Supporting Interactive Learning in Active Video Watching

Abstract

The potential of Active Video Watching (AVW) to train soft skills is evident. Despite considerable achievements in learning via AVW, the capacity of interactive learning has yet to be explored. This PhD research aims to investigate and support interactive learning in AVW via (a) interaction among learners, and (b) intelligent and adaptive interaction between the system and learners (comment recommendations). To this end, I initially provided learners with the possibility of responding to other learners’ comments on videos and calling attention to them by Like/Dislike rating mechanism. In the second phase, a comment recommendation engine will be developed, based on the learner model and a specific-domain ontology with respect to the target soft skill. I will also augment comment recommendations with verbal and visual explanations to increase transparency of the recommendations in hope of enhancing learners’ engagement, interactions, and learning.