This study investigates the adoption of artificial intelligence (AI) among students in learning enhancement within open, distance, and digital education (ODDE) higher institutions, a context where AI holds huge potential to personalise learning experiences, bridge geographical barriers, and enhance engagement. Given the fragmented research landscape and the unique challenges faced by ODDE students, this study aims to examine the complex relationships between perceived usefulness, perceived ease of use, learners’ autonomy, and AI adoption, with learning engagement acting as a mediator. Employing a comprehensive survey instrument comprising 23 observable variables adapted from established scales, data were collected from 297 valid responses obtained through purposive sampling. Structural equation modelling (SEM) was utilised via SmartPLS software to analyse the data and test the proposed hypotheses. The results generally support the proposed model, revealing that learners' autonomy and perceived usefulness positively influence AI adoption, with learning engagement playing a crucial mediating role. However, perceived ease of use did not directly impact AI adoption. These findings highlight the importance of strategic implementation of AI, with an emphasis on creating user-friendly interfaces and fostering learner autonomy. Future research could explore longitudinal dynamics, contextual barriers, and specific design features to enhance AI adoption further. This study offers valuable theoretical implications by integrating the Technology Acceptance Model (TAM) with constructivist learning principles, while also providing actionable managerial insights for higher education institutions aiming to optimise AI integration for improved learning outcomes and organisational competitiveness. By focusing on perceptual and behavioural factors, institutions can foster sustainable and impactful AI adoption in the digital education landscape.
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