EXAMINATION OF THE PREDICTION OF FLEXIBILITY FOR LEARNER SATISFACTION IN ONLINE COURSES

Universities consider student satisfaction in order to improve the online education they give to students and to question the fulfillment of their responsibilities. Student satisfaction may depend not only on the educational institution but also on individual characteristics. One of these individual characteristics is flexibility, which requires multidimensional pedagogical responsibility in online learning environments. The aim of this study is to examine whether the flexibility of time management, the flexibility of teacher contact, and the flexibility of content predict online course satisfaction. In this research, the predictive relational research method was used. 1794 students participated in the research. During an academic term, students took an online Turkish II course at a university’s Distance Education Research and Application Center. According to the results of the analysis, the students’ three flexibility predicts their satisfaction and the model that explains their satisfaction is significant (R2=.60; p<.01). In the model, the variable that most explains student satisfaction is the flexibility of content. In addition, other variables explaining student satisfaction are students’ flexibility in teacher contact and their flexibility in time management. Based on the results of the research, implications, and suggestions are presented.

Keywords:

Online course satisfaction, the flexibility of time management, the flexibility of teacher contact the flexibility of content,

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Abdel-Jaber, H. (2017). Experimental analysis of students’ satisfaction factors in e-learning environment: A case study on Saudi Arabian University. Journal of Information and Knowledge Management, 16(2), 1–21. https://doi.org/10.1142/S0219649217500186
Abuhassna, H., Al-Rahmi, W. M., Yahya, N., Zakaria, M. A. Z. M., Kosnin, A. B. M., & Darwish, M. (2020). Development of a new model on utilizing online learning platforms to improve students’ academic achievements and satisfaction. International Journal of Educational Technology in Higher Education, 17(1). https://doi.org/10.1186/s41239-020-00216-z
Akyol, Z., Vaughan, N., & Garrison, D. R. (2011). The impact of course duration on the development of a community of inquiry. Interactive Learning Environments, 19(3), 231–246. https://doi.org/10.1080/10494820902809147
Almoeather, R. (2020). Effectiveness of blackboard and edmodo in self-regulated learning and educational satisfaction. Turkish Online Journal of Distance Education, 21(2), 126–140. https://doi.org/10.17718/tojde.728140
Andrade, M. S., & Alden-Rivers, B. (2019). Developing a framework for sustainable growth of flexible learning opportunities. Higher Education Pedagogies, 4(1), 1–16. https://doi.org/10.1080/23752696.2018.1564879
Bayrak, F., Tibi, M. H., & Altun, A. (2020). Development of online course satisfaction scale. Turkish Online Journal of Distance Education, 21(4), 110–123. https://doi.org/10.17718/tojde.803378
Bell, C., Bowden, M., & Trott, A. (1997). Implementing flexible learning. London: Kogan Page Ltd.
Bergamin, P. B., Werlen, E., Siegenthaler, E., & Ziska, S. (2012). The relationship between flexible and self-regulated learning in open and distance universities. International Review of Research in Open and Distance Learning, 13(2), 101–123. https://doi.org/10.19173/irrodl.v13i2.1124
Bergamin, P., Ziska, S., & Groner, R. (2010). Structural equation modelling of factors affecting success in student’s performance in ODL-Programs: Extending quality management concepts. Open Praxis, 4(1), 1–8. https://www.openpraxis.org/articles/abstract/218/
Cheng, M., & Yuen, A. H. K. (2018). Student continuance of learning management system use: A longitudinal exploration. Computers and Education, 120, 241–253. https://doi.org/10.1016/j.compedu.2018.02.004
Cheng, Y. M. (2020). Students’ satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors. Education and Training, 62(9), 1037–1059. https://doi.org/10.1108/ET-10-2019-0245
Chow, W. S., & Shi, S. (2014). Investigating students’ satisfaction and continuance intention toward e-learning: An extension of the expectation–confirmation model. Procedia - Social and Behavioral Sciences, 141, 1145–1149. https://doi.org/10.1016/j.sbspro.2014.05.193
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd Ed.). Lawrence Erlbaum Associates. https://doi.org/10.4324/9780203771587
Cornelius, S., Gordon, C., & Ackland, A. (2011). Towards flexible learning for adult learners in professional contexts: An activity-focused course design. Interactive Learning Environments, 19(4), 381–393. https://doi.org/10.1080/10494820903298258
Council of Higher Education. (2020a). Küresel salgında yeni normalleşme süreci [The new normalization process in the global pandemic]. https://www.yok.gov.tr/Documents/Yayinlar/Yayinlarimiz/2020/kuresel-salginda-yeni-normallesme-sureci-2020.pdf
Council of Higher Education. (2020b). YÖK’ten salgın sürecinde üniversitelerdeki uzaktan eğitimin bir aylık durum tespiti [One-month status determination of distance education at universities during the pandemic from Council of Higher Education]. https://www.yok.gov.tr/Sayfalar/Haberler/2020/uzaktan-egitime-yonelik-degerlendirme.aspx
Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior, 60, 198–211. https://doi.org/10.1016/j.chb.2016.02.066
Divjak, M., Rupel, V. P., & Lešnik, K. M. (2018). The impact of study attitudes and study behaviour on satisfaction of online students with the implementation of online study programmes. Educational Media International, 55(3), 287–300. https://doi.org/10.1080/09523987.2018.1512450
Faize, F. A., & Nawaz, M. (2020). Evaluation and Improvement of students’ satisfaction in Online learning during COVID-19. Open Praxis, 12(4), 495. https://doi.org/10.5944/openpraxis.12.4.1153
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146
Flannery, M., & McGarr, O. (2014). Flexibility in higher education: an Irish perspective. Irish Educational Studies, 33(4), 419–434. https://doi.org/10.1080/03323315.2014.978658
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). New York, NY: McGraw-Hill.
