Data-assisted instructional video revision via course-level exploratory video retention analysis

Chi Un Lei, Donn Gonda, Xiangyu Hou, Elizabeth Oh, Xinyu Qi, Tyrone T.O. Kwok, Yip Chun Au Yeung, Ray Lau

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Since teachers are not physically present in an online class, instructional video is the major carrier of course contents in an online learning environment. This paper aims to investigate how course-level exploratory video retention analysis can be used for identifying moments with abnormal watching behaviors and revising videos for a higher video retention. We have empirically evaluated the effectiveness of video analysis and revisions, based on evaluating retentions of revised videos.

Original languageEnglish
Title of host publicationLAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference
Subtitle of host publicationUnderstanding, Informing and Improving Learning with Data
Pages554-555
Number of pages2
ISBN (Electronic)9781450348706
DOIs
Publication statusPublished - 13 Mar 2017
Externally publishedYes
Event7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, Canada
Duration: 13 Mar 201717 Mar 2017

Publication series

NameACM International Conference Proceeding Series

Conference

Conference7th International Conference on Learning Analytics and Knowledge, LAK 2017
Country/TerritoryCanada
CityVancouver
Period13/03/1717/03/17

Keywords

  • Data-informed revision
  • Exploratory analysis
  • Video retention

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