Factors Influencing Educational Support Personnel’s Intention to Use Generative AI in Thailand’s Basic Education System: Cross-Sectional Correlational Study

Abstract

Generative artificial intelligence (GenAI) has rapidly transformed educational practices; however, existing research has predominantly focused on teachers and students, leaving the role of educational support personnel largely underexplored. This study examined factors influencing behavioral intention to use GenAI among educational support personnel in Thailand’s basic education system. Grounded in an integrated theoretical framework synthesizing the Technology Acceptance Model (TAM), TAM3, the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Information Systems Success Model (ISSM), a correlational research design was employed. Data were collected from 115 participants through an online survey. Six predictor variables were examined: perceived usefulness, self-efficacy, attitude toward using AI, system quality, information quality, and service quality. Pearson’s correlation analysis revealed significant positive relationships between all predictor variables and behavioral intention (r = .45–.87, p < .01). Multiple regression analysis indicated that the six predictors collectively explained 82% of the variance in behavioral intention (R = .90, R² = .82). However, only attitude toward using AI (β = .58, p < .01) and system quality (β = .31, p < .01) emerged as significant predictors. These findings underscore the pivotal role of personal attitudes and system performance in shaping GenAI adoption and offer practical implications for advancing digital transformation in educational administration and support services.