Towards Attentive, Bi-directional MOOC Learning on Mobile Devices

Abstract

AttentiveLearner is a mobile learning system optimized for consuming lecture videos in Massive Open Online Courses (MOOCs) and flipped classrooms. AttentiveLearner converts the built-in camera of mobile devices into both a tangible video control channel and an implicit heart rate sensing channel by analyzing the learner's fingertip transparency changes in real time. In this paper, we report disciplined research efforts in making AttentiveLearner truly practical in real-world use. Through two 18-participant user studies and follow-up analyses, we found that 1) the tangible video control interface is intuitive to use and efficient to operate; 2) heart rate signals implicitly captured by AttentiveLearner can be used to infer both the learner's interests and perceived confusion levels towards the corresponding learning topics; 3) AttentiveLearner can achieve significantly higher accuracy by predicting extreme personal learning events and aggregated learning events.