Research on generative AI within university teaching contexts a methodological analysis

Abstract

This article presents the results of a systematic literature review aimed at identifying methodological trends in empirical and review studies concerning generative artificial intelligence (GenAI) within higher education institutions. The review was conducted in accordance with PRISMA guidelines, by using a corpus of peer-reviewed articles indexed in Scopus and Web of Science, published between 2021 and early 2024. Most studies are conducted within undergraduate and teacher education settings, with a primary focus on assessment processes and academic performance. A qualitative matrix was applied to 30 selected studies, considering variables such as type of research, methodological approach, educational level, data collection techniques, and ethical-pedagogical approach. The findings show the predominance of quantitative, cross-sectional designs based on surveys with limited validation procedures. The study concludes with an insight: the need to enhance methodological rigor and ethical alignment in future research on generative artificial intelligence within the university context.

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