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Attention based video summaries of live online zoom classes

Lee, Hyowon orcid logoORCID: 0000-0003-4395-7702, Liu, Mingming orcid logoORCID: 0000-0002-8988-2104, Riaz, Hamza, Rajasekaran, Navaneethan, Scriney, Michael orcid logoORCID: 0000-0001-6813-2630 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2021) Attention based video summaries of live online zoom classes. In: AAAI-2021 Workshop on AI Education: "Imagining Post-COVID Education with AI" (TIPCE-2021)., 9 Feb 2021, Online (Vancouver, Canada).

Abstract
This paper describes a system developed to help University students get more from their online lectures, tutorials, laboratory and other live sessions. We do this by logging their attention levels on their laptops during live Zoom sessions and providing them with personalised video summaries of those live sessions. Using facial attention analysis software we create personalised video summaries composed of just the parts where a student's attention was below some threshold. We can also factor in other criteria into video summary generation such as parts where the student was not paying attention while others in the class were, and parts of the video that other students have replayed extensively which a given student has not. Attention and usage based video summaries of live classes are a form of personalised content, they are educational video segments recommended to highlight important parts of live sessions, useful in both topic understanding and in exam preparation. The system also allows a Professor to review the aggregated attention levels of those in a class who attended a live session and logged their attention levels. This allows her to see which parts of the live activity students were paying most, and least, attention to. The Help-Me-Watch system is deployed and in use at our University in a way that protects student's personal data, operating in a GDPR-compliant way.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:Educational analytics; video summarisation
Subjects:Computer Science > Artificial intelligence
Computer Science > Multimedia systems
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
Published in: TIPCE-2021, Proceedings. .
Official URL:https://drive.google.com/file/d/1lzeS3Z0YWGsCG-F-7...
Copyright Information:© 2021 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland under Grant Number SFI/12/RC/2289 P2, co-funded by the European Regional Development Fund, Google Cloud COVID19 Credits Program
ID Code:25395
Deposited On:18 Jan 2021 12:17 by Alan Smeaton . Last Modified 05 Jan 2022 17:30
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