This demo presents AttentiveLearner, a mobile learning system optimized for consuming lecture videos in Massive Open Online Courses (MOOCs) and flipped classrooms. AttentiveLearner uses on-lens finger gestures for video control and captures learners' physiological states through implicit heart rate tracking on unmodified mobile phones. Through three user studies to date, we found AttentiveLearner easy to learn, and intuitive to use. The heart beat waveforms captured by AttentiveLearner can be used to infer learners' cognitive states and attention. AttentiveLearner may serve as a promising supplemental feedback channel orthogonal to today's learning analytics technologies.
['Xiang Xiao', 'Phuong Pham', 'Jingtao Wang']
AttentiveLearner: Adaptive Mobile MOOC Learning via Implicit Cognitive States Inference