Applying big data analysis technique to students' learning behavior and learning resource recommendation in a MOOCs course

Yu Sheng Su, Ting Jou Ding, Jiann Hwa Lue, Chin Feng Lai, Chiu Nan Su

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Through MOOCs and social media platforms, users can share, track, and search for the information of their specific interests. Thus, they can make interactive discussions as well as social media learning on multimedia texts and learning materials. This paper proposes a big data analysis technique on learning portfolio to explore how the interaction, unknown correlations, and hidden patterns among learners on MOOCs and social media platforms starts, and recognize the using big data analytics transforming on students' learning behavior. Therefore, the learning behavior information will be the recommendation of the analogous courses for the instructors in the future.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Applied System Innovation
Subtitle of host publicationApplied System Innovation for Modern Technology, ICASI 2017
EditorsTeen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1229-1230
Number of pages2
ISBN (Electronic)9781509048977
DOIs
Publication statusPublished - 2017 Jul 21
Event2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan
Duration: 2017 May 132017 May 17

Publication series

NameProceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017

Other

Other2017 IEEE International Conference on Applied System Innovation, ICASI 2017
CountryJapan
CitySapporo
Period17-05-1317-05-17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Mechanical Engineering
  • Media Technology
  • Health Informatics
  • Instrumentation

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