections with the content than simply trying to remember the answer. Learning new Worlds

Most games create an environment that the user must accept if they are to win the game. This environment can be one which is completely fictional, such as Doom or Myst, or it can be one that has some counterpart in the physical world, such as SimCity or Kyoto: The Cosmology of Old Japan. Regardless of whether the environment is real or contrived, it must be engaging. Elements that tend to engage users are things such as believable characters and circumstances, an illusion of reality, and a set of controls that make sense relative to the reality they are engaged in.

The concept of believable characters is hard to define. In an action game such as Doom, the characters run the gamut between homicidal-gun-wielding villains, to monsters that are almost invincible. To believe that these characters are real, the environment must reinforce this. The goal in Doom is to get through each progressively difficult level. The greatest impediment to your success is the cast of villains in your way. You are thrown into a labyrinth where you must open doors, find keys, throw switches to open doors, and shoot people who get in your way. The illusion of physically being in this environment is heightened by pulsing music playing, and by the sound of your guns and others guns. All of these elements work in concert to make you believe that you, and not merely your computer character, are in physical danger. The lesson to be learned in this is that by careful attention to the gestalt of your environments, you can convince somebody that they are in fact there. The situations encountered in Monty Python¹s Quest for the Holy Grail are farcical. But the environment created by the game makes it possible for you to accept it, in its virtual form, as real. The creation of an environment is important to creating a place where people can exist, virtually, and thrive, or fail. The point that Reiber (1996) does not raise in his excellent article about the definition of play, is that in endogenous games the key to creating a learning environment is the environment itself. The environment is more than simply the sum of disparate parts, but it is an entity in and of itself.

Etablishing Problems I want to solve

In games, the problem is everything. There is no sense in putting yourself through the trials and tribulations unless you genuinely feel that it is worth your time. More than one participant never finished a game because it was"boring." Boredom in the game can come from different areas. Boredom with the visual appeal of the program is not uncommon, and many "older" games are not played anymore because they lack the visual and aesthetic sophistication of today¹s games. Boredom more often occurs from a lack of interest in the problem. Defining or establishing problems is important. While it has been advocated that the learner should establish the problem (Reiber, 1996), it might also be valuable to give the learner a problem. Gaming environments present us with predetermined problems all the time. Could this be a technique that could be employed in learning environments? Designer driven problems are not uncommon (Reiber, 1996), and they are often seen as limiting to the learner (Jonassen, 1988). However, interesting problems provided to the learner may prove to be as powerful in learning environments as they are in games. Obviously the larger question becomes, who gets to define what is interesting.


It is important to note that most of the participants in this study defined themselves as "naturally competitive," or as "never being afraid of a challenge." The point is critical: these are people who are not afraid of learning a new environment. These are people who thrive on the competition with others and the competition with themselves. Mistakes are not seen here as debilitating, but as a means of gathering new information to make one¹s self more capable of solving the problem. This is likely not true of every one. Many people do not like to play games. The amount of time involved, the obscurity of the patterns, and the difficulty in seeing the end make games not only not interesting to some people, but quite threatening as well.

It is also important to note that the majority of participants in this study were males, and the data collected, analyzed, and reported here does have a male bias. Whether or not issues raised by females would be different remains to be seen. In the initial sampling for this study, female game players were hard to find. A subsequent study which is ongoing at the time of this writing does include more females, but it is not reported here. Conventional wisdom, and much of the discussion on the gaming listservs I participate in, suggests that many games are not as appealing to females, but this has yet to be proved empirically. A tremendous need exists for studies of gender issues in gaming specifically, and in computer attitudes in general.

To say that every learning environment should include features of games, or somehow adhere to the conceptual similarities of games is naïve. However, it is worth considering the following: The principles in games are known to be engaging. Learning environments are meant to engage learners in a self regulated environment. While intrinsic motivation will keep many people working in the environment, others may not bring the natural curiosity or interest needed to thrive in a learning environment. Considering the notion of play and its implication to learning is important (Reiber, 1996). If we accept the notion that play can be useful, then a natural extension of this is to look at environments where play is successful.

As with any research, further study is required to reach any conclusive findings about how gaming concepts can be included learning environments, and what gaming concepts should be included in their design and development.


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Cite this document as:
Jones, Marshall G. Learning to Play; Playing to Learn: Lessons Learned from Computer Games. [Online] Available, March 7, 1997. 

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