Analysis Of Undergraduate Student’s Self Regulated Learning And Motivation In Online Learning
Abstract
All universities that are forced to conduct online learning due to pandemic era greatly affects the interpersonal conditions of students. This changing also influences student’s performance quality. The paper presents a descriptive quantitative which aims to explore: 1) differences in self-regulated learning between cumlaude and non-cumlaude students, 2) differences in learning motivation between cumlaude and non-cumlaude students, 3) correlations of self-regulated learning, learning motivation, and achievement in cumlaude students, and 4) correlation of self-regulated learning, learning motivation, and achievement in non-cumlaude students. The data collection technique used a questionnaire technique with instruments in the form of a self-regulated learning and learning motivation questionnaire, both of which were adapted questionnaires. The data obtained were then analyzed using the free sample t test and correlation test using the SPSS program. The results obtained indicate that: 1) there are differences in self-regulated learning between cum laude and non-cum laude students, 2) there are differences in learning motivation between cum laude and non-cum laude students, 3) there is a correlation between self-regulated learning, learning motivation, and achievement in cum laude students, and 4) there is no correlation between self-regulated learning, learning motivation, and learning outcome in non-cumlaude students.
Downloads
References
Asmuni, A. (2020). Problematika pembelajaran daring di masa pandemi covid-19 dan solusi pemecahannya. Jurnal Paedagogy, 7(4), 281–288. https://doi.org/10.33394/jp.v7i4.2941
Baldan Babayigit, B., & Guven, M. (2020). Self-regulated learning skills of undergraduate students and the role of higher education in promoting self-regulation. Eurasian Journal of Educational Research, 89, 47–70. https://doi.org/10.14689/ejer.2020.89.3
Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Taylor & Francis Group.
Corbeil, J. R., & Corbeil, M. E. (2015). E-learning: Past, present, and future. In B. H. Khan & M. Ally (Eds.), International Handbook of E-learning. Routledge. https://doi.org/10.4324/9781315760933.ch3
Diningrat, S. W. M., Nindya, M. A., & Salwa. (2020). Emergency online teaching: Early childhood education lecturers’ perception of barrier and pedagogical competency. Cakrawala Pendidikan, 39(3), 705–719. https://doi.org/10.21831/cp.v39i3.32304
Dron, J. (2018). Smart learning environments , and not so smart learning environments : a systems view. Smart Learning Environments, 5(25), 1–20. https://doi.org/https://doi.org/10.1186/s40561-018-0075-9
Gaumer Erickson, A. S., & Noonan, P. M. (2017). The skills that matter: Teaching interpersonal and intrapersonal competencies in any classroom (1st ed.). Corwin.
Giatman, M., Siswati, S., & Basri, I. Y. (2020). Online learning quality control in the pandemic covid-19 era in Indonesia. Journal of Nonformal Education, 6(2), 168–175.
Harandi, S. R. (2015). Effects of e-learning on students ’ motivation. Procedia-Social and Behavioral Sciences, 181(October), 423–430. https://doi.org/10.1016/j.sbspro.2015.04.905
Krejcie, R. V, & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607–610. https://doi.org/10.1891/9780826138446.0006
Muslimin, A. I., & Harintama, F. (2020). Online learning during pandemic: Students’ motivation, challenges, and alternatives. Loquen: English Studies Journal, 13(2), 60. https://doi.org/10.32678/loquen.v13i2.3558
Pintrich, R. R., & DeGroot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40. https://doi.org/10.5901/mjss.2015.v6n1p156
Saxena, R., Bhat, V., & Jhingan, A. (2017). Leapfrogging to student at the core. In Federation of Indian Chambers of Commerce and Industry (Issue November).
Sharif, T., Hossan, C. G., & McMinn, M. (2014). Motivation and determination of intention to become teacher: A case of B.Ed. students in UAE. International Journal of Business and Management, 9(5). https://doi.org/10.5539/ijbm.v9n5p60
Wandler, J. B., & Imbriale, W. J. (2017). Promoting undergraduate student self-regulation in online learning environments. Online Learning Journal, 21(2), 1–16. https://doi.org/10.24059/olj.v21i2.881
Widjaja, A. E., & Chen, J. V. (2017). Online learners’ motivation in online learning: The effect of online-participation, social presence and collaboration. In C. Muniarti & R. Sanjaya (Eds.), Learning Technologies in Education: Issues and Trends (Issue December, pp. 72–93). Soegijapranata Catholic Univeristy.
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
Yu, Z. (2021). The effects of gender , educational level , and personality on online learning outcomes during the COVID ‑ 19 pandemic. International Journal of Educational Technology in Higher Education, 18(14), 1–17. https://doi.org/10.1186/s41239-021-00252-3
Copyright (c) 2021 FKIP Universitas Palangka Raya
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright Ⓒ Author