Identifying the potential of danmaku video from eye gaze data

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

29 Scopus citations

Abstract

Video-based learning has gained popularity in higher education in recent years. Danmaku video is a kind of video where the screen is overlaid with user comments. In this study, the user comments consist of ideas and explanations about important concepts in the video, thus providing domain-specific knowledge and reducing the cognitive load for comprehension. This study tries to understand the effect of the danmaku video compared to with the normal video. Two groups of sophomore students (N= 20) were exposed to digital videos with or without danmaku. Both groups took part in a pre- And post-test on the topic of the given video. Time-locked eye movements were recorded to characterize participants' attention allocation to the Area of Interest (AOIs) consisting of danmaku, subtitles and teacher's face across the learning period. The results showed that danmaku video group outperformed the normal video group based on the increment of pre- And post-tests. Further, the percentage of fixation duration on each of the AOI was analyzed, and a significant difference was found in the amount of attention paid on different AOIs. The purpose of this study is focused on exploring the effects of Danmaku video in improving students' learning outcomes.

Original languageEnglish
Title of host publicationProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
EditorsJ. Michael Spector, Chin-Chung Tsai, Ronghuai Huang, Paul Resta, Demetrios G Sampson, Kinshuk, Nian-Shing Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages288-292
Number of pages5
ISBN (Electronic)9781467390415
DOIs
StatePublished - 28 Nov 2016
Event16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 - Austin, United States
Duration: 25 Jul 201628 Jul 2016

Publication series

NameProceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016

Conference

Conference16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016
Country/TerritoryUnited States
CityAustin
Period25/07/1628/07/16

Keywords

  • Danmaku video
  • Eye gaze data
  • Video-based learning

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