The Moderating Role of Self-Efficacy on the Effectiveness of LMS-Based Learning Modules toward Student Learning Outcomes: A Pre-Experimental Study at SMP Laboratorium UM
DOI:
https://doi.org/10.21009/jtp.v25i2.67389Keywords:
learning management system, self-efficacy, learning outcomes, e-module, moderated regression analysisAbstract
This research aims to investigate the moderating role of self-efficacy using a pre-experimental one-group pretest-posttest design. Data were collected through cognitive achievement tests (pretest and posttest), a Likert-scale questionnaire measuring perceived LMS module effectiveness, and a self-efficacy questionnaire grounded in Bandura’s three-dimensional framework (magnitude, generality, and strength). Data analysis included paired sample t-tests, Wilcoxon Signed-Rank tests, Spearman correlations, and Moderated Regression Analysis (MRA). Results indicated a statistically significant improvement in learning outcomes following the LMS-based module intervention (t(26) = −8.32, p < .001, Cohen’s d = 1.60). However, neither perceived LMS effectiveness nor self-efficacy demonstrated significant correlations with posttest scores. The moderation analysis revealed that self-efficacy did not significantly moderate the relationship between LMS effectiveness and learning outcomes (R² = .006, p = .839). These findings suggest that while LMS-based modules effectively enhance cognitive achievement, the homogeneity of self-efficacy levels and ceiling effects in posttest scores may have constrained the detection of moderation effects.
References
Alemayehu, L., & Chen, H. L. (2023). The influence of motivation on learning engagement: The mediating role of learning self-efficacy and self-monitoring in online learning environments. Interactive Learning Environments, 31(7), 4605–4618. https://doi.org/10.1080/10494820.2021.1977962
Arikunto, S. (2019). Prosedur penelitian: Suatu pendekatan praktik. Rineka Cipta.
Aulianda, N., Wijayati, P. H., Ebner, M., & Schön, S. (2023). The analysis of learning management system towards students’ cognitive learning outcome: A systematic literature review. International Journal of Emerging Technologies in Learning, 18(23), 210–229. https://doi.org/10.3991/ijet.v18i23.36443
Azwar, S. (2017). Reliabilitas dan validitas. Pustaka Pelajar.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
Cao, W. (2023). A meta-analysis of effects of blended learning on performance, attitude, achievement, and engagement across different countries. Frontiers in Psychology, 14, 1212056. https://doi.org/10.3389/fpsyg.2023.1212056
Cavus, N. (2015). Distance learning and learning management systems. Procedia—Social and Behavioral Sciences, 191, 872–877. https://doi.org/10.1016/j.sbspro.2015.04.611
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Lawrence Erlbaum Associates.
Daryanto. (2013). Menyusun modul bahan ajar untuk persiapan guru dalam mengajar. Gava Media.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Egara, F. O., & Mogege, M. (2024). Effect of blended learning approach on secondary school learners’ mathematics achievement and retention. Education and Information Technologies, 29(14), 18189–18210. https://doi.org/10.1007/s10639-024-12651-w
Gagné, R. M. (1985). The conditions of learning and theory of instruction (4th ed.). Holt, Rinehart and Winston.
Guntur, M., & Purnomo, Y. W. (2024). A meta-analysis of self-regulated learning interventions studies on learning outcomes in online and blended environments. Online Learning Journal, 28(1), 1–25.
Han, F. (2023). Evaluating blended learning effectiveness: An empirical study from undergraduates’ perspectives using structural equation modeling. Frontiers in Psychology, 14, 1059282. https://doi.org/10.3389/fpsyg.2023.1059282
Honicke, T., Broadbent, J., & Fuller-Tyszkiewicz, M. (2023). The self-efficacy and academic performance reciprocal relationship: The influence of task difficulty and baseline achievement on learner trajectory. Higher Education Research & Development, 42(8), 1936–1953. https://doi.org/10.1080/07294360.2023.2197194
Jin, S. H., Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 37. https://doi.org/10.1186/s41239-023-00406-5
Johar, N. A., Kew, S. N., Tasir, Z., & Koh, E. (2023). Learning analytics on student engagement to enhance students’ learning performance: A systematic review. Sustainability, 15(10), 7849. https://doi.org/10.3390/su15107849
Joksimovic, S., Kovanovic, V., Gasevic, D., Dawson, S., & Siemens, G. (2015). The history and state of online learning. In Preparing for the digital university (pp. 93–132). Athabasca University.
