The influence of affective AI literacy on student satisfaction in higher education

This study explores the impact of affective AI literacy on student satisfaction in Pakistan’s evolving higher education sector, which is placing greater emphasis on sustainable education and market-relevant skills. Technology Acceptance Model together with the Cognitive-Affective Theory of Learning with Media (CATLM) is used as theoretical lens for analyzing this investigation. Conducted across three geographically distinct campuses of COMSATS University Islamabad, the research uses a convenience sampling approach. 237 computer science undergraduates participated through an online survey. Measurement items are adapted from established research to ensure validity and reliability, and the data is analyzed using Structural Equation Modeling (SEM). Results indicate that affective AI literacy positively impacts students’ perceptions of AI tools’ usefulness (β = 0.655, p < .001), ease of use (β = 0.613, p < .001), and satisfaction (β = 0.148, p < .01). Perceived usefulness and perceived ease of use are found to mediate student satisfaction, enhancing student engagement and personalization in learning. The study urges higher education to include emotional, ethical, and user-friendly AI considerations into curricula, examining how feelings and attitudes shape students’ perceptions of AI’s usefulness, ease of use, and satisfaction to foster holistic AI literacy. However, limitations include the use of convenience sampling, which focused exclusively on computer science undergraduates from specific campuses, potentially limiting the generalizability to other disciplines or regions. Additionally, future research could explore additional factors like enjoyment, social influence, and academic performance to gain a broader understanding of AI literacy’s impact on student satisfaction.