Analyzing the Drivers of Adoption in Higher Education E-Learning: Exploring Factors Affecting Behavioral Intentions and Actual Usage

Abstract

Learners face problems while using traditional e-learning systems but AI introduces an innovative stage of advancement in technology that gives revolution in e-learning process. Study investigates factors that influence learner behavioral intention to use AI and actual usage in higher education. The study proposed UTAUT and IS model with additional external variables like perceive risk, work engagement and self-efficacy of learner. Cross-sectional study was used to measure research models based on several theories related to AI that brings cutting-edge technologies that enhance e-learning. Data was analysed using SEM technique. Research model and hypothesis testing was done by AMOS. Study investigate performance expectancy, effort expectancy, facilitating condition, system quality, service quality information quality, perceived risk, work engagement; self-efficacy had significantly influenced behavioral intention and actual use of AI. Finding gives practical references to stakeholders for adoption and acceptance of AI within e-learning process in higher education in NCR.