Analysis of learners' behaviors and learning outcomes in a massive open online course

Dong Liang*, Jiyou Jia, Xiaomeng Wu, Jingmin Miao, Aihua Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

This paper introduces a massive open online course (MOOC) on educational technology, and studies the factors that may influence learners' participation and performance in the MOOC. Students' learning records captured in the course management system and students' feedback collected from a questionnaire survey are explored. Regression analysis is adopted to examine the correlation among perceived learning experience, learning activities and learning outcomes; data mining is applied to optimize the correlation models. The findings suggest that learners' perceived usefulness rather than perceived ease of use of the MOOC, positively influences learners' use of the system, and consequentially, the learning outcome. In addition, learners' previous MOOC experience is not found to have a significant impact on their learning behavior and learning outcome in general. However, the performance of less active learners is found to be influenced by their prior MOOC experience.

Original languageEnglish
Pages (from-to)281-298
Number of pages18
JournalKnowledge Management and E-Learning
Volume6
Issue number3
Publication statusPublished - 1 Sept 2014
Externally publishedYes

Keywords

  • Data mining
  • Learning behavior
  • Learning outcome
  • MOOC
  • Perceived learning experience

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