Researching for better instructional methods using AB experiments in MOOCs: results and challenges
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41039_2016_Article_34.pdf
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Author(s)
Chen, Zhongzhou
Chudzicki, Christopher Alan
Palumbo, Daniel C.
Alexandron, Giora
Choi, Youn-Jeng
Zhou, Qian
Pritchard, David E.
Date Issued
April 2016
Journal
Research and Practice in Technology Enhanced Learning
Publisher
Springer-Verlag
Citation
Chen, Zhongzhou, Christopher Chudzicki, Daniel Palumbo, Giora Alexandron, Youn-Jeng Choi, Qian Zhou, and David E. Pritchard. “Researching for Better Instructional Methods Using AB Experiments in MOOCs: Results and Challenges.” Research and Practice in Technology Enhanced Learning. 2016 Apr 22;11(1):9.
Version
Final published version
Abstract
We conducted two AB experiments (treatment vs. control) in a massive open online course. The first experiment evaluates deliberate practice activities (DPAs) for developing problem solving expertise as measured by traditional physics problems. We find that a more interactive drag-and-drop format of DPA generates quicker learning than a multiple choice format but DPAs do not improve performance on solving traditional physics problems more than normal homework practice. The second experiment shows that a different video shooting setting can improve the fluency of the instructor which in turn improves the engagement of the students although it has no significant impact on the learning outcomes. These two cases demonstrate the potential of MOOC AB experiments as an open-ended research tool but also reveal limitations. We discuss the three most important challenges: wide student distribution, “open-book” nature of assessments, and large quantity and variety of data. We suggest possible methods to cope with those.
MIT Department
Massachusetts Institute of Technology. Department of Physics
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DOI of Published Version
https://doi.org/10.1186/s41039-016-0034-4
