Online learning satisfaction in higher education: what are the determining factors?

Sri Suhandiah, Airlangga University Dinamika University, Indonesia
Fendy Suhariadi, Airlangga University, Indonesia
Praptini Yulianti, Airlangga University, Indonesia
Ratna Wardani, Airlangga University Public Health, IIK Strada Indonesia, Indonesia
Yurilla Endah Muliatie, Airlangga University Universitas Wijaya Putra, Indonesia

 10.21831/cp.v41i2.35724

Abstract


Covid-19 pandemic crisis has required the implementation of comprehensive online learning in Indonesia, including in the higher education institutions. Changes in the conventional way of face-to-face learning to online one provide both positive and negative responses, which will affect student learning satisfaction. This research aims to determine student satisfaction with the online learning which is associated with perceived technological complexity, student learning experience, online learning readiness, and presence of lecturers in online learning activities. This research employed a quantitative approach. Data were collected utlizing a google online questionnaire distributed through a network of lecturers. The samples were 439 students from state and private higher education institutions spreading across eight islands in Indonesia. Statistical analysis utilized the Structural Equation Model (SEM) in Stata 15. The results show that online learning satisfaction is positively influenced by student experience, online learning readiness, and the presence of lecturers in online learning. Moreover, online learning readiness can mediate student experience and online learning satisfaction but unable to mediate technology complexity and online learning satisfaction. These findings add to the literature on online learning satisfaction and provide direction for the solution of problems on online learning satisfaction. The proposed suggestion to higher education institutions is to encourage the development of online-based collaborative models and to provide a continuous experience for students.

Keywords


online learning; learning satisfaction; learning readiness

Full Text:

PDF

References


Al-Araibi, A. A. M., Mahrin, M. N. bin, & Yusoff, R. C. M. (2019). Technological aspect factors of e-learning readiness in higher education institutions: Delphi technique. Education and Information Technologies, 24(1), 567–590. https://doi.org/10.1007/s10639-018-9780-9.

Al-Fraihat, D., Joy, M., & Sinclair, J. (2017). Identifying success factors for e-learning in higher education. 12th International Conference on E-Learning (ICEL 2017), April 2020, 247–255.

APJII. (2018). Survei Penetrasi dan Profil Perilaku Pengguna Internet Indonesia 2018. https://apjii.or.id/survei

Attis, J. (2014). An investigation of the variable that predict teacher e-learning acceptance. In Liberti University. Liberty University.

Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018). Best Practices for Developing and Validating Scales for Health, Social, and Behavioral Research: A Primer. Frontiers in Public Health, 6(June), 1–18. https://doi.org/10.3389/fpubh.2018.00149

Bolliger, D. U., & Martindale, T. (2004). Key factors for determining student satisfaction in online courses. International Journal on E-Learning, January-Ma, 61–67. https://www.learntechlib.org/primary/p/2226/.

Cole, M. T., Shelley, D. J., & Swartz, L. B. (2014). Online instruction, e-learning, and student satisfaction: A three year study. International Review of Research in Open and Distance Learning, 15(6), 111–131. https://doi.org/10.19173/irrodl.v15i6.1748.

Eom, S. B., Ashill, N., & Wen, H. J. (2006). The determinants of students’ perceived learning outcomes and satisfaction in university online education: An empirical investigation. Decision Sciences Journal of Innovative Education, 4(2), 215–235. https://doi.org/https://doi.org/10.1111/j.1540-4609.2006.00114.x

Fogerson, D. L. (2005). Readiness factors Contributing to participant satisfcction in online higher education courses [University of Tennessee - Knoxville]. https://trace.tennessee.edu/utk_graddiss/1952.

Gray, J. A., & DiLoreto, M. (2016). The effects of student engagement, student satisfaction, and perceived learning in online learning environments. NCPEA International Journal of Educational Leadership Preparation, 11(1), 98–119.

Guerra-Carrillo, B., Katovich, K., & Bunge, S. A. (2017). Does higher education hone cognitive functioning and learning efficacy? Findings from a large and diverse sample. PLoS ONE, 12(8), 1–17. https://doi.org/10.1371/journal.pone.0182276

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). Pearson Education.

Hasan, B. (2007). Examining the effects of computer self-efficacy and system complexity on the path of paths of the technology acceptance. Information Resources Management Journal, 20(3), 76–88. https://doi.org/10.4018/irmj.2007070106

Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers and Education, 55(3), 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004.

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.

Irawan, A. W., Dwisona, & Lestari, M. (2020). Psychological Impacts of Students on Online Learning During the Pandemic COVID-19. KONSELI: Jurnal Bimbingan Dan Konseling, 7(1), 53–60. https://doi.org/10.24042/kons.v7i1.6389

Jaggars, S. S., Edgecombe, N., & Stacey, G. W. (2013). Creating an effective online instructor presence. http://files.eric.ed.gov/fulltext/ED542146.pdf.

