Integrating Generative AI in Engineering Education: A Longitudinal Framework on Personality, Roles, and Perceptions

Abstract

This study investigates how engineering students’ personality traits, perceived team roles, and AI literacy influence their perceptions of generative Artificial Intelligence (Gen-AI) tools in university education. Building on previous frameworks that link psychological and behavioral variables to technology adoption, a longitudinal design was adopted across two academic years (2023–24 and 2024–25) at the University of Udine. The same validated questionnaire was administered to undergraduate and graduate engineering students, combining the Big Five personality inventory, perceived team-role selection, and five multi-item scales measuring Attitude, Trust, Social Influence, Fairness & Ethics, and Usefulness toward Gen-AI. Descriptive and inferential analyses showed stable perceptions over time, with small yet meaningful increases in Attitude and AI Literacy (p < .05). The mediation analysis indicated that AI literacy acts as a mediator between Openness and perceived Usefulness, although the effect was small and non-significant. The results suggest that continued exposure to Gen-AI fosters both greater confidence and more critical awareness among engineering students. The study provides evidence of the structural reliability of the proposed Excel-based framework and offers practical guidance for integrating AI literacy modules into design-oriented engineering curricula.

Keywords: Generative Artificial Intelligence, Engineering Education, Personality Traits, AI Literacy, Longitudinal Study, Human Factors In Design

DOI: 10.54941/ahfe1008004