Perceptions and self-efficacy in online learning: Do students' characteristics and access to technology matter?
DOI:
https://doi.org/10.58230/josse.v2i2.317Keywords:
Online Learning Perceptions, Online Learning Self-Efficacy, Students’ Characteristics, Technology AccessAbstract
While online learning has become the delivery mode of choice to facilitate flexible or distance learning amid the COVID-19 pandemic, this alternative approach to instruction has challenged the entire educational system in the Philippines. Survey data from 2027 students from a private college were analyzed using nonparametric statistical tests to examine how perceptions and self-efficacy in online learning are affected by students’ characteristics and access to technology. Findings suggest that, in general, college students have moderate to high perceptions and self-efficacy when it comes to online learning. When students’ characteristics were compared, gender, academic track, and prior online learning experience showed significant differences in the two scales. Year level and the number of units enrolled in by students did not have any significant effect. Factors related to technology access, namely, device ownership, device sharing, Internet connectivity, and type of subscription, were also investigated. Both Internet connectivity and the type of subscription were significant factors that impact how learners view online learning and how competent they are in accomplishing online tasks. When online learning perceptions and online learning self-efficacy were correlated, highly significant positive associations among the subscales were obtained.
Downloads
References
Aarts, S., van den Akker, M., & Winkens, B. (2014). The importance of effect sizes. European Journal of General Practice, 20(1), 61–64. https://doi.org/10.3109/13814788.2013.818655
Aldhahi, M. I., Alqahtani, A. S., Baattaiah, B. A., & Al-Mohammed, H. I. (2021). Exploring the relationship between students’ learning satisfaction and self-efficacy during the emergency transition to remote learning amid the coronavirus pandemic: A cross-sectional study. Education and Information Technologies. https://doi.org/10.1007/s10639-021-10644-7
Al-Emran, M., Elsherif, H. M., & Shaalan, K. (2016). Investigating attitudes towards the use of mobile learning in higher education. Computers in Human Behavior, 56, 93–102. https://doi.org/10.1016/j.chb.2015.11.033
Ali, I., Narayan, A. K., & Sharma, U. (2020). Adapting to COVID-19 disruptions: student engagement in online learning of accounting. Accounting Research Journal, 34(3), 261–269. https://doi.org/10.1108/ARJ-09-2020-0293
Almazova, N., Krylova, E., Rubtsova, A., & Odinokaya, M. (2020). Challenges and opportunities for Russian higher education amid covid-19: Teachers’ perspective. Education Sciences, 10(368), 1–11. https://doi.org/10.3390/educsci10120368
Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research-First Quarter, 9(1), 45–52.
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
Artino, A. R., & Stephens, J. M. (2009). Academic motivation and self-regulation: A comparative analysis of undergraduate and graduate students learning online. Internet and Higher Education, 12(3–4), 146–151. https://doi.org/10.1016/j.iheduc.2009.02.001
Ashong, C. Y., & Commander, N. E. (2012). Ethnicity, gender, and perceptions of online Learning in higher education. MERLOT Journal of Online Learning and Teaching, 8(2), 98–110.
Aydin, S., Akkan, Y., Arpaz, E., & Koparan, B. (2015). Online learning in vocational school: Focus on students’ perceptions. Procedia - Social and Behavioral Sciences, 174, 3663–3667. https://doi.org/10.1016/j.sbspro.2015.01.1087
Azionya, C. M., & Nhedzi, A. (2021). The digital divide and higher education challenge with emergency online learning: Analysis of tweets in the wake of the COVID-19 lockdown. Turkish Online Journal of Distance Education, 22(4), 164–182.