Khalid, M., & Quick, D. (2016). Teaching Presence Influencing Online Students’ Course Satisfaction at an Institution of Higher Education. International Education Studies, 9(3). https://doi.org/10.5539/ies.v9n3p62

Kominfo RI. (2020). Status Digital Literasi Indonesia. Direktorat Jenderal Aplikasi Informatika. https://aptika.kominfo.go.id/wp-content/uploads/2020/11/Survei-Literasi-Digital-Indonesia-2020.pdf

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.

Kusumo, N. S. A. M., Kurniawan, F. B., & Putri, N. I. (2012). Elearning obstacle faced by Indonesian students. The Eight Conference on ELearning for Knowledge-Based Society, February, 23–24. http://www.elearningap.com/eLAP2011/Proceedings/paper25.pdf.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta analysis and review of online learning studies. US Department of Education. www.ed.gov/about/offices/list/opepd/ppss/reports.html.

Parry, E. (2020). Generation Z in Asia: Patterns and Predictions. In E. Gentina & E. Parry (Eds.), The New Generation Z in Asia: Dynamics, Differences, Digitalisation (pp. 195–200). Emerald Publishing Limited. https://doi.org/10.1108/978-1-80043-220-820201021

Parsazadeh, N., Megat, N., Zainuddin, M., Ali, R., & Hematian, A. (2013). A review on the success factors of e-learning. The Second International Conference on E-Technologies and Networks for Development (ICeND2013), August 2018.

Pearson. (2019). The global learner survey. https://www.pearson.com/content/dam/global-store/global/resources/Pearson_Global_Learner_Survey_2019.pdf.

Richardson, J. C., Besser, E., Koehler, A., Lim, J. E., & Strait, M. (2016). Instructors’ perceptions of instructor presence in online learning environments. International Review of Research in Open and Distance Learning, 17(4), 82–104. https://doi.org/10.19173/irrodl.v17i4.2330.

Sahin, I., & Shelley, M. (2008). Considering students’ perceptions: The distance education student satisfaction model. Educational Technology and Society, 11(3), 216–223. https://www.j-ets.net/collection/published-issues/11_3.

Schwieger, D., & Ladwig, C. (2018). Reaching and Retaining the Next Generation: Adapting to the Expectations of Gen Z in the Classroom. Information Systems Education Journal, 16(3), 45–54.

Shea, P., Li, C. S., & Pickett, A. (2006). A study of teaching presence and student sense of learning community in fully online and web-enhanced college courses. Internet and Higher Education, 9(3), 175–190. https://doi.org/10.1016/j.iheduc.2006.06.005.

Simonds, T. A., & Brock, B. L. (2014). Relationship Between Age, Experience, and Student Preference for Types of Learning Activities in Online Courses. Journal of Educators Online, 11(1). https://doi.org/10.9743/JEO.2014.1.3

Sitzmann, T., Ely, K., Bell, B. S., & Bauer, K. N. (2010). The effects of technical difficulties on learning and attrition during online training. Journal of Experimental Psychology: Applied, 16(3), 281–292. https://doi.org/10.1037/a0019968.

Taber, K. S. (2018). The use of cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2.

Tan, S., Chuah, F., & Ting, H. (2017). Empowering 21st Century Learners Through Holistic and Enterprising Learning. Empowering 21st Century Learners Through Holistic and Enterprising Learning, 3–10. https://doi.org/10.1007/978-981-10-4241-6

Teo, T. (2012). Modelling the influences of beliefs on preservice teachers’ attitudes towards computer use. European Journal of Educational Research, 1(1), 13–22. https://doi.org/10.12973/eu-jer.1.1.13.

Vesely, P., Bloom, L., & Sherlock, J. (2007). Key elements of building online community: Comparing faculty and student perceptions. Journal of Online Learning and Teaching, 3(3). https://jolt.merlot.org/vol3no3/vesely.pdf

Wang, H., Pi, Z., & Hu, W. (2019). The instructor’s gaze guidance in video lectures improves learning. Journal of Computer Assisted Learning, 35(1), 42–50.

Warner, D., Christie, G., & Choy, S. (1998). The readiness of the VET sector for flexible delivery including on-line learning: a guide for developers of curriculum and training packages.

Warrican, S. J., Leacock, C. J., Thompson, B. P., & Alleyne, M. L. (2014). Predictors of student success in an online learning environment in the English-speaking caribbean: Evidence from the university of the west Indies open Campus. Open Praxis, 6(4). https://doi.org/10.5944/openpraxis.6.4.158.

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.

Yilmaz, R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Computers in Human Behavior, 70, 251–260. https://doi.org/10.1016/j.chb.2016.12.085.

Zhu, C. (2012). Student satisfaction, performance, and knowledge construction in online collaborative learning. Journal of Educational Technology & Society, 15(1). http://www.jstor.org/stable/jeductechsoci.15.1.127.




DOI: https://doi.org/10.21831/cp.v41i2.35724

Refbacks

  • There are currently no refbacks.


Bookmark and Share


 

Social Media:

     

 

 Creative Commons License
Jurnal Cakrawala Pendidikan by Lembaga Pengembangan dan Penjaminan Mutu Pendidikan UNY is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at https://journal.uny.ac.id/index.php/cp/index.

Translator
 
 web analytics
View Our Stats