2009_Using Student Mood and Task Performance to Train Classifier Algorithms to Select Effective Coaching Strategies within Intelligent Tutoring Systems
The ultimate goal of this research was to improve student performance by adjusting an Intelligent Tutoring System’s (ITS) coaching strategy based on the student’s mood. As a step toward this goal, this study evaluated the relationships between each student’s mood variables (pleasure, arousal, dominance and mood intensity), the coaching strategy selected by the ITS and the student’s performance. Outcomes included methods to increase the perception of the intelligent tutor to allow it to adapt coaching strategies (methods of instruction) to the student’s affective needs to mitigate barriers to performance (e.g. negative affect) during the one-to-one tutoring process.
Citation: Sottilare (2009). Doctoral Dissertation: Using student mood and performance to train classifier algorithms to select effect coaching strategies with Intelligent Tutoring Systems. University of Central Florida. ISBN: 978-1-124-06561-8.