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Playback-centric visualizations of video usage using weighted interactions to guide where to watch in an educational context

Lee, Hyowon orcid logoORCID: 0000-0003-4395-7702, Liu, Mingming orcid logoORCID: 0000-0002-8988-2104, Scriney, Michael orcid logoORCID: 0000-0001-6813-2630 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2022) Playback-centric visualizations of video usage using weighted interactions to guide where to watch in an educational context. Frontiers in Education . ISSN 2504-284X

Abstract
The steady increase in use of online educational tools and services has led to a large amount of educational video materials made available for students to watch. Finding the right video content is usually supported by the overarching learning management system and its user interface that organizes various video items by course, categories and weeks, and makes them searchable. However, once a wanted video is found, students are often left without further guidance as to what parts in that video they should focus on. In this article, an additional timeline visualization to augment the conventional playback timeline is introduced which employs a novel playback weighting strategy in which the history of different video interactions generate scores based on the context of each playback. This includes whether the playback started after jumping forward or backward in the video, whether the playback was at a faster or slower speed, and whether the playback window was in focus on the student’s screen or was in the background. The resultant scores are presented on the additional timeline, making it in effect a playback-centric usage graph nuanced by how each playback was executed. Students are informed by this visualization on the playback by their peers and can selectively watch those portions which the contour of the usage visualization suggests. The visualization was implemented as a fully-fledged web application and deployed in an undergraduate course at a university for two full semesters. A total of 270 students used the system throughout both semesters watching 52 videos, guided by visualizations on what to watch. Analysis of playback logs revealed that students selectively watched portions in videos corresponding to the most important portions of the videos as assessed by the instructor who created the videos. The characteristics of this method as a way of guiding students as to where to watch as well as a complementary tool for playback analysis, are discussed. Further insights into the potential values of this visualization and its underlying playback weighting strategy are also discussed.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:learning analytics; online learning; educational video; interaction logging; system deployment
Subjects:Computer Science > Algorithms
Computer Science > Information retrieval
Computer Science > Information technology
Computer Science > Interactive computer systems
Computer Science > Visualization
Computer Science > World Wide Web
Engineering > Systems engineering
Social Sciences > Educational technology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Publisher:Frontiers
Official URL:https://dx.doi.org/10.3389/feduc.2022.733646
Copyright Information:© 2022 The Authors.
Funders:Science Foundation Ireland Grant Number SFI/12/RC/2289 P2, co-funded by the European Regional Development Fund, Google Cloud COVID-19 Credits Program
ID Code:27390
Deposited On:26 Jul 2022 14:52 by Hyowon Lee . Last Modified 14 Mar 2023 15:07
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