Taken Together: Conceptualizing Students’ Concurrent Course Enrollment across the Post-Secondary Curriculum using temporal analytics

Supplemental Files
Brown, Michael
DeMonbrun, R. Matthew
Teasley, Stephanie
Journal Title
Journal ISSN
Volume Title
Research Projects
Organizational Units
School of Education
Organizational Unit
Journal Issue

In this study, we develop and test four measures for conceptualizing the potential impact of co-enrollment in different courses on students’ changing risk for academic difficulty and recovery from academic difficulty in a focal course. We offer four predictors, two related to instructional complexity and two related to structural complexity (the organization of the curriculum) that highlight different trends in student experience of the focal course. Course difficulty, discipline of major, time in semester, and simultaneous difficulty across courses were all significantly related to entering a moderate and high-risk classification in the early warning system (EWS). Course difficulty, discipline of major, and time in semester were related to exiting academic difficulty classifications. We observe a snowball effect, whereby students who are experiencing difficulty in the focal course are at increased risk of experiencing difficulty in their other courses. Our findings suggest that different metrics may be needed to identify risk for academic difficulty and recovery from academic difficulty. Our results demonstrate what a more holistic assessment of academic functioning might look like in early warning systems and course recommender systems, and suggest that academic planners consider the relationship between course co-enrollment and student academic success.


This article is published as Brown, M.G, DeMonbrun, R., and Teasley, S. Taken Together: Conceptualizing students concurrent course enrollment across the postsecondary curriculum using temporal analytics. Journal of Learning Analytics 5 (2018): 60-72. doi: 10.18608/jla.2018.53.5.

Educational technology, curriculum analytics, survival analysis, early warning systems, undergraduate education