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  • Affordances of Elliptical Learning in Arcade Video Games

    - Sébastien Hock-koon

  • Elliptical mechanism + elliptical closure

    The non-learning afforded by Linn's gun to the player emerges from both the properties of the gun and the capacities of the player. In order not to learn something about this gun, there must be something that can be learnt and subsequently ignored about it. I consider the two main points to be hidden features and a weakness that can be counterbalanced. On the one hand, hidden features refer to the fact that one press of a button may have many consequences at the same time. When you press the button A, there are two possible outcomes: you may fire bullets and empty the gun gauge or you may prevent your character from moving while she is reloading. These outcomes depend on the state of the game at the moment you press the button. It is possible to ignore some of these relations and consequently not understand what is happening.

    On the other hand, Linn's gun has a strong weakness that can be compensated. This feature allows the gun to present two faces to the player. Without mastery, it seems weaker than the other guns, but with enough skill, it becomes the most powerful. This gun may perfectly have been the best weapon for both beginners and expert players. A gun which could instantly kill every enemy on the screen with infinite ammunitions would be the best weapon for beginners as well as experts. But Linn's pistol is not good for beginners; this change of perception rewards the attention given to the game by the player. It also makes learning worthwhile because there is a real gap between the average affordances offered by the gun to a beginner and the ones available when you truly master it.

    In video games, many weapons offer various affordances depending on the player's skills. In Halo and Philosophy (Hock-koon, 2011), I highlighted the phenomenon through a study of Halo: Combat Evolved (Bungie Software, 2001). The different weapons of the game are more or less efficient according to the player's skills and the difficulty level. Beginners' weapons are easy to use but finally become ineffective as the player reaches harder levels. Experts' weapons are rather useless as long as they are not mastered, but once they are, beginners' weapons cannot compare with them. But even a good player may keep using beginners' weapons if she or he does not know what experts' weapons are capable of. Indeed, Gibson's affordances are independent from the subject's knowledge or ability to perceive them.

    When I started my training, I was at the third level of understanding. I reached the fourth level by watching a one credit-run performed by the supergamer "Naru2005" (2008). I had to watch a few levels before realizing that the player was able to move while reloading. It made me realize how bad I was and that I was wrong about Linn's gun's properties. Then, I had to play myself in order to figure out how the player did this. This technique is not well-known even on the internet, and without Naru2005, I may perfectly have never heard of it. It opens a whole new set of very efficient affordances. Finishing the game with one credit without these affordances would have been far more difficult.

    In Understanding Comics, McCloud (1993, p 63) uses the concept of "closure"; he understands it as the "phenomenon of observing the parts but perceiving the whole." Closure is what allows a reader to fill the gap between two panels in a comic or a viewer to transform the separated frames of a movie into a continuous movement. Closure also allows people to understand what is represented in a picture or to read words. It refers to the action of completing something as well as the feeling that something has been completed, or understood. So the capacity to perform closure is essential to any affordance of understanding. For example, if you can read these three sentences, you are making several closures, two of which are wrong:

    • "This is closure"
    • "Tihs is clo sure"
    • "Tihs is colsure"

    Closure may be applied to the type of learning I described but it does not bear a notion of missing something. On the contrary, the word "ellipsis," which consists of the omission of some elements, does bear the notion of omission. This omission is made by the author to allow closure from the reader. But while completing what she or he sees, a reader may also omit some elements while thinking that she or he has correctly understood everything. It is what I did on each level before the fourth level of understanding. I built a comprehension using the elements I had and thought I did understand the affordances offered by Linn's gun. Further learning proved to me that I effectively made several ellipses and then was wrong about these affordances. The phenomenon of understanding something while omitting some elements may be called "elliptical closure".

    To perform an elliptical closure, one has to give a meaning to something and think she or he has understood this phenomenon while having neglected a part of it. Raphael Koster (2004, p 12-33) considers the pattern of a situation as what we understand of it. As for him, people are "amazing pattern-matching machines" that "tend to see patterns where there aren't any." He states that our brains have the following properties:

    • The brain is good at cutting out the irrelevant
    • The brain notices a lot more than we think it does
    • The brain is actively hiding the real world from us

    These properties have an influence on the way our brain applies a pattern. We may see a pattern where there is none and we may not see elements that do not fit in the pattern we see. The properties of our brain result in our capacities to perform closure and ellipsis at the same time. Let us take the example of elliptical closure concerning the way Linn's gun works. Please consider the following figure:

    Figure 1: Linn Kurosawa and four possible targets.

    Readers may know a lot about her gun's mechanism now. But do they know what would happen if she shot in this position? If one has not played the game, or at least seen it, chances are one would not know the four targets would be touched. When Linn fires a burst of bullets, first she aims at the ground just in front of her, and then she raises her gun to touch more distant targets. This detail was omitted on purpose; if readers did not ask themselves how she actually fires, then an elliptical closure made them think they understood how shooting works with this character.

    The gun's mechanism has properties allowing elliptical closure. Such a mechanism could be called an "elliptical mechanism". It would have several levels of understanding leading to different perceptions of the affordances it offers. Each level would rely on a closure which would make the player believe she or he has understood the mechanism and an ellipsis which would make her or him ignore some parts of it. Thus, an elliptical mechanism could be understood roughly or deeply. Due to the capacity to perform elliptical closure, a rough understanding would not prevent the player from thinking that she or he has correctly understood the mechanism. Elliptical learning, resulting from elliptical closure, would be afforded by elliptical mechanisms and the player's capacity to realize an elliptical closure.

    Elliptical learning

    The study of a specific mechanism in a specific great video game led us to the concept of elliptical learning. We have seen the four levels of understanding one single mechanism may have. It may be learned quickly, but it does not require a lifetime or even years to be mastered. However, there is more than one mechanism in a video game; shooting is only one of the possible actions. The mechanisms managing movement or fighting may also be elliptical and each enemy may have an elliptical behavior. Thus they could all provide an elliptical learning. The interaction between all of them may make the game even more complex. At the same time, a rough understanding would remain fast to acquire. All these causes may explain how one can think that a game can take a minute to learn and a lifetime to master. Such a game would make the player believe she or he has learnt it quickly while still overlooking a majority of it and therefore still having much to learn.

    This changes the way we should look at great games. They do not take one minute to learn and a lifetime to master; it takes one minute for the player to believe she or he has learnt the game while it takes years to actually master everything that can be mastered. Thinking that you have mastered a game while you have not is an obstacle to learning. If a player does not think there is more to learn, she or he is not likely to look for it. Unless something shows the player how bad she or he is, further learning may not happen, especially if she or he is already able to finish the game.

    To better understand elliptical learning, the next step would be to study further both great video games and expert players. Other great games could provide some other types of elliptical mechanisms. Comparing great video games to great non-digital games would highlight the very specific properties of the digital medium affording game designers to create this type of mechanism. On the players' side, it would be interesting to study how expert players are able to break their own elliptical closure in order to truly understand a game and whether or not the video game itself may have an influence on it. These properties and these capacities could lead to the discovery of unknown affordances of digital technologies. However, whatever is found will have to be related to engagement and then validated through empirical experimentations.


    I would like to thank the reviewers for their feedback which helped me strengthen my argument and focus on the key contribution of this article.


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