Document Type
Article
Publication Date
2019
DOI
10.1080/10494820.2019.1610453
Publication Title
Interactive Learning Environments
Volume
27
Issue
5-6
Pages
655-669
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.
Original Publication Citation
Moore, R. L., Oliver, K. M., & Wang, C. (2019). Setting the pace: Examining cognitive processing in MOOC discussion forums with automatic text analysis. Interactive Learning Environments, 27(5-6), 655-669. doi:10.1080/10494820.2019.1610453
ORCID
0000-0002-5645-9297 (Moore)
Repository Citation
Moore, Robert L.; Oliver, Kevin M.; and Wang, Chuang, "Setting The Pace: Examining Cognitive Processing in MOOC Discussion Forums With Automatic Text Analysis" (2019). STEMPS Faculty Publications. 110.
https://digitalcommons.odu.edu/stemps_fac_pubs/110
Included in
Educational Assessment, Evaluation, and Research Commons, Educational Psychology Commons, Educational Technology Commons
Comments
This article has been accepted for publication in Interactive Learning Environments, published by Taylor & Francis.
This is an original manuscript/preprint of an article published by Taylor & Francis in Interactive Learning Environments on April 30, 2019, available online:
http://www.tandfonline.com/10.1080/10494820.2019.1610453.