Análisis bibliométrico sobre la evaluación del aprendizaje con IA.

Abstract

The objective of this research is to evaluate the impact of artificial intelligence (AI) on learning outcomes in education through a bibliometric analysis of the literature in Web of Science. The study identifies emerging trends, influential authors, leading institutions, and key thematic areas related to the integration of AI in education. Tools such as VOSviewer, Tree of Science, and Sci2 Tool were used to map networks of co-citation, co-authorship, and keyword co-occurrence, visualizing connections and collaboration patterns among researchers in this field. The results show that research on AI and education is rapidly growing. There is a notable focus on topics such as personalized learning, automated assessment, and the development of digital competencies, reflecting an interdisciplinary approach to the use of advanced technologies. One limitation is the study's reliance on a single database and its focus on a specific category, which could bias the results. Future studies should expand the use of various databases and explore more thematic areas to provide a more comprehensive view of AI's impact on education.