Is Artificial Intelligence a New Pillar of Higher Education? Exploratory and Confirmatory Factor Analysis of the Student Academic Experience

Abstract

Traditional frameworks evaluating the university academic experience often give limited attention to students’ reported use of Artificial Intelligence. This study psychometrically validates a novel measurement model, testing whether AI-related academic practices emerge as a distinct component of students’ perceived academic experience. Using a cross-validation design, 2403 undergraduate students from a private university in Bolivia were surveyed. The dataset was randomly split for Exploratory Factor Analysis (EFA, n = 1200) to uncover latent variables and Confirmatory Factor Analysis (CFA, n = 1203) to validate the structural stability of a refined 31-item scale. The EFA revealed a cohesive five-factor structure: (1) Academic Engagement and Student Life, (2) Student-Reported AI Use in Academic Learning, (3) Communication and Critical Thinking Skills, (4) Teaching Quality, and (5) Academic Dedication. The CFA confirmed an excellent model fit (CFI = 0.954, RMSEA = 0.046), supporting strong construct validity. Furthermore, inter-factor correlations showed that student-reported AI use was positively associated with academic engagement and with the broader Communication, Ethical, and Critical Thinking Skills domain. These empirical results suggest that, within this institutional context, students perceive AI as a relevant element of their academic routines. By validating the University Academic Experience and AI Integration Survey, this study provides a context-specific framework for assessing students’ self-reported use and perceived integration of AI in academic learning as a distinct dimension of their academic experience. The validated instrument is not intended for directly measuring learning outcomes, educational effectiveness, teaching effectiveness, or institutional quality.