Bates, R., & Khasawneh, S. (2007). Self-efficacy and college students’ perceptions and use of online learning systems. Computers in Human Behavior, 23(1), 175–191. https://doi.org/10.1016/j.chb.2004.04.004
Baticulon, R. E., Sy, J. J., Alberto, N. R. I., Baron, M. B. C., Mabulay, R. E. C., Rizada, L. G. T., Tiu, C. J. S., Clarion, C. A., & Reyes, J. C. B. (2021). Barriers to online learning in the time of COVID-19: A national survey of medical students in the Philippines. Medical Science Educator, 31(2), 615–626. https://doi.org/10.1007/s40670-021-01231-z
Bhagat, K. K., Wu, L. Y., & Chang, C.-Y. (2019). The impact of personality on students’ perceptions towards online learning. Australasian Journal of Educational Technology, 35(4). https://doi.org/10.14742/ajet.4162
Borun, M., Schaller, D. T., Chambers, M. B., & Allison-Bunnell, S. (2010). Implications of learning style, age group, and gender for developing online learning activities. Visitor Studies, 13(2), 145–159. https://doi.org/10.1080/10645571003621513
Bozkurt, A., & Sharma, R. C. (2020). Emergency remote teaching in a time of global crisis due to coronaVirus pandemic. Asian Journal of Distance Education, 15(1), 2020. http://www.asianjde.org
Ching, Y.-H., & Hsu, Y.-C. (2015). Online graduate students’ preferences of discussion modality: does gender matter? MERLOT Journal of Online Learning and Teaching, 11(1), 31–41. https://www.qualitymatters.org/rubric
Daniels, M. M., Sarte, E., & Cruz, J. dela. (2019). Students’ perception on e-learning: A basis for the development of e-learning framework in higher education institutions. IOP Conference Series: Materials Science and Engineering, 482(1). https://doi.org/10.1088/1757-899X/482/1/012008
Eng, T. H., Ibrahim, A. F., & Shamsuddin, N. E. (2015). Students’ perception: Student Feedback Online (SuFO) in higher education. Procedia - Social and Behavioral Sciences, 167, 109–116. https://doi.org/10.1016/j.sbspro.2014.12.651
Fearnley, M. R., & Amora, J. T. (2020). Learning management system adoption in higher education using the extended technology acceptance model. IAFOR Journal of Education, 8(2). https://doi.org/10.22492/ije.8.2.05
Fearnley, M., & Malay, C. (2021). Assessing students’ online learning readiness: Are college freshmen ready? Asia-Pacific Social Science Review, 21(3), 249–259. https://apssr.com/volume-21-no-3/assessing-students-online-learning-readiness-are-college-freshmen-ready/
Ferri, F., Grifoni, P., & Guzzo, T. (2020). Online learning and emergency remote teaching: Opportunities and challenges in emergency situations. Societies, 10(4), 86. https://doi.org/10.3390/soc10040086
Fletcher, K. M. (2005). Self-efficacy as an evaluation measure for programs in support of online learning literacies for undergraduates. Internet and Higher Education, 8, 307–322. https://doi.org/10.1016/j.iheduc.2005.09.004
Garad, A., Al-Ansi, A. M., & Qamari, I. N. (2021). The role of e-learning infrastructure and cognitive competence in distance learning effectiveness during the COVID-19 pandemic. Cakrawala Pendidikan, 40(1), 81–91. https://doi.org/10.21831/cp.v40i1.33474
Gonçalves, S. P., Sousa, M. J., & Pereira, F. S. (2020). Distance learning perceptions from higher education students—the case of Portugal. Education Sciences, 10(12), 1–15. https://doi.org/10.3390/educsci10120374
Hachey, A. C., Wladis, C., & Conway, K. (2015). Prior online course experience and G.P.A. as predictors of subsequent online STEM course outcomes. Internet and Higher Education, 25, 11–17. https://doi.org/10.1016/j.iheduc.2014.10.003
Hafeez, M., Kazmi, Q. A., & Tahira, F. (2022). Challenges faced by the teachers and students in online learning during COVID-19. Cakrawala Pendidikan, 41(1), 55–70. https://doi.org/10.21831/cp.v41i1.35411
Harvey, H. L., Parahoo, S., & Santally, M. (2017). Should gender differences be considered when assessing student satisfaction in the online learning environment for millennials? Higher Education Quarterly, 71(2), 141–158. https://doi.org/10.1111/hequ.12116
Haverila, M. (2011). Prior E-learning experience and perceived learning outcomes in an undergraduate E-learning course. In MERLOT Journal of Online Learning and Teaching (Vol. 7, Issue 2). http://eduix.fi/web/briefly-in-english/
