Full metadata
Title
Content Agnostic Game Based Stealth Assessment
Description
Serious or educational games have been a subject of research for a long time. They usually have game mechanics, game content, and content assessment all tied together to make a specialized game intended to impart learning of the associated content to its players. While this approach is good for developing games for teaching highly specific topics, it consumes a lot of time and money. Being able to re-use the same mechanics and assessment for creating games that teach different contents would lead to a lot of savings in terms of time and money. The Content Agnostic Game Engineering (CAGE) Architecture mitigates the problem by disengaging the content from game mechanics. Moreover, the content assessment in games is often quite explicit in the way that it disturbs the flow of the players and thus hampers the learning process, as it is not integrated into the game flow. Stealth assessment helps to alleviate this problem by keeping the player engagement intact while assessing them at the same time. Integrating stealth assessment into the CAGE framework in a content-agnostic way will increase its usability and further decrease in game and assessment development time and cost. This research presents an evaluation of the learning outcomes in content-agnostic game-based assessment developed using the CAGE framework.
Date Created
2021
Contributors
- Verma, Vipin (Author)
- Craig, Scotty D (Thesis advisor)
- Bansal, Ajay (Thesis advisor)
- Amresh, Ashish (Committee member)
- Baron, Tyler (Committee member)
- Levy, Roy (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
249 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.161463
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2021
Field of study: Human Systems Engineering
System Created
- 2021-11-16 01:19:23
System Modified
- 2021-11-30 12:51:28
- 2 years 11 months ago
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