Artificial Intelligence Adoption in Open, Distance, and Digital Education: Examining the Mediating Effect of Learning Engagement

HRMARS - This study examines the adoption of artificial intelligence (AI) in enhancing student learning within open, distance, and digital education (ODDE) higher education institutions. While AI offers significant potential to personalise learning, improve engagement, and overcome geographical barriers, empirical evidence on its adoption in ODDE contexts remains limited. To address this gap, the study investigates the relationships between perceived usefulness (PU), perceived ease of use (PEU), and learners’ autonomy (LA) in influencing AI adoption, with learning engagement (LE) examined as a mediating variable. A quantitative research design was employed using a structured questionnaire comprising 23 validated items. Data were collected from 297 ODDE students through purposive sampling and analysed using Structural Equation Modelling (SEM) via SmartPLS. The findings reveal that perceived usefulness and learners’ autonomy have significant positive effects on AI adoption. Learning engagement plays a critical mediating role, indicating that positive perceptions and autonomy must translate into active involvement to support adoption. In contrast, perceived ease of use does not directly influence AI adoption, although it positively contributes to learning engagement. The study extends the Technology Acceptance Model (TAM) by incorporating learner-centred constructs and highlights the importance of engagement in AI adoption. Practically, the findings suggest that institutions should focus on fostering learner autonomy, meaningful engagement, and clear value communication when integrating AI into ODDE environments.