Hodges, C. B. (2008). Self-efficacy in the context of online learning environments: A review of the literature and directions for research. Performance Improvement Quarterly, 20(3–4), 7–25. https://doi.org/10.1002/piq.20001
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
Iglesias-Pradas, S., Hernández-García, Á., Chaparro-Peláez, J., & Prieto, J. L. (2021). Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study. Computers in Human Behavior, 119. https://doi.org/10.1016/j.chb.2021.106713
Joaquin, J. J. B., Biana, H. T., & Dacela, M. A. (2020). The Philippine higher education sector in the time of COVID-19. Frontiers in Education, 5. https://doi.org/10.3389/feduc.2020.576371
Johnson, R. D. (2011). Gender differences in E-learning: Communication, social presence, and learning outcomes. Journal of Organizational and End User Computing, 23(1), 79–94. https://doi.org/10.4018/joeuc.2011010105
Kasch, J., van Rosmalen, P., Löhr, A., Klemke, R., Antonaci, A., & Kalz, M. (2021). Students’ perceptions of the peer-feedback experience in MOOCs. Distance Education, 42(1), 145–163. https://doi.org/10.1080/01587919.2020.1869522
Kauffman, H. (2015). A review of predictive factors of student success in and satisfaction with online learning. Research in Learning Technology, 23. https://doi.org/10.3402/rlt.v23.26507
Kotrlik, J., Williams, H., & Jabor, K. (2011). Reporting and interpreting effect size in quantitative agricultural education research. Journal of Agricultural Education, 52(1), 132–142. https://doi.org/10.5032/jae.2011.01132
Lakhal, S., & Khechine, H. (2021). Technological factors of students’ persistence in online courses in higher education: The moderating role of gender, age and prior online course experience. Education and Information Technologies, 26(3), 3347–3373. https://doi.org/10.1007/s10639-020-10407-w
Malindog-Uy, A. R. (2020, June 7). Blended learning in virus-hit Philippines. The ASEAN Post. https://theaseanpost.com/article/blended-learning-virus-hit-philippines
Martin, F., & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning Journal, 22(1), 205–222. https://doi.org/10.24059/olj.v22i1.1092
Mertler, C. A. (2016). Introduction to educational research. SAGE Publications, Inc.
Muilenburg, L. Y., & Berge, Z. L. (2005). Students barriers to online learning: A factor analytic study. Distance Education, 26(1), 29–48. https://doi.org/10.1080/01587910500081269
Naji, K. K., Du, X., Tarlochan, F., Ebead, U., Hasan, M. A., & Al-Ali, A. K. (2020). Engineering students’ readiness to transition to emergency online learning in response to COVID-19: Case of Qatar. Eurasia Journal of Mathematics, Science and Technology Education, 16(10). https://doi.org/10.29333/EJMSTE/8474
Ní Shé, C., Farrell, O., Brunton, J., Costello, E., Donlon, E., & Eccles, S. (2019). Teaching online is different: Critical perspectives from the literature. https://doi.org/http://doi.org/10.5281/zenodo.3479402
Nortvig, A. M., Petersen, A. K., & Balle, S. H. (2018). A literature review of the factors influencing E-learning and blended learning in relation to learning outcome, student satisfaction and engagement. The Electronic Journal of E-Learning, 16(1), 46–55. www.ejel.org
Örs, M. (2018). The self-directed learning readiness level of the undergraduate students of midwife and nurse in terms of sustainability in nursing and midwifery education. Sustainability (Switzerland), 10(10). https://doi.org/10.3390/su10103574
Pelmin, M. A. (2020). Readings on coronavirus disease (COVID-19) and the higher education institution (HEIs) emergency preparedness in the Philippines. https://ssrn.com/abstract=3573896
Seiver, J. G., & Troja, A. (2014). Satisfaction and success in online learning as a function of the needs for affiliation, autonomy, and mastery. Distance Education, 35(1), 90–105. https://doi.org/10.1080/01587919.2014.891427
Shen, D., Cho, M. H., Tsai, C. L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. Internet and Higher Education, 19, 10–17. https://doi.org/10.1016/j.iheduc.2013.04.001
Sivo, S. A., & Ku, C.-H. (2018). Understanding how university student perceptions of resources affect technology acceptance in online learning courses. Australasian Journal of Educational Technology, 34(4), 72–91.
