Relationship Between AI Literacies and Academic Performance of Graduate Students: A Study of Punjab

Abstract

This quantitative empirical study investigates the relationship between Artificial Intelligence (AI) literacies and academic performance among graduate students in Punjab, Pakistan. Drawing upon Cognitive Constructivism and the Technology Acceptance Model (TAM), AI literacy was operationalized as a four-dimensional construct comprising AI Awareness, AI Use Competence, AI Critical Evaluation, and AI Ethical Awareness. A cross-sectional survey design was implemented across public and private sector universities in Punjab. A target population of N=365 enrolled Master’s and Ph.D. students was surveyed using a structured, validated instrument. Academic performance was evaluated using cumulative grade point average (CGPA) and self-reported research output efficiency. Structural Equation Modeling (SEM) via SmartPLS was conducted to evaluate hypotheses. Descriptive statistics revealed moderate to high overall AI literacy among graduate students, with AI Use Competence recording the highest mean score. Pearson correlation and multiple regression analyses demonstrated that AI Use Competence, AI Critical Evaluation, and AI Ethical Awareness exert significant positive influences on academic performance, whereas basic AI Awareness alone showed a weaker direct association. The complete model explained 41.8% of the variance (R 2 =0.418) in graduate students' academic performance. The study provides empirical proof that functional, critical, and ethical AI integration directly boosts scholarly productivity, recommending formal institutional AI literacy modules within Pakistani higher education curricula.