An empirical investigation of the antecedents of learner-centered outcome measures in MOOCs

Eyal Rabin*, Yoram Kalman, M. Kalz

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


This research revealed the antecedes of two learner-centered outcome measures of success in massive open online courses (MOOCs): learner satisfaction and learner intention-fulfillment. Previous studies used success criteria from formal education contexts placing retention and completion rates as the ultimate outcome measures. We argue that the suggested learner-centered outcomes are more appropriate for measuring success in non-formal lifelong learning settings because they are focused on the learner’s intentions, rather than the intentions of the course developer. The behavioural measures of 125 MOOC participants who answered a pre- and a post-questionnaire were harvested. The analysis revealed that learner satisfaction was directly affected by: the importance of the MOOC’s benefits; online self-regulated learning - goal setting; number of video lectures accessed; and, perceived course usability. Age and the number of quizzes accessed indirectly effected learner satisfaction, through perceived course usability and through number of video lectures accessed. Intention-fulfillment was directly affected by: gender; the importance of the MOOC’s benefits; online self-regulated learning - goal setting; the number of quizzes accessed; the duration of participation; and, perceived course usability. Previous experience with MOOCs and the importance of MOOC’s benefits, indirectly affected intention-fulfillment through the number of quizzes accessed and perceived course usability.
Original languageEnglish
Article number14
Pages (from-to)1-20
Number of pages20
JournalInternational Journal of Educational Technology in Higher Education
Publication statusPublished - 29 Apr 2019



  • mooc
  • Perceived learning outcomes
  • Structural equation modeling
  • Student satisfaction
  • Intention-fulfilment
  • learning analytics
  • Educational data mining

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