A Framework for Evaluating Online Degree Programs Through Student Satisfaction

Authors

  • Zikai Zhou University of Southern Mississippi
  • Sharon Rouse University of Southern Mississippi

DOI:

https://doi.org/10.24059/olj.v28i2.3983

Keywords:

Online degree program, student satisfaction, key factors, perceived learning, program recommendation

Abstract

Student satisfaction is a key indicator in evaluating any degree program's performance. In light of the vast difference between online and traditional degree programs, the factors that affect student satisfaction may vary across different courses. Based on the previous literature, this study explores the factors that may affect student satisfaction with online degree programs. A structured framework is proposed for evaluating online degree programs, including six big categories of factors and three outcome variables related to student satisfaction. Data were collected from an online degree program in a large public university to assess the underlying relationships and identify the key factors affecting student satisfaction. In addition, students’ self-regulated learning behavior was identified as the primary factor leading to the significant difference among the three outcome variables. The implications to school administrators and accreditation bodies were also addressed.

References

Al Hassani, A. A., & Wilkins, S. (2022). Student retention in higher education: the influences of organizational identification and institution reputation on student satisfaction and behaviors. International Journal of Educational Management, 36(6), 1046-1064. https://doi.org/10.1108/ijem-03-2022-0123

Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research (CIER), 9(1), 45-52. https://doi.org/10.19030/cier.v9i1.9549

Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133-148. https://doi.org/10.1080/01587919.2018.1553562

Astivia, O. L. O., & Zumbo, B. D. (2019). Heteroskedasticity in Multiple Regression Analysis: What it is, How to Detect it and How to Solve it with Applications in R and SPSS. Practical Assessment, Research, and Evaluation, 24(1), 1. https://doi.org/10.7275/q5xr-fr95

Avcı, Ü., & Ergün, E. (2019). Online students’ LMS activities and their effect on engagement, information literacy and academic performance. Interactive Learning Environments, 1-14. https://doi.org/10.1080/10494820.2019.1636088

Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. L. (2009). Measuring self-regulation in online and blended learning environments. Internet and Higher Education, 12(1), 1-6. https://doi.org/10.1016/j.iheduc.2008.10.005

Blau, G., Williams, W., Jarrell, S., & Nash, D. (2019). Exploring common correlates of business undergraduate satisfaction with their degree program versus expected employment. Journal of Education for Business, 94(1), 31-39. https://doi.org/10.1080/08832323.2018.1502144

Bolliger, D. U. (2004). Key factors for determining student satisfaction in online courses. International Journal on E-learning, 3(1), 61-67. https://www.learntechlib.org/primary/p/2226/

Canning, J. (2017). Conceptualising student voice in UK higher education: four theoretical lenses. Teaching in Higher Education, 22(5), 519-531. https://doi.org/10.1080/13562517.2016.1273207

Chaka, C. (2020). Higher education institutions and the use of online instruction and online tools and resources during the COVID-19 outbreak-An online review of selected US and SA's universities. https://doi.org/10.21203/rs.3.rs-61482/v1

Cole, A., Anderson, C., Bunton, T., Cherney, M., Fisher, V. C., Featherston, M., Motel, L., Nicolini, K., Peck, B., & Allen, M. (2017). Student predisposition to instructor feedback and perceptions of teaching presence predict motivation toward online courses. Online Learning Journal, 21(4). https://doi.org/10.24059/olj.v21i4.966

Crawford, J., Butler-Henderson, K., Rudolph, J., Malkawi, B., Glowatz, M., Burton, R., Magni, P., & Lam, S. (2020). COVID-19: 20 countries' higher education intra-period digital pedagogy responses. Journal of Applied Learning & Teaching, 3(1), 1-20. https://doi.org/10.37074/jalt.2020.3.1.7

Darlington, R. B., & Hayes, A. F. (2016). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.

Davis, F. D., Marangunic, A., & Granic, A. (2020). Technology acceptance model: 30 Years of Tam. Springer.

