Evaluación y acreditación universitaria:  Integración de la inteligencia artificial en los sistemas de calidad

Geovanny Francisco  Ruiz Muñoz; Juan Carlos  Vasco Delgado; Silvana Lorena  Lozano Zamora

doi:10.59814/resofro.2024.4(6)511

Authors

Geovanny Francisco Ruiz Muñoz Universidad de Guayaquil, Ecuador https://orcid.org/0000-0001-7529-6342
Juan Carlos Vasco Delgado Universidad de Guayaquil, Ecuador https://orcid.org/0000-0003-0587-9758
Silvana Lorena Lozano Zamora Universidad Técnica Estatal de Quevedo, Ecuador https://orcid.org/0009-0009-2189-0958

DOI:

https://doi.org/10.59814/resofro.2024.4(6)511

Keywords:

artificial intelligence, higher education accreditation, higher education modernization, quality assurance systems, university evaluation

Abstract

This research analyzes the potential of integrating Artificial Intelligence (AI) systems into university evaluation and accreditation processes, with the aim of optimizing their efficiency, objectivity, and precision. Through a mixed methodological approach, a comprehensive documentary analysis, a multiple case study in 25 higher education institutions, and an empirical analysis including interviews, questionnaires, and systematic observation were conducted. The results reveal significant improvements in process efficiency, with a considerable reduction in total evaluation times. Moreover, an increase in the consistency and objectivity of evaluations was observed, with high levels of statistical reliability. The implementation of AI systems also generated important savings in human resources. However, the study also identified challenges related to initial staff resistance and the need for greater training. In conclusion, the integration of AI into university accreditation processes represents a significant step towards the modernization and continuous improvement of educational quality.

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