An Integrated Observing Technic for Collaborative Learning: The Multimodal Learning Analytics Based on the Video Coding and EEG Data Mining

  • Shuo Feng
  • , Shuwen Wang
  • , Yufei Chen
  • , Sixu Zhang
  • , Lishan Zhang*
  • *Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Observing collaborative learning in real contexts has always been a problem because of the difficulty of representing the learning engagement, a multi-facet construct including behavior, cognition and emotion. This study adopts multimodal learning analytics to tackle it. Specifically, it is an integrated observation technic to represent it at both macro and micro levels through video coding and electroencephalogram (EEG) data mining. The analysis of a quasi-experiment was conducted to justify the feasibility. And this study also finds that learning engagement is related with the learning gain in collaborative learning.

Original languageEnglish
Title of host publicationTALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1097-1101
Number of pages5
ISBN (Electronic)9781665436878
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 - Wuhan, China
Duration: 5 Dec 20218 Dec 2021

Publication series

NameTALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings

Conference

Conference2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021
Country/TerritoryChina
CityWuhan
Period5/12/218/12/21

Keywords

  • collaborative learning
  • EEG data mining
  • multimodal learning analytics
  • video coding

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