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This evaluation agent simulates students' behavior in Intelligent Tutoring Systems, utilizing temperamental and cognitive models to enhance educational software efficiency. By analyzing temperamental data such as user speed, certainty, and concentration along with cognitive data like knowledge level and retention capabilities, it provides valuable feedback during the design process. The agent helps detect design mistakes, ensuring a risk-free evaluation process.
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An evaluation agent that simulates students’ behavior in Intelligent Tutoring Systems Maria Virvou, Konstantinos Manos, George Katsiwnis Department of Informatics University of Piraeus
Introduction • Risk – Free Evaluation!
Evaluation Agent’s Reasoning • Purpose: Simulate a student in an ITS • Needed Material: A student’s digital image • Temperamental Model: Student’s reaction in the VR-Environment of the ITS • Cognitive Model: Student’s mental capabilities and knowledge level of the domain
Temperamental Model • The student’s behavior is related to the way s/he plays the educational game in the virtual world • In the game, one must fight one’s way through using one’s knowledge
Temperamental Data • The way a user walks around the virtual world • Familiarity with the computer • Time to answer a question (speed) • Pausing time after response (surprise) • Corrections before answer (certainty) • Unclear mouse moves (concentration) • Determination Speed + Certainty
Cognitive Model • The level of student’s knowledge • The student’s retention capabilities • Cause of error(typographic,spelling…) • Ebbinghaus Forgetting Model
Agent Agent Agent Agent Model A Model B Model C Model D Authoring Process’ Teacher VR-Integate Knowledge Base VR-Engage
Conclusions • Both Temperamental and Cognitive data are used to simulate students • Feedback for the efficiency of the educational software can be received during the design process • Students do not face possible design mistakes of the author, since these can be spotted and corrected beforehand