Affective e-Learning in residential and pervasive computing environments

Abstract

This article examines how emerging pervasive computing and affective computing technologies might enhance the adoption of ICT in e-Learning which takes place in the home and wider city environment. In support of this vision we describe two cutting edge ICT environments which combine to form a holistic connected future learning environment. The first is the iSpace, a specialized digital-home test-bed that represents the kind of high-tech, context aware home-based learning environment we envisage future learners using, the second a sophisticated pervasive e-Learning platform that typifies the educational delivery platform our research is targeting. After describing these environments we then present our research that explores how emotion evolves during the learning process and how to leverage emotion feedback to provide adaptive e-Learning system. The motivation driving this work is our desire to improve the performance of the educational experience by developing learning systems that recognize and respond appropriately to emotions exhibited by learners. Finally we report on the results about the emotion recognition from physiological signals which achieved a best-case accuracy rate of 86.5% for four types of learning emotion. To the best of our knowledge, this is the first report on emotion detection by data collected from close-to-real-world learning sessions. We also report some finding about emotion evolution during learning, which are still not enough to validate Kort's learning spiral model.