Investigating Teachers' Readiness for Revolutionizing Education with Artificial Intelligence: Private School Teachers as an Example

Parween Yaqub Saadi (Zhyar English Compound – Erbil, Iraq)
Shamal Abdullah Abdullah (English Department, Faculty of Arts, Soran University, Iraq)
Karwan Kakabra Kakamad (Department of Psychology, Counselling and Mental Health, Faculty of Arts, Soran University, Iraq)

Jounal of Education and Teaching (JET)
Vol 7 No 2 (2026): Mei 2026

Artificial intelligence (AI) is transforming education, yet empirical research on educators' readiness to develop in regions such as the Kurdistan Region of Iraq (KRI) remains scarce. To address this gap, this quantitative cross-sectional study investigates private school teachers’ readiness to integrate AI by synthesizing the Technology Acceptance Model (TAM) and Teacher Self-Efficacy (TSE) frameworks. Data was collected via a purposive sample of KRI teachers (N=107). Readiness was measured across three dimensions: knowledge, practicality, and ethics. Construct validity was established using Confirmatory Factor Analysis (CFA), followed by multiple linear regression. Results revealed that while teachers possess high conceptual AI knowledge, they exhibit significant hesitation toward practical, high-stakes implementation. Crucially, the inferential analysis yielded a novel finding: theoretical pedagogical knowledge (= 0.506,  < .001), rather than practical technical self-efficacy, significantly predicts teachers' ethical readiness. This study makes a vital contribution to the literature by demonstrating that, to overcome ethical implementation barriers in developing educational contexts, institutional policy must pivot from providing basic technical exposure to delivering rigorous, conceptual AI pedagogical training.