Vocational Special Education Teachers’ Competency in Implementing Digital Learning for Students with Special Educational Needs

Authors

Nurul Ain Afiqah Kamaludin

Fakulti Pendidikan Teknikal dan Vokasional, Universiti Tun Hussein Onn Malaysia, Batu Pahat, 86400, Malaysia (Malaysia)

Fazlinda Ab Halim

Fakulti Pendidikan Teknikal dan Vokasional, Universiti Tun Hussein Onn Malaysia, Batu Pahat, 86400, Malaysia (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.100600491

Subject Category: Education

Volume/Issue: 10/6 | Page No: 7078-7085

Publication Timeline

Submitted: 2026-06-10

Accepted: 2026-06-15

Published: 2026-06-27

Abstract

The rapid advancement of digital technology has significantly transformed teaching and learning practices across educational settings, including vocational special education. The integration of digital learning provides opportunities for more flexible, interactive, and student-centred instructional approaches that can accommodate the diverse needs of students with special educational needs (SEN). However, successful implementation depends largely on teachers’ competency and their ability to overcome various technological and instructional challenges. Therefore, this study aimed to determine the level of competency among vocational special education teachers in implementing digital learning, identify the challenges encountered during implementation, and examine the relationship between digital learning challenges and teacher competency.
A quantitative descriptive survey design was employed involving 96 vocational special education teachers in Johor, Malaysia. Data were collected using a structured questionnaire developed based on Spencer and Spencer’s Competency Theory and the Unified Theory of Acceptance and Use of Technology (UTAUT). Descriptive statistics and Pearson correlation analyses were conducted using Statistical Package for the Social Sciences (SPSS).
The findings revealed that vocational special education teachers demonstrated a very high level of competency (M = 4.33, SD = 0.59). The level of challenges experienced in implementing digital learning was also very high (M = 4.36, SD = 0.66). Furthermore, Pearson correlation analysis indicated a significant positive relationship between digital learning challenges and teacher competency (r = 0.649, p < 0.001). The findings suggest that continuous exposure to technological challenges contributes to the development of more competent and adaptive teachers.
This study contributes to the growing body of knowledge on digital learning in vocational special education and provides empirical evidence that strengthening digital infrastructure, institutional support, and continuous professional development can further enhance teachers’ competency in implementing effective digital learning environments for students with special educational needs.

Keywords

Teacher Competency, Digital Learning, Vocational Special Education, Special Educational Needs, Challenges

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References

1. Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. [Google Scholar] [Crossref]

2. Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2021). Mapping research in student engagement and educational technology in higher education: A systematic evidence map. Educational Technology Research and Development, 69(2), 653–685. [Google Scholar] [Crossref]

3. Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications. [Google Scholar] [Crossref]

4. Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. [Google Scholar] [Crossref]

5. 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. [Google Scholar] [Crossref]

6. Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004 [Google Scholar] [Crossref]

7. König, J., Jäger-Biela, D. J., & Glutsch, N. (2020). Adapting to online teaching during COVID-19 school closure: Teacher education and teacher competence effects among early career teachers in Germany. European Journal of Teacher Education, 43(4), 608–622. https://doi.org/10.1080/02619768.2020.1809650 [Google Scholar] [Crossref]

8. Montenegro-Rueda, M., & Fernández-Batanero, J. M. (2024). Adaptation and validation of an instrument for assessing the digital competence of special education teachers. European Journal of Special Needs Education, 39(3), 367–382. [Google Scholar] [Crossref]

9. Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first-century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. [Google Scholar] [Crossref]

10. Rakes, G. C., & Casey, H. (2023). Competencies of special education teachers in using digital learning tools. Journal of Special Education Technology, 38(1), 45–59. https://doi.org/10.1177/01626434221110374 [Google Scholar] [Crossref]

11. Ramakrishnan, R., Mohamad Salleh, N., & Aliza, A. (2022). The relationship between teaching style, self-efficacy and competency in vocational special education teachers. Akademika, 92(Special Issue 1), 81–94. https://doi.org/10.17576/akad-2022-92IK1-07 [Google Scholar] [Crossref]

12. Reinholz, D. L., Stone-Johnstone, A., White, I., Sianez, L. M., & Shah, N. (2020). A pandemic crash course: Learning to teach equitably in synchronous online classes. CBE—Life Sciences Education, 19(4), 1–13. https://doi.org/10.1187/cbe.20-06-0127 [Google Scholar] [Crossref]

13. Roslin, N. B., & Salleh, N. M. (2021). Penggunaan M-learning sebagai bahan bantu pengajaran dalam kelas pendidikan khas. Malaysian Journal of Social Sciences and Humanities, 6(5), 53–63. https://doi.org/10.47405/mjssh.v6i5.760 [Google Scholar] [Crossref]

14. Scherer, R., Siddiq, F., & Tondeur, J. (2021). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Computers & Education, 128, 13–35. https://doi.org/10.1016/j.compedu.2018.09.009 [Google Scholar] [Crossref]

15. Spencer, L. M., & Spencer, S. M. (1993). Competence at work: Models for superior performance. John Wiley & Sons. [Google Scholar] [Crossref]

16. Tondeur, J., Scherer, R., Siddiq, F., & Baran, E. (2021). A comprehensive analysis of teacher digital competence. Computers & Education, 162, Article 104080. [Google Scholar] [Crossref]

17. Trust, T., & Whalen, J. (2020). Should teachers be trained in digital learning? Lessons learned from the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 189–199. [Google Scholar] [Crossref]

18. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540 [Google Scholar] [Crossref]

19. Yusof, N., Ismail, H., & Rahman, S. (2022). Integrasi teknologi digital dalam pendidikan khas: Cabaran dan penyelesaian. Jurnal Pendidikan Malaysia, 47(2), 50–60. [Google Scholar] [Crossref]

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