Digital Self- Efficacy and Student Engagement in AI-Supported Learning Environment: The Mediating Role of Academic Motivation

Abstract

This study aimed to explore the correlation between the construct of digital self-efficacy and engagement of students in the context of AI-driven learning environments, while also investigating the potential mediation of academic motivation. The design applied was a descriptive correlational cross-sectional design. The study included a sample of 130 undergraduate students at Al Esraa University who had experience in using AI tools to help in the academic process. A 24-item questionnaire, assessed through three constructs - digital self-efficacy, academic motivation, and student engagement, was used for data collection. Means, standard deviations, Pearson's correlation coefficients, and mediation analysis using Hayes' PROCESS Macro, Model 4, were employed to analyze the data. The results indicated that students possessed high digital self-efficacy and were highly motivated and engaged in learning environments supported by AI. Academic motivation was the highest and positively significant with student engagement, and digital self-efficacy was positively and significantly associated with academic motivation and student engagement. The mediation analysis revealed that digital self-efficacy was partially mediated by academic motivation. The findings pointed out that students' confidence with the use of digital and AI-supported tools had a direct influence on the engagement of students, but also had an indirect effect through strengthening the academic motivation of the students. Overall, the study suggested steps to be implemented to enhance students' confidence, critical evaluation, and motivation while fostering meaningful and responsible interaction with the use of AI in their learning process.