Predicting student performance in a blended MOOC-Reference-Cited by-同舟云学术

Predicting student performance in a blended MOOC

Published:2018-05-02 Issue:5 Volume:34 Page:615-628
ISSN:0266-4909
Container-title:Journal of Computer Assisted Learning
language:en
Short-container-title:J Comput Assist Learn

Author:

Conijn R.¹²^ORCID,Van den Beemt A.²,Cuijpers P.³

Affiliation:

1. Department of Cognitive Science and Artificial Intelligence; Tilburg University; The Netherlands

2. Eindhoven School of Education; Eindhoven University of Technology; The Netherlands

3. Department of Mathematics and Computer Science; Eindhoven University of Technology; The Netherlands

Publisher

Wiley

Subject

Computer Science Applications,Education

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/jcal.12270/fullpdf

Reference48 articles.

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2. Mass attrition: An analysis of drop out from principles of microeconomics MOOC;Allione;The Journal of Economic Education,2016

3. Anderson , A. Huttenlocher , D. Kleinberg , J. Leskovec , J. 2014 Engaging with massive online courses Proceedings of the 23rd International Conference on World Wide Web

4. Comparing student success between developmental math courses offered online, blended, and face-to-face;Ashby;Journal of Interactive Online Learning,2011

5. Transforming the Measurement of Learning and Teaching in Higher Education

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