Success Rate Disparities Between Online and On-campus Economics Courses

The Roles of Campus Affiliation, Student Characteristics, and Course Level

Authors

DOI:

https://doi.org/10.24059/olj.v27i4.3447

Keywords:

online learning, economics, success gaps, higher education, community

Abstract

Students enrolled in online courses tend to be less successful as measured by the rate of A’s, B’s, and C’s than students enrolled in face-to-face courses. Yet little work has been done addressing whether these gaps vary depending on students’ broader relationship with the university, including whether they are degree-seeking students and whether they take any face-to-face courses. We use institutional data on Economics enrollments between 2012 and 2018 at a mid-sized land-grant university to deconstruct online/face-to-face success gaps into a student’s term modality (or modalities) and institutional affiliation components. We identify these components by using a fixed effects regression methodology and comparing outcomes across four student groups: affiliated students who are enrolled in exclusively online courses, exclusively face-to-face courses, or in a mix of courses each term, as well as unaffiliated (external) students exclusively taking online courses. Although students in online courses are less successful on average, part of this gap is explained by the student’s institutional affiliation and whether they exclusively take online courses. External students are the least successful in online courses while students who are affiliated with the institution fare much better. We examine potential reasons for these patterns using survey data from several online courses. These findings suggest that institutions should take steps to ensure that institutional support services and activities exist and extend to students in online courses.

Author Biographies

Melanie G. Long, The College of Wooster

Assistant Professor of Economics and Business Economics

Karen Gebhardt, University of Colorado Boulder

Director of the Online Economics Program in the Department of Economics

Kelly McKenna, Colorado State University

Associate Professor in the School of Education

Associate Director of the Center for the Analytics of Learning and Teaching

References

Andrade, M. S. (2015). Teaching online: A theory-based approach to student success. Journal of Education and Training Studies, 3(5), 1-9. http://dx.doi.org/10.11114/jets.v3i5.904

Aragon, S. R., & Johnson, E. S. (2008). Factors influencing completion and noncompletion of community college online courses. The American Journal of Distance Education, 22(3), 146-158. https://doi.org/10.1080/08923640802239962

Artino, A. R. (2007). Self-regulated learning in online education: A review of the empirical literature. International Journal of Instructional Technology and Distance Learning, 4(6). http://www.itdl.org/Journal/Jun_07/article01.htm

Boston, W.E., & Ice, P. (2011). Assessing retention in online learning: An administrative perspective. Online Journal of Distance Learning Administration, 14(2). https://www.learntechlib.org/p/52638/

Broadbent, J.,& Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1-13. https://doi.org/10.1016/j.iheduc.2015.04.007

Cochran, J. D., Campbell, S. M., Baker, H. M., & Leeds, E. M. (2014). The role of student characteristics in predicting retention in online courses. Research in Higher Education, 55(1), 27-48. https://doi.org/10.1007/s11162-013-9305-8

Denny, E. (2014). Factors influencing the performance of non-economics majors in an introductory economics course. International Review of Economics Education, 17, 1-16. https://doi.org/10.1016/j.iree.2014.04.003

DeTure, M. (2004). Cognitive style and self-efficacy: Predicting student success in online distance education. American Journal of Distance Education, 18(1), 21-38. https://doi.org/10.1207/s15389286ajde1801_3

Dupin-Bryant, P. A. (2004). Pre-entry variables related to retention in online distance education. The American Journal of Distance Education, 18(4), 199-206. https://doi.org/10.1207/s15389286ajde1804_2

Edwards, L. (2000). An econometric evaluation of academic development programmes in economics. South African Journal of Economics, 68(3), 204-215. https://doi.org/10.1111/j.1813-6982.2000.tb01178.x

Euzent, P., Martin, T., Moskal, P., Moskal, P. D. (2011). Assessig student performance and perceptions in lecture capture vs. face-to-face course delivery. Journal of Information Technology Education: Research, 10(1), 295-307. https://www.learntechlib.org/p/111523/

Fendler, R. J., Ruff, C., and Shrikhande, M. M. (2018). No significant difference – unless you are a jumper. Online Learning, 22(1), 39-60. https://doi.org/10.24059/olj.v22i1.887

Fritz, J. (2017). Using analytics to nudge student responsibility for learning. New Directions for Higher Education, Fall(179), 65-74. https://doi.org/10.1002/he.20244

Gebhardt, K., & McKenna, K. N. (2019). A messaging framework for online educators. eLearn Magazine, May, n.p. https://doi.org/10.1145/3331175

Grant, M. R., & Heather R. Thornton. (2007). Best practices in undergraduate adult centered online learning: mechanisms for course design and delivery. Journal of Online Learning and Teaching, 3(4), 346-356. https://jolt.merlot.org/vol3no4/grant.htm

Gratton-Lavoie, C., & Stanley, D. (2009). Teaching and learning principles of microeconomics online: An empirical assessment. The Journal of Economic Education, 40(1), 3-25. https://doi.org/10.3200/JECE.40.1.003-025

Greenland, S. J., & Moore, C. (2014). Patterns of online student enrolment and attrition in Australian open access online education: a preliminary case study. Open Praxis, 6(1), 45-54. https://search.informit.org/doi/abs/10.3316/INFORMIT.935906696497074

