[IAEP] Webinar tonight, February 17th: Math game design framework

[Maria Droujkova]

This is a part of the Math 2.0 Interest Group series of weekly open
webinars. We will discuss a few game design books, see what game mechanics
correspond to math ideas, and look at examples of favorite (or not) math
games.

Wednesday, February 17th 2010 we will meet in the LearnCentral public
Elluminate room at 6:30pm Pacific / 9:30pm Eastern time:
https://sas.elluminate.com/d.jnlp?sid=lcevents&password=Webinar_Guest

The game subgroup <http://mathfuture.wikispaces.com/GameGroup> has been
focusing on the subject of serious games for learning mathematics since the
Fall of 2009. We are working on a conceptual framework for evaluating and
designing math games. It is based on the series of decisions in design.
Definitions of decisions come from game theory research and gaming studies.
The gameplay consequences of each decision are analyzed based on existing
games viewed through the lens of these definitions. The mathematics
education consequences of each decision are then analyzed based on the
pedagogy embodied in the gameplay, and viewed through the lens of learning
theories. A series of parallels between gaming concepts and pedagogical
notions helps mathematics educators make sense of game theory concepts, and
apply these concepts to teaching. The resulting structure makes it clear
that some types of math games are overused, and other promising types are
rarely employed by mathematics education game developers.
The decisions, as well as their mathematics and math education parallels,
are made along these dimensions that provide dichotomies, gradients or
levels:
· *Abstraction dichotomy:* narrative-based vs. abstract; situated vs.
formalized
· *Revelation gradient:* full disclosure to hidden information; open-book to
closed-book
· *Strategic gradient:* strategic to typed; problem-solving to exercises
· *Resource levels:* bounded rationality gameplay or not; level or stage
learning theories
· *Agency and autonomy gradient:* high to none; open-ended to closed-ended
tasks
· *Planning levels:* interactions, tasks, tactics, strategies; order of math
tasks
· *Depth gradient:* expert to superficial knowledge; deep learning to
expository learning
· *Goal gradient:* sandbox play to clear goals; conceptual learning to
procedural fluency

Cheers,
Maria Droujkova
http://www.naturalmath.com

Make math your own, to make your own math.
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