Harsasi, M., & Sutawijaya, A. (2018). Determinants of student satisfaction in online tutorial: A study of a distance education institution. Turkish Online Journal of Distance Education, 19(1), 89–99. https://doi.org/10.17718/tojde.382732
Hostetter, C. (2013). Community matters: Social presence and learning outcomes. Journal of the Scholarship of Teaching and Learning, 13(1), 77–86. https://files.eric.ed.gov/fulltext/EJ1011685.pdf
Houlden, S., & Veletsianos, G. (2019). A posthumanist critique of flexible online learning and its “anytime anyplace” claims. British Journal of Educational Technology, 50(3), 1005–1018. https://doi.org/10.1111/bjet.12779
Ilgaz, H., & Gülbahar, Y. (2015). A snapshot of online learners: e-Readiness, e-Satisfaction and expectations. International Review of Research in Open and Distance Learning, 16(2), 171–187. https://doi.org/10.19173/irrodl.v16i2.2117
Ilgaz, H., & Gülbahar, Y. (2020). Examining e-learners’ preferences and readiness satisfaction: A holistic modelling approach. Open Praxis, 12(2), 209. https://doi.org/10.5944/openpraxis.12.2.1070
Islam, A. K. M. N. (2014). Sources of satisfaction and dissatisfaction with a learning management system in post-adoption stage: A critical incident technique approach. Computers in Human Behavior, 30, 249–261. https://doi.org/10.1016/j.chb.2013.09.010
Islam, A. K. M. N., & Azad, N. (2015). Satisfaction and continuance with a learning management system comparing perceptions of educators and students. International Journal of Information and Learning Technology, 32(2), 109–123. https://doi.org/10.1108/IJILT-09-2014-0020
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. https://doi.org/10.1080/08923647.2014.867697
Jakupec, V., & Garrick, J. (2000). Flexible learning, work and human resource development. In V. Jakupec & J. Garrick (Eds.), Flexible learning, human resource and organisational development: Putting theory to work (pp. 1–8). Routledge. https://doi.org/10.4324/9780203991817
Kantoğlu, B., Torkul, O., & Altunışık, R. (2013). E- öğrenmede öğrenci memnuniyetini etkileyen faktörlerin incelenmesine yönelik model önerisi [A study on the factors affecting student’s satisfaction in e-learning: A model proposition]. Business and Economics Research Journal, 4(1), 121–141. https://www.berjournal.com/a-study-on-the-factors-affecting-student’s-satisfaction-in-e-learning-a-model-proposition
Kocatürk Kapucu, N., & Uşun, S. (2020). Üniversitelerde ortak zorunlu derslerin öğretiminde uzaktan eğitim uygulamaları [Distance education practices in teaching common compulsory courses at universities]. Açıköğretim Uygulamaları ve Araştırmaları Dergisi (AUAd), 6(1), 8–27. https://dergipark.org.tr/en/pub/auad/issue/55639/761236
Koh, J. H. L., & Kan, R. Y. P. (2020). Perceptions of learning management system quality, satisfaction, and usage: Differences among students of the arts. Australasian Journal of Educational Technology, 36(3), 26–40. https://doi.org/10.14742/AJET.5187
Kokoç, M. (2020). Açık ve uzaktan öğrenmede esneklik ölçeğini Türkçe’ye uyarlama çalışması [Adaptation study of the scale of flexibility in open and distance learning]. Educational Technology: Theory and Practice, 10(2), 366–385. https://doi.org/10.17943/etku.643358
Kuo, Y. C., Walker, A. E., Belland, B. R., & Schroder, K. E. E. (2013). A predictive study of student satisfaction in online education programs. International Review of Research in Open and Distance Learning, 14(1), 16–39. https://doi.org/10.19173/irrodl.v14i1.1338
Landrum, B. (2020). Examining students’ confidence to learn online, self-regulation skills and perceptions of satisfaction and usefulness of online classes. Online Learning, 24(3), 128–146. https://doi.org/10.24059/olj.v24i3.2066
Levy, Y. (2007). Comparing dropouts and persistence in e-learning courses. Computers and Education, 48, 185–204. https://doi.org/10.1016/j.compedu.2004.12.004
Li, K. C., & Wong, B. Y. Y. (2018). Revisiting the definitions and implementation of flexible learning. In K. C. Li, K. S. Yuen, & B. T. M. Wong (Eds.), Innovations in Open and Flexible Education (pp. 3–13). Springer. https://doi.org/10.1007/978-981-10-7995-5_1
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system. Computers and Education, 51(2), 864–873. https://doi.org/10.1016/j.compedu.2007.09.005
