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Erica L. Snow; Maria Ofelia Z. San Pedro; Matthew Jacovina; Danielle S. McNamara; Ryan S. Baker – Grantee Submission, 2015
This study investigates how we can effectively predict what type of game a user will choose within the game-based environment iSTART-2. Seventy-seven college students interacted freely with the system for approximately 2 hours. Two models (a baseline and a full model) are compared that include as features the type of games played, previous game…
Descriptors: Game Based Learning, Decision Making, Prediction, Student Attitudes
Erica L. Snow; Danielle S. McNamara; Matthew E. Jacovina; Laura K. Allen; Amy M. Johnson; Cecile A. Perret – Grantee Submission, 2014
Metacognitive awareness has been shown to be a critical skill for academic success. However, students often struggle to regulate this ability during learning tasks. The current study investigates how features designed to promote metacognitive awareness can be built into the game-based intelligent tutoring system (ITS) iSTART-2. College students…
Descriptors: Educational Technology, Intelligent Tutoring Systems, Game Based Learning, College Students
Erica L. Snow; Mathew E. Jacovina; Laura K. Allen; Jianmin Dai; Danielle S. McNamara – Grantee Submission, 2014
This study investigates variations in how users exert agency and control over their choice patterns within the game-based ITS, iSTART-2, and how these individual differences relate to performance. Seventy-six college students interacted freely with iSTART-2 for approximately 2 hours. The current work captures and classifies variations in students'…
Descriptors: Personal Autonomy, College Students, Individual Differences, Game Based Learning

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