PREDICTING TEACHERS' BEHAVIORAL INTENTION TO INTEGRATE AI IN EDUCATION: A STUDY OF KEY INFLUENCING VARIABLES

In the Philippines, understanding how teachers perceive the usefulness of AI in education remains critical, as skepticism and ethical concerns continue to hinder its adoption. Many teachers express apprehension about using AI tools due to technological barriers, lack of regulatory policies, and resistance to change. Thus, it is important to understand predictors of behavioral intention to address these challenges, as it provides insights into the factors that motivate or discourage teachers from integrating AI into their practices. This study aims to explore private school teachers’ willingness to adopt AI in their teaching practices and identify the factors contributing to its effective integration, using Partial Least Squares Structural Equation Modeling. A total of 129 private school teachers from Caloocan and Quezon City who participated in this study. The result shows that perceived usefulness, computer self-efficacy, and social influence significantly influence behavioral intention of teachers to integrate AI. It also highlights the critical role of computer self-efficacy in shaping perceived usefulness, while perceived ease of use was found to have minimal relevance to this context. Findings calls for policymakers, educational institutions, and stakeholders to focus on promoting practical benefits of AI, building teacher confidence, and designing seminar and workshops that emphasize real-world applications and best practices.