Lighting the Path: Enhancing Student Acceptance of Artificial Intelligence-Assisted Tutoring in Open, Distance, and Digital Education Higher Institutions
This study emphasises the crucial role of AI-assisted tutoring acceptance among students in Open Distance Digital Education (ODDE) higher institutions, highlighting its potential to significantly enhance learning experiences and outcomes in digital environments. As technological integration becomes increasingly vital in education, understanding factors that influence students’ acceptance is essential for the effective implementation and adoption of AI tools. The study aims to investigate the relationships between perceived usefulness, perceived ease of use, and student engagement as they influence acceptance of AI-assisted tutoring, with engagement serving as a mediating variable. Data were collected through a structured survey distributed via purposive sampling to 492 students across various ODDE institutions. The analysis employed Partial Least Squares-Structural Equation Modelling (PLS-SEM) to assess the hypothesised relationships and path coefficients. Results revealed that perceived usefulness had a strong, direct impact on acceptance, while perceived ease of use influenced acceptance indirectly through student engagement; both relationships were statistically significant. Specifically, the study confirmed that empowering students with easy-to-use, valuable AI tools and fostering engagement can significantly boost acceptance levels. Future research should explore the longitudinal effects of AI adoption and include qualitative insights to better understand barriers and motivators. Practically, the findings suggest that higher education policymakers should focus on designing user-friendly AI systems, providing continuous training, and implementing engagement strategies like gamification and interactive activities to foster acceptance.
Authors
- Zahir Osman (ORCID: https://orcid.org/0000-0001-8443-3062)
- Hamidah Mat (ORCID: https://orcid.org/0000-0001-9766-6180)
- Aliza Ali
- Raziana Che Aziz
Institutions
- Open University Malaysia (MY)
Publication Details
- Journal
- International Journal of Academic Research in Business and Social Sciences
- Published
- 2026-01-29
- DOI
- https://doi.org/10.6007/ijarbss/v16-i1/27419
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00