Factors influencing vocational teachers’ e-Learning adoption: A technology acceptance model approach

Authors

DOI:

https://doi.org/10.21831/jpv.v15i2.86375

Keywords:

adoption, behavioral intention, e-learning, Technology Acceptance Model (TAM), vocational teachers

Abstract

The rapid expansion of digital learning environments has encouraged schools to integrate e-learning into teaching practices. However, many vocational teachers still show uneven levels of adoption, indicating that the factors shaping their willingness and actual use of e-learning require deeper investigation. This study examines the determinants of vocational teachers’ e-learning adoption using the Technology Acceptance Model (TAM), focusing on the roles of perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention (BI), and actual use (AU). A quantitative survey was administered to 118 vocational high school teachers, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that PEOU significantly influences both PU and BI, while PU also exerts a positive effect on BI. Furthermore, BI demonstrates a strong and significant effect on AU, mediating the relationships between PU, PEOU, and AU. Overall, the model explains a substantial proportion of variance in teachers’ behavioral intention and actual use of e-learning. These results confirm the robustness of TAM in vocational education contexts and highlight that teachers are more likely to use e-learning when they perceive it as easy, useful, and aligned with their instructional needs. Practically, the study suggests that vocational schools should strengthen digital literacy training, provide technical support, and design user-friendly platforms to enhance teachers’ confidence and motivation. At the policy level, establishing clear digital competence standards may foster sustainable e-learning adoption across vocational institutions.

References

Al Kurdi, B., Alshurideh, M., & Salloum, S. (2020). Investigating a theoretical framework for e-learning technology acceptance. International Journal of Electrical and Computer Engineering (IJECE), 10, 6484–6496. https://doi.org/10.11591/ijece.v10i6.pp6484-6496

Almulla, M. (2021). Technology Acceptance Model (TAM) and E-Learning System Use for Education Sustainability. Academy of Strategic Management Journal, 20(4), 1–801.

Casey, J. D., Beskow, L. M., Brown, J., Brown, S. M., Gayat, É., Ng Gong, M., Harhay, M. O., Jaber, S., Jentzer, J. C., Laterre, P.-F., Marshall, J. C., Matthay, M. A., Rice, T. W., Rosenberg, Y., Turnbull, A. E., Ware, L. B., Self, W. H., Mebazaa, A., & Collins, S. P. (2022). Use of pragmatic and explanatory trial designs in acute care research: Lessons from COVID-19. The Lancet Respiratory Medicine, 10(7), 700–714. https://doi.org/10.1016/S2213-2600(22)00044-3

Creswell, J. W. (2019). Research Desain: Pendekatan Metode, Kualitatif, Kuantitatif, dan Campuran (4th ed.). Pustaka Pelajar.

Dash, G. (2023). Pandemic Induced E-Learning and the Impact on the Stakeholders: Mediating Role of Satisfaction and Moderating Role of Choice. Athens Journal of Education, 10(1), 27–48. Scopus. https://doi.org/10.30958/aje.10-1-2

Dash, G., & Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Research Center, University of Minnesota.

Hadromi, H., Widjanarko, D., Kurniawan, A., Budiman, F., Amron, H., Irawan, D., Surya, M., & Gendroyono, R. (2022). Online Teaching and Learning Platform at Vocational Education in Semarang-Indonesia (pp. 187–197). https://doi.org/10.2991/978-2-494069-47-3_24

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (Eighth edition). Cengage.

Im, T. (2021). Online and blended learning in vocational training institutions in South Korea. Knowledge Management and E-Learning, 13(2), 194–208. Scopus. https://doi.org/10.34105/j.kmel.2021.13.011

Isnaini, R., Budiyanto, C. W., & Widiastuti, I. (2020). E-LEARNING IMPLEMENTATION IN VOCATIONAL TRAINING EDUCATION WITH HANDS-ON LEARNING. Journal of Mechanical Engineering and Vocational Education (JoMEVE), 3(1), Article 1. https://doi.org/10.20961/jomeve.v3i1.45971

Karisma, I. G. P. Y. A., & Gui, A. (2023). UNDERSTANDING E-LEARNING SYSTEM ACCEPTANCE: AN EMPIRICAL ANALYSIS OF KEY FACTORS AMONG ELEMENTARY SCHOOL STUDENTS USING TAM MODEL. Jurnal TAM (Technology Acceptance Model), 14(2), Article 2. https://doi.org/10.56327/jurnaltam.v14i2.1599

