National Evidence of the Impact of First-Year Online Enrollment on Postsecondary Students’ Long-Term Academic Outcomes

Abstract

This study examines the influence of first-year online enrollment on the long-term academic outcomes of postsecondary students. Using a nationally representative sample and propensity score weighting, I find that enrolling in some online courses is associated with lower odds of dropping out of college. Additional results reveal a positive relationship between enrolling in some online courses and sub-baccalaureate indicators of long-term academic success, such as earning an associate’s degree and transferring from a community college to a 4-year institution.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Notes

  1. 1.

    “Some online courses” will be used throughout the paper; it suggests that students took at least one, but not all, of their courses online.

  2. 2.

    This meta-analysis has received criticism for the following reasons: the majority of studies included in the meta-analysis had a sample size of fewer than 100 students, only half of the students were taking the course(s) for credit, and only 7 of the 45 studies included in the meta-analysis examined postsecondary students enrolled in semester-long online courses, which limits the generalizability of its conclusions for the majority of higher education institution offering online courses.

  3. 3.

    This term can be used to describe the successful transfer from a community college to a 4-year institution.

  4. 4.

    Previous work has suggested that students enrolled in hybrid courses achieve the same (Bowen et al. 2014) or greater (Means et al. 2013) academic outcomes when compared to their peers enrolled in face-to-face courses.

  5. 5.

    Missing SAT scores and high school GPAs were imputed by applying a multiple imputation method with 20 iterations to impute the missing values for both variables before generating the propensity scores. The majority of respondents who were missing these values were enrolled at a 2-year institution during their first year.

  6. 6.

    I ran additional specifications to examine the concentrated influence of online enrollment on bachelor’s degree attainment at public 4-year institutions relative to private 4-year institutions, but the results were not statistically significant.

References

  1. Adelman, C. (1999). Answers in the tool box: Academic intensity, attendance patterns, and bachelor’s degree attainment. United States Department of Education.

  2. Adelman, C. (2004). Principal indicators of student academic histories in postsecondary education. United States Department of Education.

  3. Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. United States Department of Education.

  4. Allen, E. & Seaman, J. (2014). Grade change: Tracking online education in the United States. The Sloan Consortium.

  5. American Federation of Teachers. (2003). Student persistence in college: More than counting caps and gowns. Washington, DC: American Federation of Teachers.

    Google Scholar 

  6. Ary, E., & Brune, C. (2011). A comparison of student learning outcomes in traditional and online personal finance courses. MERLOT Journal of Online Learning and Teaching, 7(4), 465–474.

    Google Scholar 

  7. Bean, J., & Metzner, B. (1985). A conceptual model of nontraditional undergraduate student attrition. Review of Educational Research, 55, 485–650.

    Article  Google Scholar 

  8. Bowen, W. (2013). Higher education in the digital age. Princeton, NJ: Princeton University Press.

    Book  Google Scholar 

  9. Bowen, W. G., Chingos, M. M., Lack, K. A., & Nygren, T. I. (2014). Interactive learning online at public universities: Evidence from a six-campus randomized trial. Journal of Policy Analysis and Management, 33(1), 94–111.

    Article  Google Scholar 

  10. Cejda, B. D., & Kaylor, A. J. (2001). Early transfer: A case study of traditional-aged community college students. Community College Journal of Research & Practice, 25(8), 621–638.

    Article  Google Scholar 

  11. Chen, P. S. D., Lambert, A. D., & Guidry, K. R. (2010). Engaging online learners: The impact of Web-based learning technology on college student engagement. Computers & Education, 54(4), 1222–1232.

    Article  Google Scholar 

  12. Cheslock, J., Ortagus, J., Umbricht, M., & Wymore, J. (2016). The cost of producing higher education: An exploration of theory, evidence, and institutional policy. In J. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 31). Dordrecht: Springer.

    Google Scholar 

  13. Daymont, T., & Blau, G. (2008). Student performance in online and traditional sections of an undergraduate management course. Journal of Behavioral and Applied Management, 9(3), 275.

