IJIET 2026 Vol.16(4): 1103-1113
doi: 10.18178/ijiet.2026.16.4.2579
doi: 10.18178/ijiet.2026.16.4.2579
Building a Training Model to Enhance Digital Competencies Among Learning Support Teachers in Jordan: Examining the Role of Gender, Academic Qualifications, and Teaching Experience
Burhan Mahmoud Hamadneh1,*, Iyad Mohammed Hamadneh2, Malek Turki Jdaitawi3, and Mohannad Igdaifan Alseraa4
1. Department of Special Education, Faculty of Educational Sciences, Ajloun National University, Ajloun, Jordan
2. Department of Psychology and Special Education, Faculty of Educational Sciences, Al al-Bayt University, Mafraq, Jordan
3. Department of Classroom Teacher, Faculty of Educational Sciences, Zarqa University, Zarqa, Jordan
4. Counseling Psychology, Ministry of Education, Jordan
Email: b.hamadneh@anu.edu.jo (B.M.H.); imh_2005@aabu.edu.jo (I.M.H.); mjdaitawi@zu.edu.jo (M.T.J.); mohannadalhamad@yahoo.com (M.I.A.)
*Corresponding author
2. Department of Psychology and Special Education, Faculty of Educational Sciences, Al al-Bayt University, Mafraq, Jordan
3. Department of Classroom Teacher, Faculty of Educational Sciences, Zarqa University, Zarqa, Jordan
4. Counseling Psychology, Ministry of Education, Jordan
Email: b.hamadneh@anu.edu.jo (B.M.H.); imh_2005@aabu.edu.jo (I.M.H.); mjdaitawi@zu.edu.jo (M.T.J.); mohannadalhamad@yahoo.com (M.I.A.)
*Corresponding author
Manuscript received August 25, 2025; revised September 11, 2025; accepted November 19, 2025; published April 22, 2026
Abstract—This study assesses the digital competencies of Learning Support Teachers (LSTs) in Jordan and examines the effects of gender, academic qualifications, and teaching experience. Using a descriptive survey design, data were collected from 187 randomly selected LSTs in public schools in Amman. A validated 32-item electronic questionnaire covering four domains was employed. Results indicated that teachers demonstrated a moderate level of digital competence. Significant differences were observed based on academic qualification and teaching experience, with higher competence among those holding university degrees and with less than ten years of experience, while no significant differences were found by gender. These findings highlight the influence of professional background and experience on digital readiness. In response to these findings, the researchers developed the Digital Integration for Competency Enhancement (DICE) model, which targets identified competency gaps and provides context-specific professional development for language teachers. The DICE model helps teachers effectively integrate digital tools into inclusive classroom practices, thereby enhancing both teaching quality and learner engagement. In addition, this study offers original insights into LSTs’ digital competencies in Jordan and proposes a practical, theoretically grounded training model that underscores the role of qualifications and experience in promoting digital readiness within inclusive education.
Keywords—digital competencies, learning support teachers, teacher training model, educational technology, inclusive education, teaching experience, professional development
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—digital competencies, learning support teachers, teacher training model, educational technology, inclusive education, teaching experience, professional development
Cite: Burhan Mahmoud Hamadneh, Iyad Mohammed Hamadneh, Malek Turki Jdaitawi, and Mohannad Igdaifan Alseraa, "Building a Training Model to Enhance Digital Competencies Among Learning Support Teachers in Jordan: Examining the Role of Gender, Academic Qualifications, and Teaching Experience," International Journal of Information and Education Technology, vol. 16, no. 4, pp. 1103-1113, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).