[In this comprehensive thesis, Sébastien Hock-koon details the results of his PhD research and his first-hand experience regarding the unique potential for learning in video games. This article was first published in the Proceedings of 2012 DiGRA Nordic.]
James Paul Gee argues that good commercial video games incorporate good learning principles, which he describes in his famous book What video games have to teach us about learning and literacy (2003). What players learn when they are playing video games is not always good, but "what they are doing when they are playing good video games is often good learning" (ibid., p 199). Gee sees 36 learning principles at work in video games, although they are not exclusive to games. Among these, we may mention the following principles (ibid., p 207-212):
- Active, Critical Learning Principle: The learning environment encourages active, critical and not passive learning.
- Achievement Principle: For all skills levels there are rewards for improving oneself.
- Practice Principle: Learners spend a lot of time on the task.
- Multiple Routes Principle: Learners are allowed to find their own way to make progress relying on their strengths and their own style of learning or problem solving.
- Discovery Principle: Learners are given the opportunity to experiment and make discoveries.
Marc Prensky considers that learning always occurs when someone plays (2005, p 104):
Learning takes place every time one plays, in every game, continuously and simultaneously, on several levels. One need not even be paying much conscious attention. But we do have to pay some attention in order to analyze how and what players learn.
The process of learning a commercial video game may be observed as what Daniel Schugurensky calls "informal learning" (2007). Informal learning is not easy to define. Formal learning refers to learning occurring in situations specifically designed to teach by educational institutions. Non-formal learning happens in situations designed to teach by other institutions. Informal learning would thus be "everything else" (ibid., p 14).
One problem with informal learning is that it may be unconscious as well as unintentional. Plus, we often lack tools to estimate the efficiency of this type of learning. In school, we may use exams or tests to evaluate students, however it is more difficult to evaluate players of video games. Exams and exam situations are designed to avoid cheating, which may be understood as minimizing the risk of students giving the right answer without having learnt it. Video games do not face the same issue; they want players to keep playing. One methodological obstacle is highlighting the actual learning that occurs in commercial video games. Prensky also pointed out that measuring "true learning [...] is no easy task. The real measure of learning is behavior change [and] we can never know this until it happens" (2005, p 103).
According to Gilles Brougère (2005, p 152), the question of informal learning lies in the relationship between the learning affordances of an activity and the player's engagement in this activity. In other words, informal learning relates what is possible to learn from a situation to the player's disposition to actually learn what she or he may learn from this situation. What a player can learn with a game greatly depends on the game's design (Prensky, 2005, p 103):
Many criticize today's learning games, and there is much to criticize. But if some of these games don't produce learning it is not because they are games, or because the concept of "game-based learning" is faulty. It's because those particular games are badly-designed.
A good video game may be designed to help the player learn how to play but the activity itself is not designed by the game developer. Indeed, if "ultimately, game design is play design" (Salen & Zimmerman, 2003, p 299), the game designer only defines it indirectly. You can never know for sure whether or not the game will work (ibid., p 67):
Game design is an act of faith - in your rules, in your players, in your game itself.
This article will leave the question of engagement aside and study video games' affordances of learning. More precisely, the focus will be placed on the particular learning offered by "great video games" (Kunkel, 2003). This study will allow the introduction of the concept of "elliptical learning."
Many researchers share a belief in video game's educational potential. Kurt Squire and Henry Jenkins (2003) pointed it out in Harnessing the power of games in education, but even today we are still "a long way from having tapped the full pedagogical potentials of existing game hardware and design practices." Katrin Becker studies the design of successful commercial video games to improve the design of educational digital games (2008). However, as pointed out by Van Eck (2006):
If we continue to preach only that games can be effective, we run the risk of creating the impression that all games are good for all learners and for all learning outcomes, which is categorically not the case.
In order to use video games properly, we should not only understand how and why they may work as learning tools but also, and perhaps even more importantly, how and why they may fail. Linderoth (2010) suggest that we may be mistaken about their potential as teaching tools. More precisely, he criticizes the way researchers relate a successful action in the game to learning. He uses Gibson's ecological approach and the concept of affordance to study how video games may facilitate the player's progression without requiring actual learning. Thus, he points out that, in order to know whether or not a player has learnt something in order to achieve a goal, one must carefully study both the game and the practice. This approach allows the researcher to understand the difficulty level in order to track whether or not the player has gained knowledge.
Through the concept of affordance, Gibson's ecological approach (1979) leads us to consider the relations between the environment and the subject. There is often some confusion between Gibson's affordance and Norman's affordance (1988). Joanna McGrenere and Wayne Ho (2000) compared affordances as defined by Gibson and Norman:
Offerings or action possibilities in the environment in relation to the action capabilities of an actor
Independent of the actor's experience, knowledge, culture, or ability to perceive
Existence is binary - an affordance exists or it does not exist
Perceived properties that may or may not actually exist
Suggestions or clues as to how to use the properties
Can be dependent on the experience, knowledge, or culture of the actor
Can make an action difficult or easy
Table 1: Comparison of affordances as defined by Gibson and Norman.
Norman himself recognized a misunderstanding about the way he used the term "affordance" (2011):
I introduced the term affordance to design in my book, "The Psychology of Everyday Things" (POET: also published as "The Design of ..."). The concept has caught on, but not always with true understanding. Part of the blame lies with me: I should have used the term "perceived affordance," for in design, we care much more about what the user perceives than what is actually true. What the designer cares about is whether the user perceives that some action is possible (or in the case of perceived non-affordances, not possible).
An affordance is an action possibility offered by the properties of an environment to the capacities of a subject. According to this concept, an action is possible not only because the subject is able to perform it but also because the environment allows it. The environment may make an action easier; in this case, performing it will require fewer capacities. An action may be facilitated by the game itself which would limit compulsory learning. Linderoth (2010, p 6) enumerate several ways to do so:
- Designs for supporting exploratory actions: Highlighting, alternative vision modes and points of interest help players to see and find affordances available in the game environment.
- Designs for supporting performatory actions: Changing the played character, improving her or his capacities or equipment, giving temporary power-ups make performing actions easier.
Using this kind of assistance reduces what a player has to learn in order to succeed in a video game. It is why this learning has to be questioned by a real knowledge of the studied game. Linderoth's argument may be related to Becker's "Magic Bullet" Model (2011). This tool is intended to monitor the way a game manages the player's learning and it classifies learning in four categories (ibid., p 22-24):
- Things we CAN learn: It includes "anything and everything we can learn directly from the game."
- Things we MUST learn: This set is "almost always [...] a subset of the first category". It includes "only those items that are necessary in order to win or get to the end."
- Collateral Learning: This category includes things that "are not part of the game and that do not impact on our success in the game."
- External Learning: This set includes "learning that can impact on our success in the game but that happens entirely outside of the game in places like fan sites and other social venues."
Linderoth does not negate the amount of "Things we CAN learn" from a video game. On the contrary, he suggests that the category of "Things that we MUST learn" in order to finish a video game may be far smaller than what researchers would expect initially.