    Google Scholar 

  14. Deming, D. J., Goldin, C., Katz, L. F., & Yuchtman, N. (2015). Can online learning bend the higher education cost curve? The American Economic Review, 105(5), 496–501.

    Article  Google Scholar 

  15. Dougherty, K. J. (2002). The evolving role of the community college: Policy issues and research questions. In J. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 17). Dordrecht: Springer.

    Google Scholar 

  16. Driscoll, A., Jicha, K., Hunt, A., Tichavsky, L., & Thompson, G. (2012). Can online courses deliver in-class results? A comparison of student performance and satisfaction in an online versus a face-to-face introductory sociology course. Teaching Sociology, 40(4), 312–331.

    Article  Google Scholar 

  17. DuGoff, E. H., Schuler, M., & Stuart, E. A. (2014). Generalizing observational study results: Applying propensity score methods to complex surveys. Health Services Research, 49(1), 284–303.

    Article  Google Scholar 

  18. Enriquez, A. (2010) Assessing the effectiveness of synchronous content delivery in an online introductory circuits analysis course. In Proceedings from the annual conference of the American Society for Engineering Education, Louisville, Kentucky.

  19. Figlio, D., Rush, M., & Lu, Y. (2013). Is it live or is it internet? Experimental estimates of the effects of online instruction on student learning. Journal of Labor Economics, 31(4), 763–784.

    Article  Google Scholar 

  20. Flores, S. M., & Park, T. J. (2015). The effect of enrolling in a minority-serving institution for Black and Hispanic students in Texas. Research in Higher Education, 56(3), 247–276.

    Article  Google Scholar 

  21. Fonte, R. (2011). The community college alternative. Academic Questions, 24(4), 419–428.

    Article  Google Scholar 

  22. Gonzalez, A., & Hilmer, M. J. (2006). The role of 2-year colleges in the improving situation of Hispanic postsecondary education. Economic of Education Review, 25(3), 249–257.

    Article  Google Scholar 

  23. Guo, S., & Fraser, M. (2015). Propensity score analysis: Statistical methods and applications (2nd ed.). Thousand Oaks, CA: SAGE Publications.

    Google Scholar 

  24. Hagedorn, L. S., Cypers, S., & Lester, J. (2008). Looking in the review mirror: Factors affecting transfer for urban community college students. Community College Journal of Research and Practice, 32, 643–664.

    Article  Google Scholar 

  25. Jaggars, S. S. (2014). Choosing between online and face-to-face courses: Community college student voices. American Journal of Distance Education, 28(1), 27–38.

    Article  Google Scholar 

  26. Jaggars, S. S., & Xu, D. (2010). Online Learning in the Virginia Community College System. Community College Research Center, Columbia University.

  27. Jenkins, D., & Fink, J. (2016). Tracking transfer: New measures of institutional and state effectiveness in helping community college students attain bachelor’s degrees. Community College Research Center, Columbia University.

  28. Lack, K. (2013). Current status of research on online learning in postsecondary education. Ithaka S-R.

  29. Lewis, J., & Harrison, M. (2012). Online delivery as a course adjunct promotes active learning and student success. Teaching of Psychology, 39(1), 72–76.

    Article  Google Scholar 

  30. Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115, 1–47.

    Google Scholar 

  31. Mentzer, G., Cryan, J., & Teclehaimanot, B. (2007). Two peas in a pod? A comparison of face- to-face and web-based classrooms. Journal of Technology and Teacher Education, 15(2), 233–246.

    Google Scholar 

  32. Meyer, K. A. (2006). Cost-efficiencies in online learning. ASHE Higher Education Report, Volume 32, Number 1. ASHE Higher Education Report, 32(1), 1–123.

    Article  Google Scholar 

  33. Olson, T., & Wisher, R. (2002). The effectiveness of web-based instruction: An initial inquiry. The International Review of Research in Open and Distance Learning, 3(2).

  34. Ortagus, J. (2017). From the periphery to prominence: An examination of the changing profile of online students in American higher education. The Internet and Higher Education, 32, 47–57.

