Using course-level factors as predictors of online course outcomes: a multi-level analysis at a US urban community college
Abstract
Research has documented lower retention rates in online versus face-to-face courses. However, little research has focused on the impact of course-level characteristics (e.g. elective versus distributional versus major requirements; difficulty level; STEM status) on online course outcomes. Yet, focusing interventions at the course level versus the student level may be a more economical approach to reducing online attrition. This study used multi-level modeling, and controlled for the effects of both instructor-level and student characteristics, to measure the relationship of course-level characteristics with successful completion of online and face-to-face courses. Elective courses, and to a lesser extent distributional course requirements, were significantly more likely to have a larger gap in successful course completion rates online versus face-to-face, when compared with major course requirements. Upper level courses had better course completion rates overall, but a larger gap in online versus face-to-face course outcomes than lower level courses.
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Course type (major requirement, distributional requirement, elective) explains variation in online versus face-to-face courses.
“These categories have also been shown to explain variation in online versus face-to-face courses in prior research (Wladis et al., 2014(Wladis et al., , 2017)).”
From Competing hypotheses about online versus face-to-face course outcomes: Analysis leveraging the unique circumstances of the COVID-19 pandemic (2025) · cites this paper as Wladis et al., 2017
Cites
Bernard, R. M., Abrami, P. C., Lou, Y., Borokhovski, E., Wade, A., Wozney, L., Wallet, P. A., Fiset, M., & Huang, B. (2004) · Review of Educational Research · doi:10.3102/00346543074003379 · Cited by 1,761 · see citing works
Allen, J., Robbins, S. B., Casillas, A., & Oh, I.-S. (2008) · Research in Higher Education · doi:10.1007/s11162-008-9098-3 · Cited by 430 · see citing works
Xu, D., & Jaggars, S. S. (2011) · Educational Evaluation and Policy Analysis · doi:10.3102/0162373711413814 · Cited by 239 · see citing works
Wladis, C., Conway, K. M., & Hachey, A. C. (2015) · Community College Review · doi:10.1177/0091552115571729 · Cited by 127 · see citing works
Self-citationREAL COSTS OF NOMINAL GRADE INFLATION? NEW EVIDENCE FROM STUDENT COURSE EVALUATIONS
BABCOCK, P. (2010) · Economic Inquiry · doi:10.1111/j.1465-7295.2009.00245.x · Cited by 97 · cited 1× · see citing works
“…suggests that instructor effectiveness (Lee, Yoon, and Lee 2009; Paechter, Maier, and Macher 2010) and instructor leniency (in relation to grading) (Babcock 2010) can be factors in course selection, but we attempted to mitigate for these variables by using matched courses taught by the same…”
MethodWladis, C., Hachey, A. C., & Conway, K. M. (2015) · Community College Review · doi:10.1177/0091552114555904 · Cited by 48 · see citing works
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Salim Muljana, P., & Luo, T. (2019) · Journal of Information Technology Education: Research · doi:10.28945/4182 · Cited by 222 · see citing works
Wladis, C., Hachey, A. C., Conway, K., & Manly, C. (2025) · Online Learning · doi:10.24059/olj.v29i3.5018
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- Authors
- Wladis, C., Conway, K., & Hachey, A. C.
- Affiliations
- Borough of Manhattan Community College (US)
- Corresponding author
- Wladis, Claire
- Venue
- Studies in Higher Education
- Publisher
- Informa UK Limited
- Published
- 2015-06-09
- Volume
- 42
- Issue
- 1
- Pages
- 184-200
- ISSN
- 0307-5079 (ISSN-L)
- 1470-174X
- OpenAlex
- W1541772887
- Cited by
- 35
- References
- 6
- Citations by year
- 2026: 4 · 2025: 1 · 2024: 2 · 2023: 3 · 2022: 8 · 2021: 5 · 2020: 3 · 2019: 2 · 2018: 4 · 2017: 2 · 2014: 1
- FWCI
- 10.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Studies in Higher Education (publishedVersion)
- Funders
- psc-cuny (65541-00-43)
- Topics
- Social Sciences › Education › Online and Blended Learning
- Social Sciences › Education › Higher Education Research Studies
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- online course completion, elective courses, course difficulty, STEM courses, course level, community college students, student retention
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