Title: The Effectiveness of AI-Integrated Blended Educational Supervision in Developing Teaching Competencies and Enhancing Job Satisfaction Among Information Technology Teachers in Al Dhahirah Governorate, Oman
Authors: Fatma Hamad AL-Shuhumi
Dr. Abdullah Said AL-Aamri
Dr Mourad M.H Henchiri
Volume: 10
Issue: 8
Pages: 280-289
Publication Date: 2026/08/28
Abstract:
This study aimed to examine the effectiveness of AI-integrated blended educational supervision in developing teaching competencies and enhancing job satisfaction among Information Technology teachers in Al Dhahirah Governorate, Sultanate of Oman. It also examined the role of AI-supported personalized feedback, data-informed recommendations, and teachers' responsible use of AI and emerging digital technologies. The study adopted a mixed-methods approach using an explanatory sequential design within a quasi-experimental framework. The study population consisted of 167 Information Technology teachers, from which 110 teachers were randomly selected and divided into an experimental group (55) and a control group (55). The experimental group participated in an AI-integrated blended educational supervision program developed using the ADDIE model, including an intelligent educational supervision platform and an AI supervisory assistant, while the control group received existing blended supervision practices. Data were collected using a 24-item teaching competencies questionnaire, a 20-item job satisfaction questionnaire, and semi-structured interviews. Cronbach's alpha coefficients were 0.903 and 0.945, respectively. The results showed statistically significant differences in teaching competencies in favor of the experimental group, with a large effect size (?² = 0.699), and significant differences in job satisfaction, also in favor of the experimental group, with a large effect size (?² = 0.442). A significant positive relationship was found between teaching competencies and job satisfaction (r = 0.635, p < .001). Qualitative findings indicated that continuous support, personalized feedback, improved communication, and AI-supported guidance enhanced teachers' instructional practices, confidence, and motivation. Teachers also identified opportunities and challenges related to AI usability, trust, ethics, and responsible use. The study concludes that AI-integrated blended educational supervision can support teacher development and more personalized, continuous, and data-informed supervision. It recommends an evidence-based framework for sustainable AI adoption in educational supervision in Oman, aligned with Oman Vision 2040, while maintaining human supervision as a central element.