Use of Artificial Intelligence to Improve Engineering Students’ Learning at the Delta Regional Faculty (#1647)

Authors

Carrillo, Carla Daniela

Carrillo, Elvio German

Echazarreta, Carla Paola

Visintin, Fernando Pablo

Abstract

The integration of artificial intelligence (AI) into higher education presents a strategic opportunity to transform teaching and learning processes in engineering, particularly in Latin American contexts facing structural challenges related to equity, student retention, and pedagogical innovation. This paper presents a mixed-methods study conducted at the National Technological University, Delta Regional Faculty (UTN–FRD), aimed at analyzing the impact of AI tools on engineering student learning, explicitly integrating a gender perspective and an ethical approach. The study examines the implementation of intelligent tutors, content recommendation systems, learning analytics, and adaptive assessments in selected courses from the basic and advanced cycles. Variables related to academic performance, motivation, self-regulated learning, and perceived equity are analyzed. The expected results aim to provide empirical evidence to support the responsible integration of AI as a driver of educational innovation and as a tool for reducing gender gaps.