Teacher’s Acceptance and Intention to Use Artificial Intelligence Technology in Teaching and Learning Based on the UTAUT Model
Intan Farahana Kamsin · International Journal of Information and Education Technology · 2025
The integration of Artificial Intelligence (AI) technology in teaching and learning is becoming increasingly prevalent, necessitating teacher preparedness for pedagogical reform. This study investigates the factors influencing secondary school teachers’ acceptance of AI technology based on the Modified Integrated Theory of Acceptance and Use of Technology (UTAUT). Specifically, it examines the roles of Performance Expectation, Effort Expectation, Social Influence, and AI Anxiety in shaping behavioral intention, and explores the moderating effects of gender, age, and teaching experience. Data were collected through a structured questionnaire administered to 88 secondary school teachers in Kuala Lumpur, Malaysia. Statistical analyses, including one-way ANOVA and multiple linear regression using SPSS version 29, conducted to evaluate the data. The results reveal that Effort Expectation and AI Anxiety significantly influence behavioral intention, while Performance Expectation and Social Influence do not. Additionally, teaching experience positively moderates the relationship between predictor factors and behavioral intention, whereas gender and age have no moderating effect. These findings contribute to understanding the factors that promote AI technology acceptance among teachers and provide insights for strategies to enhance AI adoption in Malaysian education.