Assessing Zoomers Readiness for Artificial Intelligence Adoption in Higher Academic Institutions in Bangladesh: A PLS-SEM Approach

Abstract

The purpose of the study is to examine the Zoomers readiness to adopt AI in Bangladeshi higher educational institutions by employing the extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework where Zoomers attitudes toward AI are considered as a mediating factor. A structured questionnaire was distributed to 400 respondents using a convenience sampling method, resulting in 335 valid responses for data analysis. PLS-SEM was utilized to examine the measurement and structural model, with data analysis conducted using SmartPLS 4.1.1.8. The findings reveal that effort expectancy positively influences both behavioural intention (β = 0.211, p < .001) and attitudes toward AI (β = 0.443, p < .001) with attitude serving as the strongest predictor of behavioural intention (β = 0.600, p < .001). While performance expectancy (β = 0.166, p = .010) and facilitating conditions (β = 0.117, p = .038) significantly enhance attitudes but do not directly predict behavioural intention. Social influence is found to be insignificant for both attitude and behavioural intention. Moreover, attitude significantly mediates the effects of performance expectancy, effort expectancy, and facilitating conditions on behavioural intention. These findings extend UTAUT framework by emphasizing the role of attitude as a pivotal factor in the adoption of AI. They also offer practical implications for creating accessible, supportive, and learner-centred AI environments in Bangladeshi higher education. Future research could consider other variables like trust in AI, ethical issues in media sharing, and comparisons of generational differences across various education levels in Bangladesh.