http://orcid.org/0000-0002-5645-9297
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ABSTRACT
Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can create challenges for understanding and adequately describing student behaviors. Utilizing automatic text analysis, this study built a hierarchical linear model that examines the influence of the pacing condition of a massive open online course (MOOC), whether it is self-paced or instructor-paced, on the demonstration of cognitive processing in a HarvardX MOOC. The analysis of 2,423 discussion posts generated by 671 students revealed the number of dictionary words used were positively associated with cognitive processing while analytical thinking and clout was negatively associated. We found that none of the student background information (gender, education), status of the course engagement (explored or completed), or the course pace (self-paced versus instructor paced) significantly influenced the cognitive processing of the postings.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Robert L. Moore is an Assistant Professor of Instructional Design & Technology at Old Dominion University. His research interests include the design and development of online learning environments and the role of analytics in exploring student engagement in these environments.
Kevin M. Oliver is a Professor of Learning Design and Technology at North Carolina State University. His research interests include online/distance learning pedagogy with implications for instructional design/policy.
Chuang Wang is a Professor of Educational Research Measurement and Evaluation at the University of North Carolina Charlotte. His research interests include multi-level modeling and educational statistics.
ORCID
Robert L. Moore http://orcid.org/0000-0002-5645-9297
Kevin M. Oliver http://orcid.org/0000-0001-8463-0621
Chuang Wang http://orcid.org/0000-0003-3372-2053