Online Learning Self-Efficacy as Correlates to Academic Procrastination among Pre-Service Teachers

Erika Arazo, Ma. Robelene Durana, Abegail Umali, & Rona Christina Almazan*
College of Teacher Education, Laguna State Polytechnic University, Philippines
DOI –
http://doi.org/10.37502/IJSMR.2023.6508

Abstract

This study investigates the relationship between academic procrastination and self-efficacy in online learning. The researchers noticed this phenomenon in a larger area because students put off finishing their academic assignments, putting off studying for exams despite being advised to do so beforehand, and presenting projects on time without procrastination or delay. To identify whether there is a correlation between academic procrastination and self-efficacy in online learning, researchers conducted the study. The respondents in this study were from the 5 majors of the third year of the Bachelor of Secondary Education. This study used a descriptive-correlational design. The results show that students who have high levels of self-efficacy are intrinsically driven and more likely to succeed in their efforts to finish the activities, which is not surprising. But even though pre-service teachers have high self-efficacy, this does not mean that they do not tend to procrastinate. Thus, a student’s decision to resist or run away from a task, such as an individual or group assignment, a midterm, or a final test, indicated their level of academic self-efficacy. According to the study’s findings and conclusions, the researchers recommend that for the students to stay on track and avoid procrastination, they can use tools or productivity apps like Forest, Pomodoro, and similar ones. They might also provide them with a checklist so they can keep track of the tasks and activities they should prioritize.

Keywords: Online Learning Self-Efficacy, Academic Procrastination, Pre-service Teachers.

