PREDICTORS OF TEACHERS' ADOPTION OF ARTIFICIAL INTELLIGENCE FOR EDUCATIONAL ASSESSMENT IN NIGERIAN SECONDARY SCHOOLS

Abstract

This study investigated the association of AI self-efficacy and perceived usefulness with teachers' adoption of AI technologies in educational assessment in Nigerian secondary schools using a correlational survey design. The study targeted senior secondary school teachers in Ibadan Metropolis and Lagos State, and 214 teachers from purposively selected schools participated voluntarily. Data were collected using a self-designed Google Form questionnaire titled AI Self-efficacy & Perceived usefulness in Educators’ adoption of Classroom Technology (ASPECT), with reliability α = .88. Four research questions guided the study. Findings revealed that AI self-efficacy had a significant positive association with teachers’ adoption of AI in educational assessment (β = .45, p < .001). Similarly, perceived usefulness significantly predicted adoption in educational assessment (β = .20, p = .003), although with a relatively smaller effect size. In contrast, teachers’ attitude toward technology adoption showed a very weak and non-significant relationship with adoption of AI for educational assessment (r = .06, p = .397). Furthermore, school support emerged as the strongest predictor of adoption of AI technologies for educational assessment (β = .73, p < .001). At the same time, access to technological resources was not a statistically significant predictor of adoption of AI in educational assessment (β = −.09, p = .073). The study concluded that teachers’ confidence in using AI and the presence of strong institutional support systems are important factors associated with AI adoption in educational assessment. In contrast, general attitudes and mere access to technological resources are insufficient to ensure adoption. It was recommended that policymakers and educational stakeholders prioritise capacity-building initiatives, provide sustained institutional support, and develop clear implementation frameworks to enhance the effective integration of AI in educational assessment practices.