Denis, D. J. (2018). SPSS data analysis for univariate, bivariate, and multivariate statistics. John Wiley & Sons.

DeShields, O. W., Kara, A., & Kaynak, E. (2005). Determinants of business student satisfaction and retention in higher education: applying Herzberg's two‐factor theory. International Journal of Educational Management, 19(2), 128-139. https://doi.org/10.1108/09513540510582426

Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5-22. https://doi.org/http://dx.doi.org/10.1177/0047239520934018

National Center for Education Statistics. (2021). Digest of education statistics. https://nces.ed.gov/programs/digest/d21/tables/dt21_311.15.asp

Ellis, R. K. (2009). Field guide to learning management systems. ASTD Learning Circuits. https://home.csulb.edu/~arezaei/ETEC551/web/LMS_fieldguide_20091.pdf

Farahmandian, S., Minavand, H., & Afshardost, M. (2013). Perceived service quality and student satisfaction in higher education. Journal of Business and Management, 12(4), 65-74. https://doi.org/10.9790/487X-1246574

Fidell, L. S., & Tabachnick, B., G. (2018). Using Multivariate Statistics (7th ed.). Pearson.

Freeman, L., & Urbaczewski, A. (2019). Critical success factors for online education: longitudinal results on program satisfaction. Communications of the Association for Information Systems, 44(1), 630-645. https://doi.org/10.17705/1cais.04430

Gares, S. L., Kariuki, J. K., & Rempel, B. P. (2020). Community matters: Student instructor relationships foster student motivation and engagement in an emergency remote teaching environment. Journal of Chemical Education, 97(9), 3332-3335. https://doi.org/10.1021/acs.jchemed.0c00635

Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. International Journal of Educational Leadership Preparation, 11(1), n1. https://files.eric.ed.gov/fulltext/EJ1103654.pdf

Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.

Hanssen, T.-E. S., & Solvoll, G. (2015). The importance of university facilities for student satisfaction at a Norwegian University. Facilities, 33(13/14), 744-759. https://doi.org/10.1108/F-11-2014-0081

Khosravi, A. A., Poushaneh, K., Roozegar, A., & Sohrabifard, N. (2013). Determination of factors affecting student satisfaction of Islamic Azad University. Procedia-Social and Behavioral Sciences, 84, 579-583. https://doi.org/10.1016/j.sbspro.2013.06.607

Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford Publications.

Kucuk, S., & Richardson, J. C. (2019). A structural equation model of predictors of online learners' engagement and satisfaction. Online Learning, 23(2), 196-216. https://doi.org/10.24059/olj.v23i2.1455

Kuo, Y. C., Walker, A. E., Schroder, K. E. E., & Belland, B. R. (2014). Interaction, Internet self-efficacy, and self-regulated learning as predictors of student satisfaction in online education courses. Internet and Higher Education, 20, 35-50. https://doi.org/10.1016/j.iheduc.2013.10.001

Letcher, D. W., & Neves, J. S. (2010). Determinants of undergraduate business student satisfaction. Research in Higher Education Journal, 6, 1. https://api.semanticscholar.org/CorpusID:2373494

Li, K. (2019). MOOC learners' demographics, self-regulated learning strategy, perceived learning and satisfaction: A structural equation modeling approach. Computers & Education, 132, 16-30. https://doi.org/10.1016/j.compedu.2019.01.003

Malik, M. W. (2010). Factor effecting learner’s satisfaction towards e-Learning: A conceptual framework. OIDA International Journal of Sustainable Development, 2(3), 77-82. https://ssrn.com/abstract=1711989

Moller, L., & Huett, J. B. (2012). The next generation of distance education: Unconstrained learning. Springer Science & Business Media.

