abstract: Currently, educational games are designed with the educational content as the primary factor driving the design of the game. While this may seem to be the optimal approach, this design paradigm causes multiple issues. For one, the games themselves are often not engaging as game design principles were put aside in favor of increasing the educational value of the game. The other issue is that the code base of the game is mostly or completely unusable for any other games as the game mechanics are too strongly connected to the educational content being taught. This means that the mechanics are impossible to reuse in future projects without major revisions, and starting over is often more time and cost efficient.
This thesis presents the Content Agnostic Game Engineering (CAGE) model for designing educational games. CAGE is a way to separate the educational content from the game mechanics without compromising the educational value of the game. This is done by designing mechanics that can have multiple educational contents layered on top of them which can be switched out at any time. CAGE allows games to be designed with a game design first approach which allows them to maintain higher engagement levels. In addition, since the mechanics are not tied to the educational content several different educational topics can reuse the same set of mechanics without requiring major revisions to the existing code.
Results show that CAGE greatly reduces the amount of code needed to make additional versions of educational games, and speeds up the development process. The CAGE model is also shown to not induce high levels of cognitive load, allowing for more in depth topic work than was attempted in this thesis. However, engagement was low and switching the active content does interrupt the game flow considerably. Altering the difficulty of the game in real time in response to the affective state of the player was not shown to increase engagement. Potential causes of the issues with CAGE games and potential fixes are discussed. / Dissertation/Thesis / Doctoral Dissertation Engineering 2017
| Identifer | oai:union.ndltd.org:asu.edu/item:44170 |
| Date | January 2017 |
| Contributors | Baron, Tyler John (Author), Amresh, Ashish (Advisor), Nelson, Brian C (Committee member), Niemczyk, Mary (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 232 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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