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Characteristics and Learning Behavior of Active Learners on SWU-MOOC

Published: 03 May 2020 Publication History

Abstract

In 2017, the SWU-MOOC project began from the collaboration between Srinakharinwirot University and Thai cyber University project to developing 10 courses on innovation and technology. There are over 3,000 enrolled students, with more than 40% of students completing the course. This research aimed at analyzing characteristics and learning behavior of active learners on SWU-MOOC. The sample involved 773 active learners who filled the questionnaires after completing the course. The data was analyzed using percentage. The findings were as follow: (1) most of the active learners' characteristics in gender ranged from 64.94% for female students, Occupation ranged from 63.26% for University students, and age ranged from 60.28% for 18-24 years. (2) Learning behavior in terms of frequency in attending SWU-MOOC took 2-3 times per week (42.82%) and in terms of length of study per time, 30-60 minutes (25.61%) of spent time had the highest percentage.

References

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  • (2024)Enhancing digital competence through story-based learning: a massive open online course (MOOC) approachJournal of Research in Innovative Teaching & Learning10.1108/JRIT-04-2024-0091Online publication date: 19-Nov-2024
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  • (2021)Interaction recognition and intervention based on context feature fusion of learning behaviors in interactive learning environmentsInteractive Learning Environments10.1080/10494820.2021.187163231:4(2033-2050)Online publication date: 17-Jan-2021
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  1. Characteristics and Learning Behavior of Active Learners on SWU-MOOC

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      cover image ACM Other conferences
      IC4E '20: Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning
      January 2020
      441 pages
      ISBN:9781450372947
      DOI:10.1145/3377571
      © 2020 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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      • Ritsumeikan University: Ritsumeikan University

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      Published: 03 May 2020

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      Author Tags

      1. E-learning
      2. Moocs
      3. Online Characteristics
      4. Online Learner's Behavior
      5. Thaimooc

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      Cited By

      View all
      • (2024)Enhancing digital competence through story-based learning: a massive open online course (MOOC) approachJournal of Research in Innovative Teaching & Learning10.1108/JRIT-04-2024-0091Online publication date: 19-Nov-2024
      • (2021)Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic RepresentationsFrontiers in Research Metrics and Analytics10.3389/frma.2021.6739286Online publication date: 2-Aug-2021
      • (2021)Interaction recognition and intervention based on context feature fusion of learning behaviors in interactive learning environmentsInteractive Learning Environments10.1080/10494820.2021.187163231:4(2033-2050)Online publication date: 17-Jan-2021
      • (2020)Random field design and collaborative inference strategies for learning interaction activitiesInteractive Learning Environments10.1080/10494820.2020.186323631:4(1933-1957)Online publication date: 30-Dec-2020

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