Intelligent Games for Education - An Intention Monitoring Approach based on Dynamic Bayesian Network

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The Eurographics Association
Computer games have become one of the preferred choices for entertainment in our society primarily because they are interactive, have appealing multimedia content, and provide an immersive and rewarding environment for players. These qualities constitute an essential psychophysical factor that inspires learning abilities and new knowledge. Despite all these promising elements, studies have shown that current educational games are not as effective as they could be. A lack of adaptive tutoring and feedback tools, lack of proper knowledge assessment, and weakly designed gameplay are the major factors for their inefficiency.We address these problems by proposing an Intelligent Tutoring System (ITS) for computer games. An important contribution of this ITS is its capability to track player intentions and award partial marks, which provides more accurate assessment than simply giving full mark to the correct result and none to an incorrect answer. Two strategies adopted in this system are Bayesian Networks based student modeling and individualized tutoring. The system can incorporate one or more games and can address one or more educational topic. The information collected from student interaction with computer games is used to update a student module that reports a student s current level of knowledge, making adaptive tutoring and assessment with computer games more effective. In order to provide an engaging and interactive environment, each game in the system has a local student module constructed based on a Dynamic Bayesian Network. We describe the design and evaluation of our ITS using a prototype implementation with several game examples. Positive evaluation results support the feasibility of the proposed system.

, booktitle = {
Eurographics 2010 - Education Papers
}, editor = {
L. Kjelldahl and G. Baronoski
}, title = {{
Intelligent Games for Education - An Intention Monitoring Approach based on Dynamic Bayesian Network
}}, author = {
Cheng, Irene
Chen, Feng
Rodrigues, Saul Daniel
Pañella, Oscar Garcia
Vicent, Lluis
Basu, Anup
}, year = {
}, publisher = {
The Eurographics Association
}, ISBN = {}, DOI = {
} }