Application of data mining in MOOCs for developing vocational education: A review and future research directions

Jianzhen Zhang, Jia Tina Du, Fang Xu

Research output: Contribution to journalArticlepeer-review

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Abstract

minent developments in education, which brings new opportunities for higher and vocational education. This paper presented an in-deep literature review on the application of data mining in MOOCs. We found there are 8 types of behavior data mainly researched by the existing publications, and then classified the main application of the data mining in MOOCs into 7 directions. However, there is as yet little evidence on the application of data mining on MOOCs for developing vocational education. Based upon the review findings, we presented 3 recommendations, including applying cluster to find the effective marketing area for vocational education organizations, applying association analysis to figure out vocational education course sets for the specific profession, and applying regression analysis to recommend the personalized career planning for candidates. This article can be useful for vocational institutes and MOOCs platforms to develop learner-centered strategies.
Original languageEnglish
Pages (from-to)411-417
Number of pages7
JournalInternational Journal of Information and Education Technology
Volume8
Issue number6
DOIs
Publication statusPublished - Jun 2018

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