Hachey, A. C., Wladis, C. W., & Conway, K. M. (2013). Balancing retention and access in online courses: Restricting enrollment… Is it worth the cost? Journal of College Student Retention: Research, Theory & Practice, 15(1), 9-36. https://doi.org/10.2190%2FCS.15.1.b

Halsne, A. M. Gatta., LA (2002). Online versus traditionally-delivered instruction: A descriptive study of learner characteristics in a community college setting. Online Journal of Distance Learning Administration, 5(1), 1-14. https://www.learntechlib.org/p/92518/

Horspool, A., & Lange, C. (2012). Applying the scholarship of teaching and learning: student perceptions, behaviours and success online and face-to-face. Assessment & Evaluation in Higher Education, 37(1), 73-88. https://doi.org/10.1080/02602938.2010.496532

Johnson, D., & Palmer, C. C. (2015). Comparing student assessments and perceptions of online and face-to-face versions of an introductory linguistics course. Online Learning, 19(2). https://eric.ed.gov/?id=EJ1062936

Johnson, N. (2012). The Institutional Costs of Student Attrition. Research Paper. Delta Cost Project at American Institutes for Research. https://eric.ed.gov/?id=ED536126

Lundberg, S., & Stearns, J. (2019). Women in economics: Stalled progress. Journal of Economic Perspectives, 33(1), 3-22. https://doi.org/10.1257/jep.33.1.3

Kaiser, L. M. R., & McKenna, K. (2021). COVID-19 and the shift to remote education: Opportunity and obligation for adult educators. Adult Learning, 32(4), 181-183. https://doi.org/10.1177%2F1045159520984547

McKenna, K., Gebhardt, K., & Altringer, L. (2019). Exploring community in discussion board activities. The Online Journal of Distance Education and e-Learning, 7(3), 185-198. https://www.tojdel.net/journals/tojdel/articles/v07i03/v07i03-04.pdf

McKenna, K., Altringer, L., Gebhardt, K., & Long, M. G. (2022). Promoting meaningful interaction and community development through discussion board activities in the online classroom. The Journal of Educators Online, 19(1), n.p. https://www.thejeo.com/archive/archive/2022_191/mckenna_altringer_gebhardt__longpdf

Morris, L. V., Finnegan, C., & Wu, S. (2005). Tracking student behavior, persistence, and achievement in online courses. The Internet and Higher Education, 8(3), 221-231.

Nicol, D. J., & Macfarlane‐Dick, D. (2006). Formative assessment and self‐regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199-218. https://doi.org/10.1080/03075070600572090

North, S. (2016). Examining self-regulated learning in an asynchronous, online course: A qualitative study. In E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 757-763. Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/p/174004/

Palvia, S., Aeron, P., Gupta, P., Mahapatra, D., Parida, R., Postner, R., & Sindhi, S. (2018). Online education: Worldwide status, challenges, trends, and implications. Journal of Global Information Technology Management, 21(4), 233-241. https://doi.org/10.1080/1097198X.2018.1542262

Patterson, B., & McFadden, C. (2009). Attrition in online and campus degree programs. Online Journal of Distance Learning Administration, 12(2), 1-8. https://www.learntechlib.org/p/76592/

Rovai, A. A. P. (2002). A preliminary look at the structural differences of higher education classroom communities in traditional and ALN courses. Journal of Asynchronous Learning Networks, 6(1), 41-56. https://olj.onlinelearningconsortium.org/index.php/olj/article/view/1871

Schaeffer, C. E., & Konetes, G. D. (2010). Impact of learner engagement on attrition rates and student success in online learning. International Journal of Instructional Technology & Distance Learning, 7(5), n.p. http://itdl.org/Journal/May_10/article01.htm

Shelton, B., Hung, J., & Lowenthal, P. R. (2017). Predicting student success by modeling student interaction in asynchronous online courses. Distance Education, 38(1), 59-69. https://doi.org/10.1080/01587919.2017.1299562

Stock, W. A., Ward, K., Folsom, J., Borrenpohl, T., Mumford, S., Pershin, Z., Carriere, D., and Smart, H. (2013). Cheap and effective: The impact of student-led recitation classes on learning outcomes in introductory economics. The Journal of Economic Education, 44(1), 1-16. https://doi.org/10.1080/00220485.2013.740368

Williams, R. L. (2000). A note on robust variance estimation for cluster‐correlated data. Biometrics, 56(2), 645-646. https://doi.org/10.1111/j.0006-341X.2000.00645.x

Wladis, C., Conway, K., & Hachey, A. C. (2017). Using course-level factors as predictors of online course outcomes: a multi-level analysis at a US urban community college. Studies in Higher Education, 42(1), 184-200. https://doi.org/10.1080/03075079.2015.1045478

Xu, D., & Xu, Y. (2019). The promises and limits of online higher education: Understanding how distance education affects access, cost, and quality. Washington, D.C.: American Enterprise Institute. https://eric.ed.gov/?id=ED596296

Zhan, Z., & Mei, H. (2013). Academic self-concept and social presence in face-to-face and online learning: Perceptions and effects on students' learning achievement and satisfaction across environments. Computers & Education, 69: 131-138. https://doi.org/10.1016/j.compedu.2013.07.002

Downloads

Published

2023-12-01

Issue

Section

Section II