Leveraging smartwatches to estimate students' perceived difficulty and interest in online video lectures

Jinhan Choi, Jeongyun Han, Woochang Hyun, Hyunchul Lim, Sun Young Huh, So Hyun Park, Bongwon Suh

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

4 Scopus citations

Abstract

Online videos have become a popular medium for delivering educational materials. Analyzing video interaction log can provide valuable educational insights. However, for small-sized online courses, due to the small size of samples, analyzing online log is often not enough for modeling students' learning behaviors. In this study, we aim to explore the feasibility of utilizing commercial smartwatches to augment building of such models. We collected online video interaction log as well as physiological data from smartwatches and built models to estimate the perceived difficulty and interest of students while watching online video lectures. The results show that smartwatch data could significantly improve the amount of explained variance in their perceived difficulty and interest by 100% and 64% respectively. We hope the result could inform the application of a smartwatch for students' in online video learning.

Original languageEnglish
Title of host publicationProceedings of the 2019 11th International Conference on Education Technology and Computers, ICETC 2019
PublisherAssociation for Computing Machinery
Pages171-175
Number of pages5
ISBN (Electronic)9781450372541
DOIs
StatePublished - 28 Oct 2019
Event11th International Conference on Education Technology and Computers, ICETC 2019 - Amsterdam, Netherlands
Duration: 28 Oct 201931 Oct 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Conference on Education Technology and Computers, ICETC 2019
Country/TerritoryNetherlands
CityAmsterdam
Period28/10/1931/10/19

Keywords

  • Cognitive state inference
  • Perceived difficulty
  • Perceived interest
  • Smartwatch data
  • Video activity data

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