Self-Determined Learning, Digital Competence, and Learning Styles as Predictors of Students' Attitudes toward Flipped Learning

Authors

DOI:

https://doi.org/10.61255/itej.v4i1.1116

Keywords:

Digital competence, Flipped learning, Learning style, PLS-SEM, Self-determined learning

Abstract

Flipped learning effectiveness depends heavily on student attitudinal acceptance, yet prior research has typically examined its determinants in isolation focusing separately on technology acceptance, self-regulation, or learning preferences. This study proposes and tests an integrated structural model linking Self-Determined Learning (SDL), Digital Competence (DC), and Learning Style (LS) to students' attitudes toward flipped learning (SFLIPP) among undergraduates in Indonesian higher education. A cross-sectional survey was administered to 395 students, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS SEM). The measurement model demonstrated robust reliability and validity (AVE > .50; CR > .838; HTMT < .90). Results showed that Learning Style was the strongest direct predictor of attitudes (β = .413, p < .001), followed by Digital Competence (β = .190, p < .001) and Self-Determined Learning (β = .164, p < .001). SDL exerted a substantial total effect on SFLIPP (β = .535), with approximately 69.3% of this effect mediated indirectly predominantly through LS (71.4% of the mediated portion) rather than DC (28.6%). The model explained 42.7% of the variance in attitudes. These findings indicate that fostering positive attitudes toward flipped learning requires a holistic approach that simultaneously strengthens student agency, cultivates responsible digital competence, and ensures pedagogical preference alignme.

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References

Abeysekera, L., & Dawson, P. (2015). Motivation and cognitive load in the flipped classroom: Definition, rationale and a call for research. Higher Education Research and Development, 34(1), 126–141. https://doi.org/10.1080/07294360.2014.934336

Akçayır, G., & Akçayır, M. (2018). The flipped classroom: A review of its advantages and challenges. Computers & Education, 126, 334–345. https://doi.org/10.1016/j.compedu.2018.07.021

Alyoussef, I. Y. (2022). Acceptance of a flipped classroom to improve university students' learning: An empirical study on the TAM model and the unified theory of acceptance and use of technology (UTAUT). Heliyon, 8(12), e12529. https://doi.org/10.1016/j.heliyon.2022.e12529

Amiruddin, A., Nurlaela, N., Hasim, M., & Setialaksana, W. (2022). Pedagogi, andragogi dan heutagogi sebagai kontinum di perguruan tinggi: Deskripsi dan model pengukuran. Jurnal Nalar Pendidikan, 10(2), 80–86.

Ayuningsih, R. F., Andrianto, D., & Kurniawan, W. (2025). Integrasi model pembelajaran blended learning dan flipped classroom: Strategi efektif dalam pembelajaran abad ke-21. STRATEGY: Jurnal Inovasi Strategi Dan Model Pembelajaran, 5(1), 10–21.

Blaschke, L. M. (2012). Heutagogy and lifelong learning: A review of heutagogical practice and self-determined learning. International Review of Research in Open and Distance Learning, 13(1), 56–71. https://doi.org/10.19173/irrodl.v13i1.1076

Chen, F., Lui, A. M., & Martinelli, S. M. (2017). A systematic review of the effectiveness of flipped classrooms in medical education. Medical Education, 51(6), 585–597. https://doi.org/10.1111/medu.13288

Fan, S., & Wang, Y. (2022). Development and validation of a digital skills scale for university students in the context of developing countries. Education and Information Technologies, 27(9), 12345–12367. https://doi.org/10.1007/s10639-022-11234-5

Felder, R. M., & Silverman, L. K. (1988). Learning and teaching styles in engineering education. Engineering Education, 78(7), 674–681.

Felder, R. M., & Spurlin, J. (2005). Applications, reliability and validity of the index of learning styles. International Journal of Engineering Education, 21(1), 103–112.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-013-0403-8

Ilomäki, L., Paavola, S., Lakkala, M., & Kantosalo, A. (2016). Digital competence—An emergent boundary concept for policy and educational research. Education and Information Technologies, 21(3), 655–679. https://doi.org/10.1007/s10639-014-9346-4

Kapur, M., Hattie, J., GrossHewman, I., & Sinha, T. (2022). Fail, flip, fix, and feed – Rethinking flipped learning: A review of meta-analyses and a subsequent meta-analysis. Frontiers in Education, 7, 956416. https://doi.org/10.3389/feduc.2022.956416

Karabulut-Ilgu, A., Jaramillo Cherrez, N., & Jahren, C. T. (2018). A systematic review of research on the flipped learning method in engineering education. British Journal of Educational Technology, 49(3), 398–411. https://doi.org/10.1111/bjet.12548

Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1–10. https://doi.org/10.4018/IJeC.2015100101

Koh, J. H. L. (2019). Four pedagogical dimensions for understanding flipped classroom practices in higher education: A systematic review. Educational Sciences: Theory and Practice, 19(4), 14–33. https://doi.org/10.12738/estp.2019.4.002

Nurlaela, N., Irfan, A. M., Rahman, M. H., Putra, K. P., Mahmud, A., & Setialaksana, W. (2025). Understanding AR/VR adoption through heutagogy and cybergogy: Insights from the UTAUT2 model in vocational education. Education and Information Technologies, 30(12), 17111–17132. https://doi.org/10.1007/s10639-025-13465-0

O'Flaherty, J., & Phillips, C. (2015). The use of flipped classrooms in higher education: A scoping review. Internet and Higher Education, 25, 85–95. https://doi.org/10.1016/j.iheduc.2015.02.002

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68

Sarstedt, M., & Cheah, J. H. (2019). Partial least squares structural equation modeling using SmartPLS: A software review. Journal of Marketing Analytics, 7(3), 196–202. https://doi.org/10.1057/s41270-019-00058-3

Strelan, P., Osborn, A., & Palmer, E. (2020). The flipped classroom: A meta-analysis of effects on student performance across disciplines and education levels. Educational Research Review, 30, 100314. https://doi.org/10.1016/j.edurev.2020.100314

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart Learning Environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x

van Alten, D. C. D., Phielix, C., Janssen, J., & Kester, L. (2020). Self-regulated learning support in flipped learning videos enhances learning outcomes. Computers and Education, 158, 104000. https://doi.org/10.1016/j.compedu.2020.104000

Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926

Vuorikari, R., Punie, Y., Carretero, S., & Van Den Brande, L. (2016). DigComp 2.0: The Digital Competence Framework for Citizens. Publications Office of the European Union. https://doi.org/10.2791/11517

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Published

2026-05-08

How to Cite

Rahman, M. H., Amiruddin, & Nurlaela. (2026). Self-Determined Learning, Digital Competence, and Learning Styles as Predictors of Students’ Attitudes toward Flipped Learning. Indonesian Technology and Education Journal, 4(1), 102–112. https://doi.org/10.61255/itej.v4i1.1116

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