Factors Influencing AI Remote Proctoring Acceptance in Ghanaian Distance Education: A Mixed-Methods UTAUT Analysis

The COVID-19 pandemic accelerated the adoption of online education across Africa, necessitating innovative approaches to assessment integrity. This study explores Ghanaian students' and faculty perceptions of AI Remote Proctoring Systems (AIRPS) in distance education using the Unified Theory of Acceptance and Use of Technology (UTAUT). A concurrent mixed-methods design (n=370) revealed that performance expectancy (β=0.37, p<.001) and effort expectancy (β=0.31, p<.001) were the strongest predictors of adoption intention, followed by social influence (β = 0.17, p = .008). However, facilitating conditions were not significant. Contrary to expectations, demographic variables did not moderate these relationships. Findings suggest the need for training protocols that emphasize AIRPS benefits over perceived barriers in the Ghanaian distance education space.