Aplicaciones de la inteligencia artificial en la evaluación del aprendizaje en la educación superior beneficios, limitaciones y desafíos éticos

Roger Audes  Baltazar Flores

Authors

Roger Audes Baltazar Flores Universidad Nacional Ciro Alegría, Perú Author https://orcid.org/0009-0001-8134-5654

Keywords:

artificial intelligence, learning assessment, higher education, automated feedback, educational technology

Abstract

This systematic review aimed to analyze the applications of artificial intelligence (AI) in learning assessment processes in higher education, identifying its benefits, limitations, and current challenges. Various scientific studies published in the last five years were reviewed, focusing on those that integrate AI tools such as automated feedback systems, predictive performance analytics, and automated grading. The findings reveal that AI contributes to the efficiency of assessment processes by reducing faculty workload, enhancing feedback quality, and facilitating more objective evaluations. However, significant barriers were also identified, including a lack of faculty training, technological inequalities among institutions, and ethical concerns related to data privacy and algorithm transparency. Moreover, the need for a solid pedagogical framework is emphasized, ensuring that AI serves as a support rather than a replacement for professional teacher judgment. The successful implementation of these technologies requires clear institutional policies, continuous training, and rigorous evaluation of their impact on teaching and learning. It is concluded that AI holds high transformative potential, provided it is applied critically, inclusively, and within a well-contextualized educational framework

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