This research study examines the influence of the pacing condition of massive open online courses (MOOCs), be they self-paced or instructor-paced, on the demonstration of cognitive presence in such courses. The research is informed by the Community of Inquiry (CoI) model of Garrison, Anderson, and Archer (2001), a framework that identifies three domains—social, teaching, and cognitive presence—that are necessary for online learning. This study utilizes an embedded multiple-case research design to allow a thorough understanding of the area of interest, specifically, cognitive presence in MOOCs. The selected cases are three MOOCs offered by Harvard University. Each one was offered in both instructor- and self-paced pacing conditions, for a total of six courses under review in this study. The analysis of the log files and discussion forums for each of these courses presents an opportunity to explore similarities and differences in learner engagement. This study analyzed 57,650 discussion posts generated by 13,495 students across these six courses. The analysis of discussion forums within MOOCs presents many logistical challenges, resulting chiefly from the size of the datasets involved. This study explores ways in which automatic text analysis tools can be used to aid in the analysis and subsequent identification of evidence of cognitive presence in MOOCs.
|School:||North Carolina State University|
|Department:||Curriculum and Instruction|
|School Location:||United States -- North Carolina|
|Source:||DAI-A 80/01(E), Dissertation Abstracts International|
|Subjects:||Instructional Design, Adult education, Educational technology|
|Keywords:||Community of inquiry, Discussion forums, Educational data mining, Learning analytics, Massive open online courses, Moocs|
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