Muljana, P. S., & Luo, T. (2019). Factors contributing to student retention in online learning and recommended strategies for improvement: A systematic literature review. Journal of Information Technology Education-Research, 18, 19-57. https://doi.org/10.28945/4182

Parahoo, S. K., Santally, M. I., Rajabalee, Y., & Harvey, H. L. (2016). Designing a predictive model of student satisfaction in online learning. Journal of Marketing for Higher Education, 26(1), 1-19. https://doi.org/10.1080/08841241.2015.1083511

Pituch, K. A., & Stevens, J. P. (2015). Applied multivariate statistics for the social sciences: Analyses with SAS and IBM’s SPSS. Routledge.

Roddy, C., Amiet, D. L., Chung, J., Holt, C., Shaw, L., McKenzie, S., Garivaldis, F., Lodge, J. M., & Mundy, M. E. (2017). Applying best practice online learning, teaching, and support to intensive online environments: An integrative review. Frontiers in Education. http://dx.doi.org/10.3389/feduc.2017.00059

Seaman, J. E., Allen, I. E., & Seaman, J. (2018). Grade increase: Tracking distance education in the United States. Babson Survey Research Group. https://files.eric.ed.gov/fulltext/ED580852.pdf

Sears, C. R., Boyce, M. A., Boon, S. D., Goghari, V. M., Irwin, K., & Boyes, M. (2017). Predictors of student satisfaction in a large psychology undergraduate program. Canadian Psychology-Psychologie Canadienne, 58(2), 148-160. https://doi.org/10.1037/cap0000082

Sebastianelli, R., Swift, C., & Tamimi, N. (2015). Factors affecting perceived learning, satisfaction, and quality in the online MBA: A structural equation modeling approach. Journal of Education for Business, 90(6), 296-305. https://doi.org/10.1080/08832323.2015.1038979

Sigala, M., Christou, E., Petruzzellis, L., D'Uggento, A. M., & Romanazzi, S. (2006). Student satisfaction and quality of service in Italian universities. Managing Service Quality: An International Journal. https://doi.org/10.1108/09604520610675694

Suhre, C. J. M., Jansen, E. P. W. A., & Harskamp, E. G. (2007). Impact of degree program satisfaction on the persistence of college students. Higher Education, 54(2), 207-226. https://doi.org/10.1007/s10734-005-2376-5

Tseng, H. W., Yi, X., & Yeh, H. T. (2019). Learning-related soft skills among online business students in higher education: Grade level and managerial role differences in self-regulation, motivation, and social skill. Computers in Human Behavior, 95, 179-186. https://doi.org/10.1016/j.chb.2018.11.035

Volery, T., & Lord, D. (2000). Critical success factors in online education. International Journal of Educational Management, 14(5), 216-223. https://doi.org/10.1108/09513540010344731

Weerasinghe, I. S., & Fernando, R. (2017). Student' satisfaction in higher education. American Journal of Educational Research, 5(5), 533-539. https://ssrn.com/abstract=2976013

Wei, H.-C., & Chou, C. (2020). Online learning performance and satisfaction: Do perceptions and readiness matter? Distance Education, 41(1), 48-69. https://doi.org/10.1080/01587919.2020.1724768

Wong, J., Baars, M., Davis, D., Van der Zee, T., Houben, G. J., & Paas, F. (2019). Supporting self-regulated learning in online learning environments and moocs: A systematic review. International Journal of Human-Computer Interaction, 35(4-5), 356-373. https://doi.org/10.1080/10447318.2018.1543084

Zhou, Z., & Wang, S. (2023). Strategies for Online Student Engagement. Society for Information Technology & Teacher Education International Conference. https://www.learntechlib.org/primary/p/221884/

Zhou, Z. K., & Zhang, Y. Y. (2023). Intrinsic and extrinsic motivation in distance education: a self-determination perspective. American Journal of Distance Education, 1-14. https://doi.org/10.1080/08923647.2023.2177032

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Published

2024-06-01

How to Cite

Zhou, Z., & Rouse, S. (2024). A Framework for Evaluating Online Degree Programs Through Student Satisfaction. Online Learning, 28(2). https://doi.org/10.24059/olj.v28i2.3983