Kemendikbudristek. (2023). Data pemanfaatan platform digital di sekolah menengah Indonesia [Data on digital platform utilization in Indonesian secondary schools]. Ministry of Education, Culture, Research and Technology.
Lin, Y. P., & Yu, Z. G. (2023). Extending technology acceptance model to higher-education students’ use of digital academic reading tools on computers. International Journal of Educational Technology in Higher Education, 20, 34. https://doi.org/10.1186/s41239-023-00403-8
Mahnegar, F. (2012). Learning management system. International Journal of Business and Social Science, 3(12), 144–150.
Mailizar, M., Burg, D., & Maulina, S. (2021). Examining university students’ behavioural intention to use e-learning during the COVID-19 pandemic: An extended TAM model. Education and Information Technologies, 26(6), 7057–7077. https://doi.org/10.1007/s10639-021-10557-5
Nafiati, D. A. (2021). Revisi taksonomi Bloom: Kognitif, afektif, dan psikomotorik. Humanika: Kajian Ilmiah Mata Kuliah Umum, 21(2), 151–172. https://doi.org/10.21831/hum.v21i2.29252
Nguyen, T. T. H., Tran, T. T., & Nguyen, H. T. T. (2024). What contributes to student language learning satisfaction and achievement with learning management systems? Behavioral Sciences, 14(4), 271. https://doi.org/10.3390/bs14040271
Pan, Z., Biegley, L., Taylor, A., & Zheng, H. (2024). A systematic review of learning analytics: Incorporated instructional interventions on learning management systems. Journal of Learning Analytics, 11(2), 52–72. https://doi.org/10.18608/jla.2023.8093
Saptono, A., Wibowo, A., Narmaditya, B. S., Karyaningsih, R. P. D., & Shafiai, M. H. M. (2024). Using technology acceptance model to investigate digital business intention among Indonesian students. Cogent Business & Management, 11(1), 2314253. https://doi.org/10.1080/23311975.2024.2314253
Suartini, K., Ardiansyahroni, A., Nyaman, R., Riyadi, & Sarifah, I. (2023). Meta-analysis: Hubungan antara self-efficacy dan academic achievement. Jurnal Ilmu Sosial dan Pendidikan, 7(3), 133–148. https://doi.org/10.58258/jisip.v7i3.5467
Sugiyono. (2021). Metode penelitian pendidikan: Pendekatan kuantitatif, kualitatif, dan R&D. Alfabeta.
Talsma, K., Robertson, K., Thomas, C., & Norris, K. (2021). COVID-19 beliefs, self-efficacy and academic performance in first-year university students: Cohort comparison and mediation analysis. Frontiers in Psychology, 12, 643408. https://doi.org/10.3389/fpsyg.2021.643408
UNESCO. (2022). Global education monitoring report 2022: Technology in education. UNESCO Publishing.
Watson, W. R., & Watson, S. L. (2007). An argument for clarity: What are learning management systems, what are they not, and what should they become? TechTrends, 51, 28–34. https://doi.org/10.1007/s11528-007-0023-y
Zh, M. H. R., Sani, N. L., Kuswandi, D., & Fadhli, M. (2024). Needs analysis of development FBO media as a support for blended learning in Al-Qur’an Hadits lesson. Jurnal Pendidikan Agama Islam Al-Thariqah, 9(1), 16–32. https://doi.org/10.25299/al-thariqah.2024.vol9(1).16889
Zhang, Z., Xu, Q., Koehler, A. A., & Newby, T. (2023). Comparing blended and online learners’ self-efficacy, self-regulation, and actual learning in the context of educational technology. Online Learning Journal, 27(4), 295–314. https://doi.org/10.24059/olj.v27i4.4039
Zysberg, L., & Schwabsky, N. (2021). School climate, academic self-efficacy and student achievement. Educational Psychology, 41(4), 467–482. https://doi.org/10.1080/01443410.2020.1813690
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