Games and Learning: The Case for the Trojan Horse PhD student Simon Egenfeldt-Nielsen 5. April 2002, Manchester Agenda : Introduction Learning games now Games: Counter-Strike & Europa Universalis Sketching a theory for game learning dynamics Introduction :
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Degree in Psychology from Copenhagen University in 2000.
PhD Student at IT-University of Copenhagen. Currently in first phase of exploring in-depth my project.
Framfab A Web agency where I was responsible for children, internet, gaming and entertainment. Placed in the department Centre for User experience.
Game Research Started to bridge the gap between arts, science and business within gaming.
I will talk about how to facilitate learning in games and what consequences it has for games.
Learning games are actually even more focused on the unfortunate tendency that game designers wish to control the universe.
Often learning is conceived in a faulty way, through the glasses of an old behaviorist-learning paradigm.
In the best cases the knowledge is part of the playing experience like in Bronkie the Bronchiasaurus, where you must fight asthma
Learning is a very important drive for humans. Psychology (Bion and Klein) operates with a basic epistemophillic desire – the thirst for knowledge.
This desire runs before fun and is a prerequisite for exploring your surroundings.
The desire to use games for learning does not stem from the fact that kids do not want to learn and have to be ‘talked into it’ through fun games. Instead it stems to derive from the fact that learning is perhaps constructed wrongly in other settings and games can offer some of the solutions for making it more lustful.
As an extension of Bateson, I try to distinguish between two different kinds of learning in relation to computer games. Bateson primarily talks about how we learn as different processes on a continuum - not what we learn
Learning proximity real life: These are elements like facts, behaviors, skills, communication, theories and language, which are closely connected with what is outside games.
Learning conceptually: These are concepts like reasoning, process, procedures, creativity and system understanding. You could call them abstractions that are not necessarily linked to real life artifacts although they mostly are in some way but they naturally exist between and across different subject areas.
The problem of Counter-Strike is not that it does not contain factual correct data, because it does for example in relation to accuracy of the weapons, uniforms and avatar movement. However, from a society point of view this is not very valuable knowledge.
The learning process above is no different than other types of learning, what is missing is a ‘curriculum’. A curriculum that the game designers are surely not able to produce without experts in different subjects.
The game primarily covers the European history from 1419 to 1820. You can choose different scenarios within this period or the grand campaign spanning the whole period. A staggering amount of different states where you must manipulate on different levels to become successful: Military, technology, economy, religion, culture, diplomacy, colonization, fleet, trade etc.
The quality of this material make it relevant for use in other contexts.
“The computer game development was drastically different from the board game….. While the board game has a deterministic view of history the philosophy for the computer game was to make historical changes possible to make a more enjoyable game.”
The combination of subject experts with game development professionals should be a goal. What sets Europa Universalis aside is that it did not set out to encompass certain aspects of history but took it as an important ingredient in the overall playing experience.
What really makes a difference is the ability to integrate learning as compelling material thereby also making possible the transfer of more factual knowledge.
An interesting project is Virtual U, which is based on the famous Simcity but is more serious. Here they have tried to put more realistic information into the simulation but still give it a game part. However, it seems quite complex and overwhelming although rather well thought out.
A parameter too often overlooked is the degree of ability to dig in.
One of the challenges of complex simulation and learning is to ease down the ambitions, so to speak – by perhaps betting more on the playability in the first ¼ of the game’s life cycle with a player and then make it necessary for him to gather knowledge in order to advance.
The games below look alike on the surface but not when you dig in they change.
Age of Empires I
Age of Empires II
What I have really been trying is to present a little documentation that the anecdotal evidence in the research literature that games increase system understanding, analysis is in fact very credible - conceptual learning but only few games produce learning proximity real life.
Games are made so they put gameplay and playing experience above simulating real life and that’s what makes it hard to take the leap from learning conceptually to learning proximity real life.
It is bound to set limits and be one more challenge in the game development that has to be solved. Furthermore, with a superficial knowledge of these things it become even harder to work creatively around the barriers.
As an encouragement you can also see that the good game universes have different layers that the players can slowly immerse into. This should be easier to do by drawing more closely on real life artifacts and especially in history. This layer approach is instead of branches which is something different. When branching you decide on different paths for the player but with layers you construct the game so factors on a deeper level can be uncovered like relations between specific units, countries or items.
Awareness of gamer
The game universe must be rich and detailed enough to provide for layers, which is often not possible if you do not include enough real life artifacts. You could use detailed fantasy worlds like Tolkien’s.
Sketch of current learning dynamics:
I believe we can identify three basic factors in making learning in games that works – furthermore, learning and knowledge share some problems:
I use story in a very pragmatic way not being a narratologist, meaning the content in the game that tells you something about the game universe context.
Scenario: Split screens environment:
Start of game part
End of game part
Start of game part
End of game part
Sketch of current learning dynamics:
Note: Could also find other models like network, but these are the most occurring
Some (new) adventure games to some degree eliminate this story problem.
Sketch for environmentnew game learning dynamics:
Instead we must use knowledge like compelling material, treat it with the same buzz as story.
Maintaining degrees of freedom both in playing, story wise and knowledge use are essential to get the full effect of game dynamics.
Happy hunting environment:
My premise is not that we need to abandon game designers and instead put in experts of learning or history but to make these groups work closer together. The subject expert serving as consultants and “filling up the head” of the designers.
So what we need to do is to relinquish the desire to take over the gaming universe in favor of our way of understanding learning. Every time someone starts to make learning stuff, he thinks of it in a quite old fashioned way.
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