    Article  Google Scholar 

  35. Poirier, C., & Feldman, R. (2004). Teaching in cyberspace: Online versus traditional instruction using a waiting-list experimental design. Teaching of Psychology, 31(1), 59–62.

    Article  Google Scholar 

  36. Rosenbaum, P. R. (2002). Observational studies. In Observational studies (pp. 1–17). New York, NY: Springer.

    Google Scholar 

  37. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.

    Article  Google Scholar 

  38. Rovai, A. P. (2003). In search of higher persistence rates in distance education online programs. The Internet and Higher Education, 6, 1–16.

    Article  Google Scholar 

  39. Rubin, D. B. (2001). Using propensity scores to help design observational studies: Application to the tobacco litigation. Health Services and Outcomes Research Methodology, 2(3–4), 169–188.

    Article  Google Scholar 

  40. Sener, J. (2012). The seven futures of American education: Improving learning and teaching in a screen-captured world. North Charleston, SC: CreateSpace.

    Google Scholar 

  41. Shadish, W. R., Clark, M. H., & Steiner, P. M. (2008). Can nonrandomized experiments yield accurate answers? A randomized experiment comparing random and nonrandom assignments. Journal of the American Statistical Association, 103(484), 1334–1344.

    Article  Google Scholar 

  42. Shea, P., & Bidjerano, T. (2014). Does online learning impede degree completion? A national study of community college students. Computers & Education, 75, 103–111.

    Article  Google Scholar 

  43. Silverman, S., Aliabadi, S., & Stiles, M. (2009). Meeting the needs of commuter, part-time, transfer, and returning students. In S. Harper & S. Quaye (Eds.), Student engagement in higher education. New York, NY: Routledge.

    Google Scholar 

  44. Summers, J., Waigandt, A., & Whittaker, T. (2005). A comparison of student achievement and satisfaction in an online versus a traditional face-to-face statistics class. Innovative Higher Education, 29(3), 233–250.

    Article  Google Scholar 

  45. Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.

    Article  Google Scholar 

  46. Townsend, B. K. (2001). Redefining the community college transfer mission. Community College Review, 29(2), 29–42.

    Article  Google Scholar 

  47. Urtel, M. (2008). Assessing academic performance between traditional and distance education course formats. Educational Technology & Society, 11(1), 322–330.

    Google Scholar 

  48. Wagner, S., Garippo, S., & Lovaas, P. (2011). A longitudinal comparison of online versus traditional instruction. MERLOT Journal of Online Learning and Teaching, 7(1), 30–42.

    Google Scholar 

  49. Xu, D., & Jaggars, S. S. (2011). The effectiveness of distance education across Virginia’s community colleges: Evidence from introductory college-level math and English courses. Educational Evaluation and Policy Analysis, 33(3), 360–377.

    Article  Google Scholar 

  50. Xu, D., & Jaggars, S. S. (2013). The impact of online learning on students’ course outcomes: Evidence from a large community and technical college system. Economics of Education Review, 37, 46–57.

    Article  Google Scholar 

  51. Xu, D., & Jaggars, S. S. (2014). Performance gaps between online and face-to-face courses: Differences across types of students and academic subject areas. The Journal of Higher Education, 85(5), 633–659.

    Article  Google Scholar 

  52. Xu, D., Jaggars, S. S., & Fletcher, J. (2016). How and why does two-year college entry influence baccalaureate aspirants’ academic and labor market outcomes? A CAPSEE Working Paper. Center for Analysis of Postsecondary Education and Employment.

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Justin C. Ortagus.

Appendix

Appendix

See Table 6.

Table 6 Balance between first-year face-to-face and online students (pooled sample)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Ortagus, J.C. National Evidence of the Impact of First-Year Online Enrollment on Postsecondary Students’ Long-Term Academic Outcomes. Res High Educ 59, 1035–1058 (2018). https://doi.org/10.1007/s11162-018-9495-1

Download citation

Keywords

  • Online education
  • Propensity score weighting
  • Long-term academic success
  • Degree completion
  • Vertical transfer