Rethinking Perceived Usefulness in AI-based Learning for Cultural and Sustainability Education Using a Value-oriented Extended TAM

Abstract

Artificial Intelligence (AI) has become an influential force in contemporary education, particularly in cultural heritage and sustainability learning that require contextual and value-oriented understanding. This study investigates the factors influencing secondary school students’ acceptance of an AI-based intelligent learning platform in Thailand using an extended Technology Acceptance Model (TAM). The model integrates core constructs—perceived ease of use, perceived usefulness, attitude toward use, intention to use, and actual platform acceptance—with additional variables, including self-efficacy, community support, learning engagement, and sustainability and cultural awareness. Data were collected from 400 learners using a five-point Likert scale questionnaire and analyzed through Structural Equation Modeling (SEM). The results indicate a good model fit. Perceived usefulness was the strongest predictor of attitude toward use. Self-efficacy, sustainability and cultural awareness, and community support significantly enhanced perceived usefulness. In contrast, learning engagement showed a small but significant negative effect, suggesting that engagement alone may not increase perceived usefulness without meaningful learning design. From a theoretical perspective, this study extends TAM by incorporating value-oriented constructs, thereby offering a more comprehensive explanation of technology acceptance in culturally and socially embedded learning contexts. From a practical standpoint, the findings highlight the importance of usability, learner confidence, and meaningful learning experiences in promoting sustained adoption of AI-based learning platforms. Overall, student acceptance is shaped by an interplay of technological, psychological, and socio-cultural factors.