Academic Procrastination and Functional Dependence on Generative Artificial Intelligence among University Students

Rodríguez R.F.; Espejo-Chacón L.F.; Montalvo-Huiñac G.L.; Meléndez-Calvo L.E.; Meléndez-Calderón F.S. · CEUR Workshop Proceedings (2026)

Resumen

This study followed an explanatory sequential mixed-methods design (DEXPLIS) to determine the relationship between academic procrastination and functional dependence on generative artificial intelligence (GenAI) among university students, and to explain this relationship from the perspective of university professors. In the quantitative phase, a probabilistic sample of 240 students was calculated from a population of 636 undergraduates of a public university in Ancash, Peru; the instruments showed excellent reliability (Cronbach’s alpha =.972 for academic procrastination and.958 for functional dependence on GenAI) and, given a non-normal distribution (Kolmogorov-Smirnov, p <.001), Spearman’s rho revealed a strong, positive, and significant correlation between academic procrastination and functional dependence on GenAI (rho =.733, p <.001), as well as between its two dimensions, self-regulation difficulty (rho =.735, p <.001) and postponement of activities (rho =.708, p <.001), and functional dependence. In the qualitative phase, semi-structured interviews with 15 professors (more than five years of experience), analyzed through open, axial, and selective coding, identified seven converging categories, with cognitive delegation as the central mechanism linking postponement and self-regulation deficits to functional dependence. These integrated quantitative and qualitative findings support strategies for critical AI literacy, self-regulated learning, and process-based assessment in higher education.

Instituciones: Universidad Tecnológica del Perú; Universidad Católica Los Ángeles de Chimbote; Universidad César Vallejo