Artificial Intelligence Adoption in Authentic Online Assessments: A Study of Online Distance Learning Institutions

Abstract

This study explores the factors influencing the adoption of artificial intelligence (AI) in authentic online assessments within open and distance learning (ODL) institutions. Using the Theory of Planned Behaviour (TPB) as the underlying framework, the research examines the roles of attitude, perceived behavioural control, subjective norms, and self-efficacy in shaping educators’ intention to adopt AI, and how this intention affects actual adoption. Data were collected from 299 academic staff through an online survey, and the analysis was conducted using SmartPLS 4. The findings show that intention, perceived behavioural control, self-efficacy, and subjective norms significantly influence the adoption of AI. Among these, intention was the strongest predictor of adoption behaviour. In contrast, attitude did not have a significant effect on adoption. The study also confirmed the mediating role of intention between the independent variables and adoption behaviour. Additional analysis using PLSpredict and the cross-validated predictive ability test (CVPAT) demonstrated that the model has good predictive relevance. These findings suggest that building educators’ confidence, ensuring access to necessary tools, and fostering a supportive institutional culture are more effective in promoting AI adoption than focusing solely on positive attitudes. The study contributes to the theoretical understanding of technology adoption in education and offers practical guidance for ODL institutions aiming to implement AI-driven assessment strategies.