Khan, T., Nag, A. K., Joshi, B., Acharya, R., & Thomas, S. (2021). Influencing Factors of Behavior Intention and Actual Use of Technology: An Application of UTAUT Model on Science Undergraduates. Journal of Higher Education Theory and Practice, 21(13), 89–103. Scopus. https://doi.org/10.33423/jhetp.v21i13.4792

Lobo, J. (2023). THE INTERSECTION OF MUSIC AND ARTS EDUCATION AND TECHNOLOGY: ASSESSING GOOGLE MEET’S USABILITY IN A CASE OF A PROMINENT LOCAL COLLEGE. Artseduca, 35, 99–114. Scopus. https://doi.org/10.6035/artseduca.7053

Lobo, J., Prevandos, F. G., Tanucan, J. C., & Setiawan, E. (2024). Is Video-Conferencing Helpful for Physical Education Classes in the New Normal? A PLS-SEM Analysis Adopting the Technology Acceptance Model. Journal of Learning for Development, 11(1), 99–114. Scopus. https://doi.org/10.56059/jl4d.v11i1.1125

Mutambara, D., & Bayaga, A. (2020). Understanding Rural Parents’ Behavioral Intention to Allow Their Children to Use Mobile Learning. In Hattingh M., Matthee M., Smuts H., Pappas I., Dwivedi Y.K., & Mäntymäki M. (Eds.), Lect. Notes Comput. Sci.: Vol. 12066 LNCS (pp. 520–531). Springer; Scopus. https://doi.org/10.1007/978-3-030-44999-5_43

Negi, A., & Sain, S. (2023). Enhancing e-learning for Today’s Learners through a Technology-Driven Approach.

Rahmawati, A., Suryani, N., Akhyar, M., & Sukarmin, S. (2021). Vocational teachers’ perspective toward Technological Pedagogical Vocational Knowledge. Open Engineering, 11(1), 390–400. https://doi.org/10.1515/eng-2021-0040

Saleh, S. S., Nat, M., & Aqel, M. (2022). Sustainable Adoption of E-Learning from the TAM Perspective. Sustainability (Switzerland), 14(6). Scopus. https://doi.org/10.3390/su14063690

Surur, A. M., Ulfa, S., Soepriyanto, Y., & Binti, M. H. (2024). Personalized Learning in a Digital Environment. Indonesian Journal of Multidisciplinary Educational Research, 2(1), Article 1. https://doi.org/10.30762/ijomer.v2i1.2737

Thohir, M. A., Ahdhianto, E., Mas’ula, S., Yanti, F. A., & Sukarelawan, M. I. (2023). The effects of TPACK and facility condition on preservice teachers’ acceptance of virtual reality in science education course. Contemporary Educational Technology, 15(2). Scopus. https://doi.org/10.30935/cedtech/12918

Ukpe, E. (2023). Information and Communication Technologies (ICTS) for E-Learning in Tertiary Education. Open Journal of Social Sciences, 11(12), Article 12. https://doi.org/10.4236/jss.2023.1112044

Umaroh, S., Musrini, M., & Maulana, F. A. (2024). Student’s Acceptance and Actual Use of E-Learning System in a Post-COVID Era Through Technology Acceptance Model. E3S Web of Conferences, 484, 02003. https://doi.org/10.1051/e3sconf/202448402003

Zaid Daher Khalaf Hazaimeh, B. A. A. (2023). VOCATIONAL EDUCATION STUDENTS’ ACQUISITION OF PRACTICAL SKILLS AT IRBID NATIONAL UNIVERSITY IN JORDAN. Journal of Southwest Jiaotong University, 58(2), Article 2. http://www.jsju.org/index.php/journal/article/view/1603

Zalat, M. M., Hamed, M. S., & Bolbol, S. A. (2021). The experiences, challenges, and acceptance of e-learning as a tool for teaching during the COVID-19 pandemic among university medical staff. PLoS ONE, 16(3), e0248758. https://doi.org/10.1371/journal.pone.0248758

Published

2025-11-20

How to Cite

Rahmat, R. E., Hadi, S., Syafmaini, I. E., Gusti, U. A., Luthfi, A., & Fortuna, A. (2025). Factors influencing vocational teachers’ e-Learning adoption: A technology acceptance model approach. Jurnal Pendidikan Vokasi, 15(2). https://doi.org/10.21831/jpv.v15i2.86375

Issue

Section

Articles

Citation Check

Most read articles by the same author(s)

Similar Articles

<< < 32 33 34 35 36 37 38 39 40 41 > >> 

You may also start an advanced similarity search for this article.