Suhandiah, S., Suhariadi, F., Yulianti, P., Wardani, R., & Muliatie, Y. E. (2022). Online learning satisfaction in higher education: what are the determining factors? Cakrawala Pendidikan, 41(2), 351–364. https://doi.org/10.21831/cp.v41i2.35724
Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on E-learning acceptance in England: A structural equation modeling approach for an extended Technology Acceptance Model. Journal of Educational Computing Research, 51(2), 163–184. https://doi.org/10.2190/EC.51.2.b
Toquero, C. M. (2021). Emergency remote education experiment amid COVID-19 pandemic in learning institutions in the Philippines. International Journal of Educational Research and Innovation, 15, 162–176. https://doi.org/https://doi.org/10.46661/ijeri.5113
Tsai, C. L., Cho, M. H., Marra, R., & Shen, D. (2020). The Self-Efficacy Questionnaire for Online Learning (SeQoL). Distance Education, 41(4), 472–489. https://doi.org/10.1080/01587919.2020.1821604
UNESCO Institute of Statistics. (2020). Dashboards on the global monitoring of school closures caused by the COVID-19 pandemic. https://covid19.uis.unesco.org/global-monitoring-school-closures-covid19/
Wang, C. H., Shannon, D. M., & Ross, M. E. (2013). Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning. Distance Education, 34(3), 302–323. https://doi.org/10.1080/01587919.2013.835779
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
Wenceslao, P., & Felisa, G. (2021). Challenges to online engineering education during the Covid-19 pandemic in Eastern Visayas, Philippines. International Journal of Learning, Teaching and Educational Research, 20(3), 84–96. https://doi.org/10.26803/ijlter.20.3.6
Wongwatkit, C., Panjaburee, P., Srisawasdi, N., & Seprum, P. (2020). Moderating effects of gender differences on the relationships between perceived learning support, intention to use, and learning performance in a personalized e-learning. Journal of Computers in Education, 7(2), 229–255. https://doi.org/10.1007/s40692-020-00154-9
Yavuzalp, N., & Bahcivan, E. (2020). The online learning self-efficacy scale: Its adaptation into Turkish and interpretation accroding to various variables. Turkish Online Journal of Distance Education, 21(3), 31–44.
Yukselturk, E., & Bulut, S. (2009). Gender differences in self-regulated online learning environment. Educational Technology & Society, 12(3), 12–22.
Zapata-Cuervo, N., Montes-Guerra, M. I., Shin, H. H., Jeong, M., & Cho, M. H. (2021). Students’ psychological perceptions toward online learning engagement and outcomes during the COVID-19 pandemic: A comparative analysis of students in three different countries. Journal of Hospitality and Tourism Education. https://doi.org/10.1080/10963758.2021.1907195
Zimmerman, W. A., & Kulikowich, J. M. (2016). Online learning self-efficacy in students with and without online learning experience. American Journal of Distance Education, 30(3), 180–191. https://doi.org/10.1080/08923647.2016.1193801
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Marissa Fearnley, Jose Noel Fabia, Dennis Caballes

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.