References

  • Achukwu, C. B., Nwosu, K. C., Uzoekwe, H. E. and Juliana, A., 2015. Computer self-efficacy, computer-related technology dependence and online learning readiness of undergraduate students. International Journal of Higher Education Management, 1(2), pp.60-71.
  • Aliazas, J. V., Panoy, J. F., Del Rosario, A. L., & Madrideo, J. (2021). Critical Success Factors of the Flexible Learning Delivery as Organizational Innovation of One State University in the Philippines. International Journal of Educational Management and Development Studies2(3), 61-77.
  • AlQudah, M. F., Alsubhien, A. M., & Heilat, M. Q. A. (2014). The relationship between academic procrastination and self-efficacy among a sample of King Saud University Students. Journal of education and practice, 5(16), 101-111.
  • Alqurashi, E. (2016). Self-efficacy in online learning environments: A literature review. Contemporary Issues in Education Research (CIER), 9(1), 45–52. https://doi.org/10.19030/cier.v9i1.9549
  • Attia, N. M., & Abdelwahid, A. E. (2020). Grit, Self-regulation, and self-efficacy as predictors of academic procrastination among nursing students. Amarjeet Kaur Sandhu, 12(1), 130-142.
  • Bailie, J. (2019). Effect of pre-term course access on online learner performance. Retrieved from https://purdueglobal.dspacedirect.org/handle/20.500.12264/14
  • Barrows, J., Dunn, S., & Lloyd, C. A. (2013). Anxiety, Self-Efficacy, and College Exam Grades. Universal Journal of Educational Research, 1(3), 204-208.
  • Broadbent, J. (2016). Academic success is about self-efficacy rather than the frequency of use of the learning management system. Australasian Journal of Educational Technology, 32(4), 10.14742/ajet.2634.
  • Calaguas, N.P., & Consunji, P. M. P. (2022). A structural equation model predicting adults’ online learning self-efficacy. Education and Information Technologies, 1-17.
  • Carada, I., Aliazas, J. V., Palacio, L., & Palacio, C. M. A. (2022). Perceived Skills and Employability of Senior High School Graduates: Basis for Youth Employment Policy. International Journal of Social Sciences and Humanities Invention9(01), 6759-6766.
  • Chen, I.-S., 2017. Computer self-efficacy, learning performance, and the mediating role of learning engagement. Computers in Human Behavior, 72, pp.362-370.
  • Chen, T., Peng, L., Yin, X., Rong, J., Yang, J., & Cong, G. (2020, July 7). Healthcare | Analysis of User Satisfaction with Online Education Platforms In China During the COVID-19 Pandemic. Retrieved from https://www.mdpi.com/2227-9032/8/3/200#cite.
  • Chung, E., Subramaniam, G., & Dass, L. C. (2020). Online learning readiness among university students in Malaysia amidst COVID-19. Asian Journal of University Education, 16(2), 46-58. Retrieved from https://eric.ed.gov/?id=EJ1267359
  • Cussó-Calabuig, R., Farran, X. C., and Bosch-Capblanch, X. (2018). Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: a systematic review. Educ. Inf. Technol. 23, 2111–2139. DOI: 10.1007/s10639-018-9706-6
  • Dhawan, S. (2020). Online Learning: A Panacea in the Time of COVID-19 Crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
  • Ge, C., Li, C. D., and Li, S. J. (2018). Study on the relationship between junior high school students’ self-efficacy and academic procrastination. J. Zhoukou Norm. Univ. 35, 146–152
  • Hong, J. C., Lee, Y. F., & Ye, J. H. (2021). Procrastination predicts online self-regulated learning and online learning ineffectiveness during the coronavirus lockdown. Personality and individual differences, 174, 110673
  • Honicke, T., and Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: a systematic review. Educ. Res. Rev. 17, 63–84. doi: 10.1016/j.edurev.2015.11.002
  • https://mb.com.ph/2020/10/05/flexible-e-learning-buses-launched-in-laguna/
  • Klassen, R. M., Krawchuk, L. L., & Rajani, S. (2008). Academic procrastination of undergraduates: Low self-efficacy to self-regulate predicts higher levels of procrastination. Contemporary Educational Psychology, 33(4), 915-931.
  • Kattoua, Tagreed, Musa Al-Lozi, and Ala’aladin Alrowwad. 2016. ” A Review of Literature on E-learning Systems in Higher Education.” International Journal of Business Management & Economic Research 7 (5): 754-762.
  • Lee, J. W., & Mendlinger, S. (2011). Perceived self-efficacy and its effect on online learning acceptance and student satisfaction. Journal of Service Science and Management, 4(03), 243.
  • Martin, F., Tutty, J. I., & Su, Y. (2010). Influence of Learning Management Systems Self-Efficacy on E-Learning Performance. Journal on School Educational Technology, 5(3), 26–35 https://files.eric.ed.gov/fulltext/EJ1102894.pdf
  • McCloskey, J., & Scielzo, S. A. (2015). Finally: The development and validation of the academic procrastination scale. Manuscript submitted for publication.
  • Murray, M. C., Pérez, J., Geist, D., & Hedrick, A. (2012). Student interaction with online course content: Build it and they might come. Journal of Information Technology Education: Research, 11(1), 125-140.
  • Nielsen, T., Dammeyer, J., Vang, M. L., & Makransky, G. (2018). Gender fairness in self-efficacy? A Rasch-based validity study of the General Academic Self-efficacy scale (GASE). Scandinavian Journal of Educational Research, 62(5), 664–681. https://doi.org/10.1080/00313831.2017.1306796
  • Ocak, G., & Boyraz, S. (2016). Examination of the Relation between Academic Procrastination and Time Management Skills of Undergraduate Students in Terms of Some Variables. Journal of Education and Training Studies, 4(5), 76-84.
  • Oranburg, S. (2020). Distance Education in the Time of Coronavirus: Quick and Easy Strategies for Professors. Legal Studies Research Paper Series. Duquesne University School of Law Research Paper, 2020-02.
  • Panergayo, A. A. E., & Aliazas, J. V. C. (2021). Students’ Behavioral Intention to Use Learning Management System: The Mediating Role of Perceived Usefulness and Ease of Use. International Journal of Information and Education Technology11(11).
  • Pellas, N., 2014. The influence of computer self-efficacy, metacognitive self-regulation, and self-esteem on student engagement in online learning programs: evidence from the virtual world of Second Life. Computers in Human Behavior, 35, pp.157-170.
  • Reyes, A., & Aliazas, J. V. (2021). Online Integrative Teaching Strategies: Thematic and Focus Inquiry for Improved Science Process Skills. International Journal of Science, Technology, Engineering and Mathematics1(2), 19-38.
  • Sabharwal, R., M. Hossain, R. Chugh, and M. Wells. 2018. “Learning Management System in the Workplace: A Literature Review.” Paper presented at the 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 387-393. Wollongong December 4-7. [Crossref], [Google Scholar]
  • Schunk, D. H., & Pajares, F. (2009). Self-efficacy theory. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motivation at school (pp. 35–53). Routledge.
  • Sison, E., Doloque, E., Santor, K., Rayla, N., Capagalan, S., & Tus, J. (2021). Amidst Online Learning: The Self-Efficacy and Academic Motivation of the College Students from the Public Higher Education Institutions in the Philippines. International Journal of Advance Research and Innovative Ideas in Education.
  • Strunk, K. K., Cho, Y. J., Steele, M. R., and Bridges, S. L. (2013). Development and validation of a 2 x 2 model of time-related academic behavior: Procrastination and timely engagement. Learn. Individ. Diff. 25, 35–44. doi: 10.1016/j.lindif. 2013.02.007
  • Talsma, K., Schüza, B., Schwarzerc, R., and Norrisa, K. (2018). I believe; therefore, I achieve (and vice versa): a meta-analytic cross-lagged panel analysis of self-efficacy and academic performance. Learn. Individ. Differ. 61, 136–150. doi: 10.1016/j.lindif.2017.11.015
  • Tsai, C. C., Chuang, S. C., Liang, J. C., & Tsai, M. J. (2011). Self-efficacy in Internet-based learning environments: A literature review. Journal of Educational Technology & Society, 14(4), 222–240 https://www.jstor.org/stable/pdf/jeductechsoci.14.4.222.pdfReturn to ref 2011 in article
  • Wu, J.-H., Tennyson, R. D. and Hsia, T.-L., 2010. A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), pp.155-164.
  • Zhang, S. M., and Feng, T. Y. (2020). Modeling procrastination: asymmetric decisions to act between the present and the future. J. Exp. Psychol. Gen. 149, 311–322. doi: 10.1037/xge0000643