Usage-based Summaries of Learning Videos
Hyowon Lee, Mingming Liu, Michael Scriney, Alan F. Smeaton

TL;DR
This paper introduces a system that analyzes student playback data of educational videos to generate usage-based summaries, helping students identify important segments for revision.
Contribution
The paper presents a novel method for scoring and visualizing video segments based on collective student playback behavior, aiding in efficient revision.
Findings
Effective identification of popular video segments
Enhanced revision efficiency for students
GDPR-compliant anonymized data collection
Abstract
Much of the delivery of University education is now by synchronous or asynchronous video. For students, one of the challenges is managing the sheer volume of such video material as video presentations of taught material are difficult to abbreviate and summarise because they do not have highlights which stand out. Apart from video bookmarks there are no tools available to determine which parts of video content should be replayed at revision time or just before examinations. We have developed and deployed a digital library for managing video learning material which has many dozens of hours of short-form video content from a range of taught courses for hundreds of students at undergraduate level. Through a web browser we allow students to access and play these videos and we log their anonymised playback usage. From these logs we score to each segment of each video based on the amount of…
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