The Effect of Distance Education on Self-efficacy towards Online Technologies and Motivation for Online Learning
Abstract
This research aimed to investigate the effect of distance education during the COVID-19 pandemic on psychological counselor candidates’ self-efficacy perceptions towards online technologies and their motivation for online learning. Single group pretest-posttest model, a quantitative method, was used in the research. The study participants were third-year students at the Faculty of Education, Psychological Counseling and Guidance Department of a state university in the fall semester of 2020-2021. Demographic Information Form, Online Technologies Self-Efficacy Scale and Online Motivation Scale were used as data collection tools. As a result of the research, it was observed that the psychological counselor candidates’ self-efficacy for online technologies and online learning motivation scores were above the average. It was concluded that the distance education used during the COVID-19 pandemic caused a statistically significant difference in psychological counselor candidates’ self-efficacy towards online technologies, but did not cause a difference in their online learning motivation. There was no significant difference in self-efficacy according to gender and place of residence. However, while there was no significant difference in motivation according to gender, a significant difference was observed in regards to the place of residence in favor of citycenter. It is important to present psychological counselor candidates’ perceptions and motivations in regards to distance education, which is an ongoing process at the moment, for their professional development.
Keywords
Distance education, online technologies, motivation, self-efficacy, psychological counselor candidate
References
- Alemayehu, L., & Chen, H. L. (2021). The influence of motivation on learning engagement: the mediating role of learning self-efficacy and self-monitoring in online learning environments. Interactive Learning Environments, 1-14. https://doi.org/10.1080/10494820.2021.1977962
- Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research, 9(1), 45-52. https://doi.org/10.19030/cier.v9i1.9549
- Apriana, A., & Hidajat, D. (2020). Analysis of Google Classroom's online learning motivation on mathematics subjects. Journal of Mathematical Pedagogy (JoMP), 2(1), 18-25. https://doi.org/10.26740/jomp.v2n1.p%25p
- Apriyanti, C. (2020). Distance learning and obstacles during Covid-19 outbreak. Jurnal Ilmiah Pendidikan Dasar, 7(2), 68-83. http://dx.doi.org/10.30659/pendas.7.2.68-83
- Bandura, A. (1971). Psychological modeling: Conflicting theories. Chicago: Aldine-Atherton.
- Bates, A. W. T. (2018). Teaching in a digital age: Guidelines for designing teaching and learning. Tony Bates Associates Ltd, Vancouver BC.
- Cabı, E., & Ersoy, H. (2017). Analysis of distance education practices in higher education: The example of Turkey. Journal of Higher Education and Science, 7(3), 419-429. Doi: 10.5961/jhes.2017.219
- Cai, S., & Zhu, W. (2012). The impact of an online learning community project on university Chinese as a foreign language students’ motivation. Foreign Language Annals, 45(3), 307-329. https://doi.org/10.1111/j.1944-9720.2012.01204.x
- Chang, C. S., Liu, E, Z.-F., Sung, H. Y., Lin, C. H., Chen, N. H., & Cheng, S. S. (2014). Effects of online college student’s Internet self-efficacy on learning motivation and performance. Innovations in Education and Teaching International, 51(4), 366-377, Doi: 10.1080/14703297.2013.771429
- Chen, K., & Jang, S. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741-752. https://doi.org/10.1016/j.chb.2010.01.011