In the context of video-based learning, particularly active video watching, social learning is facilitated by allowing students to review comments written by their peers. In previous studies with AVW-Space, all students had access to the same comments, despite differences in their knowledge. This paper presents a study in which each student received a personalized list of comments to review, based on their student model. The results show that our intervention encouraged learners to think deeper about the comments during reviewing comments.

To learn effectively by watching videos, learners need to engage actively with video content. Writing comments on videos (also known as video annotation) is a common way of engagement in Active Video Watching (AVW). Reviewing comments on videos written by peers, as a form of social learning, has also been shown to increase learning. In this paper, we extended social learning in AVW by enabling learners to respond to comments written by their peers (rather than just reviewing peer comments) and replacing a categorical comment rating design with a numerable binary one. We investigated the impact of using such a form of comment reviewing on learning, engagement, and students' perceptions. The findings show that our intervention results in increased learning, engagement and student satisfaction compared to the situation when students could not respond to comments.

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.

Presentation skills are crucial for tertiary students and graduates but are difficult to teach. We augmented active video watching (AVW) approach with the possibility of interactions among students, and conducted an experiment with AVW- Space, an online platform which supports video-based learning. The participants watched and commented on videos first. In the second phase, the participants reviewed, rated, and responded to their peers’ comments. We found that students who interacted with other students and responded to their comments increased their conceptual understanding of presentation skills.