Machado-Da-Silva, F. N., Meirelles, F. D. S., Filenga, D., & Filho, M. B. (2014). Student satisfaction process in virtual learning system: Considerations based in information and service quality from Brazil’s experience. Turkish Online Journal of Distance Education, 15(3), 122–142. https://dergipark.org.tr/en/pub/tojde/issue/16893/175971
Naidu, S. (2017). How flexible is flexible learning, who is to decide and what are its implications? Distance Education, 38(3), 269–272. https://doi.org/10.1080/01587919.2017.1371831
Nasir, M. K. M. (2020). The influence of social presence on students’ satisfaction toward online course. Open Praxis, 12(4), 485–493. http://doi.org/10.5944/openpraxis.12.4.1141
Ohliati, J., & Abbas, B. S. (2019). Measuring students satisfaction in using learning management system. International Journal of Emerging Technologies in Learning, 14(4), 180–189. https://doi.org/10.3991/ijet.v14i04.9427
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. https://doi.org/10.2307/3150499
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
Rajabalee, Y. B., & Santally, M. I. (2020). Learner satisfaction, engagement and performances in an online module: Implications for institutional e-learning policy. Education and Information Technologies, 26, 2623-2656. https://doi.org/10.1007/s10639-020-10375-1
Richardson, J. C., Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: A meta-analysis. Computers in Human Behavior, 71, 402–417. https://doi.org/10.1016/j.chb.2017.02.001
Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students’ perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68–88. http://dx.doi.org/10.24059/olj.v7i1.1864
Richardson, J. T. E. (2000). Researching student learning: Approaches to studying in campus-based and distance education. Buckingham: Open University Press. http://oro.open.ac.uk/50043/
Shih, H. F., Chen, S. H. E., Chen, S. C., & Wey, S. C. (2013). The Relationship among tertiary level EFL students’ personality, online learning motivation and online learning satisfaction. Procedia - Social and Behavioral Sciences, 103, 1152–1160. https://doi.org/10.1016/j.sbspro.2013.10.442
Soffer, T., Kahan, T., & Livne, E. (2017). E-assessment of online academic courses via students’ activities and perceptions. Studies in Educational Evaluation, 54, 83–93. https://doi.org/10.1016/j.stueduc.2016.10.001
Soffer, T., Kahan, T., & Nachmias, R. (2019). Patterns of students’ utilization of flexibility in online academic courses and their relation to course achievement. International Review of Research in Open and Distance Learning, 20(3), 202–220. https://doi.org/10.19173/irrodl.v20i4.3949
Thoms, B., & Eryilmaz, E. (2014). How media choice affects learner interactions in distance learning classes. Computers and Education, 75, 112–126. https://doi.org/10.1016/j.compedu.2014.02.002
Turhangil Erenler, H. H. (2020). A structural equation model to evaluate students’ learning and satisfaction. Computer Applications in Engineering Education, 28(2), 254–267. https://doi.org/10.1002/cae.22189
Van den Brande, L. (1993). Flexible and distance learning. Chichester: John Wiley.
Veletsianos, G., & Houlden, S. (2019). An analysis of flexible learning and flexibility over the last 40 years of Distance Education. Distance Education, 40(4), 454–468. https://doi.org/10.1080/01587919.2019.1681893
Wandler, J. B., & Imbriale, W. J. (2017). Promoting undergraduate student self-regulation in online learning environments. Online Learning, 21(2), 1–16. https://doi.org/10.24059/olj.v21i2.881
Weller, M., De los Arcos, B., Farrow, R., Pitt, B., & McAndrew, P. (2015). The impact of OER on teaching and learning practice. Open Praxis, 7(4). https://doi.org/10.5944/openpraxis.7.4.227
Yurdugül, H., & Alsancak Sarikaya, D. (2013). The scale of online learning readiness: A study of validity and reliability. Education and Science, 38(169), 391–406. http://egitimvebilim.ted.org.tr/index.php/EB/article/view/2420
Zhang, J., Burgos, D., & Dawson, S. (2019). Advancing open, flexible and distance learning through learning analytics. Distance Education, 40(3), 303–308. https://doi.org/10.1080/01587919.2019.1656151
Zhang, J., Lou, X., Zhang, H., & Zhang, J. (2019). Modeling collective attention in online and flexible learning environments. Distance Education, 40(2), 278–301. https://doi.org/10.1080/01587919.2019.1600368