AI literacy among undergraduates: Determinants and productivity outcomes in a Malaysian comprehensive university - Yusnilzahri, Nur Arifah Syahadah; Mohamad Rosman, Mohamad Rahimi; Saiful Bahry, Farrah Diana (Malaysian Journal of Library and Information Science, 2025)
AI literacy encompasses the knowledge, skills, and competencies required for individuals to effectively develop, manage, and understand the potential of AI across various domains, including education. However, previous research indicates a lack of studies focusing on AI literacy, particularly regarding its determinants and effects. This study therefore aims to examine AI literacy in relation to its influencing factors and effects within the educational sector, with a specific focus on undergraduate students at Malaysian local universities. A quantitative research methodology was employed, and responses were collected from undergraduate students in the Faculty of Information Science Studies across six Universiti Teknologi MARA (UiTM) branches. A total of 301 responses were obtained and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) and the Statistical Package for the Social Sciences (SPSS). The results provide empirical evidence of a significant and positive relationship between the influencing factors (cognitive absorption, digital divide, effort expectancy, and AI awareness) and AI literacy. However, contrary to previous studies, attitudes towards AI and performance expectation did not have a significant relationship with AI literacy. Furthermore, AI literacy was also found to be a predictor of students' productivity. The study provides significant empirical, practical, and theoretical contributions; researchers may use the theoretical model to further enhance knowledge of AI literacy. Institutions and policymakers may use the results to develop new subjects, syllabuses, and policies on AI literacy.