THE USE AND PERCEPTION OF GENERATIVE ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: A CONTENT ANALYSIS IN THE SOFTWARE ENGINEERING COURSE
DOI:
https://doi.org/10.56238/revgeov17n4-129Keywords:
Generative Artificial Intelligence, Higher Education, Software Engineering, AI Ethics, Content AnalysisAbstract
The rapid diffusion of Generative Artificial Intelligence (GAI) has significantly impacted higher education, particularly in technology-based programs such as Software Engineering. This study analyzes the pedagogical potential, ethical challenges, and governance gaps associated with the use of GAI in this context, employing Content Analysis of the 16 scientific studies selected through a PRISMA-structured review protocol.As a complementary step, external documentary validation was conducted using normative and reference documents (Brazilian National Curricular Guidelines for computing courses DCNs SWEBOK, UNESCO AI competency framework for teachers, and illustrative course syllabi; Section 5.4) to support the proposed model.Findings indicate that GAI functions both as a coding tutor and as an agent of personalized learning, while simultaneously exposing risks related to statistical bias, technical opacity, and the “transparency paradox” in assessment practices. As an original contribution, the study proposes the concept of the “Opacity-Bias-Paradox Nexus”, which synthesizes the main contemporary challenge for competency evaluation in software engineering education.
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