A CONTRIBUIÇÃO DO ESTÁGIO SUPERVISIONADO NA FORMAÇÃO DO ENGENHEIRO CIVIL: UMA ANÁLISE AUTOMATIZADA DE DADOS DE ESTÁGIOS NA UFSCAR COM O USO DE INTELIGÊNCIA ARTIFICIAL

Abstract

: This study analyzes the contribution of supervised internships to the training of civil engineers at motivated by the need to align laboratory and field practices with the New National Curricular Guidelines, and proposes a methodological innovation in the use of Artificial Intelligence (AI) for managing academic data. The general objective was to analyze the socioeconomic and professional landscape of internships, evaluating the compatibility between labor market practices, compliance with the requirements of Law No. 11,788/2008, and the development of technical and transversal competencies established by the Course's Pedagogical Project. The methodology was characterized as an exploratory and documentary case study with a qualitative-quantitative approach, employing an automated system built with Google Apps Script and integrated with Gemini AI to process 1,016 documents from 323 students. The results, based on 476 validated Internship Commitment Terms (TCE), reveal a slight predominance of non-mandatory internships (52.9%) and the hegemony of the in-person regime (65.8%). However, hybrid (15.7%) and remote (18.5%) models have allowed access to economic centers far from . It was found that 82.4% of students remained with a single company and that, despite the traditional base in construction and engineering services, the Technology and Data Analysis area accounted for 10% of the sample and had the highest average remuneration. The main conclusions indicate that the integration of AI was essential for analyzing large volumes of data and that the internship at effectively fulfills its educational role, with a high technical alignment (65% to 70%). Finally, a market in nominal appreciation is observed, preparing versatile professionals who integrate traditional field engineering with increasing digitalization and complex data analysis.