Inteligencia artificial generativa para la enseñanza de matemáticas y programación en educación superior: Revisión sistemática
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Fecha
2026
Autores
Erazo-Arteaga, Víctor A.
VACAS PALACIOS, SANTIAGO MARCELO
Cisneros Ruáles, Marcelo Bayardo
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Universidad del Zulia
Resumen
La rápida expansión de la inteligencia artificial generativa ha despertado un creciente interés en su aplicación educativa, especialmente en áreas que exigen razonamiento lógico y abstracción. El objetivo de esta revisión sistemática fue analizar el impacto de la inteligencia artificial generativa en el aprendizaje de estudiantes universitarios, así como en la preparación de clases por parte de los docentes. Se aplicaron las directrices PRISMA, definiendo criterios de inclusión y exclusión con base a preguntas PICO y PCC. La búsqueda en Scopus, Web of Science e IEEE Xplore permitió analizar 710 registros, de los cuales 67 cumplieron con los criterios establecidos. Los resultados muestran una literatura dominada por estudios descriptivos y con predominio de ChatGPT, donde se reportan beneficios en motivación y productividad, aunque sin evidencias concluyentes de mejoras en el rendimiento académico. La investigación se concentra en pocos países con ausencia de producción latinoamericana. En conclusión, el uso de inteligencia artificial generativa ofrece un potencial pedagógico prometedor, pero su efectividad depende de la integración crítica con la labor docente y de la generación de estudios experimentales más robustos que permitan establecer evidencias sólidas y generalizables.
The rapid expansion of generative artificial intelligence has sparked growing interest in its educational applications, especially in areas requiring logical reasoning and abstraction. The objective of this systematic review was to analyze the impact of generative artificial intelligence on university student learning, as well as on lesson planning by faculty. The PRISMA guidelines were applied, defining inclusion and exclusion criteria based on PICO and PCC questions. A search of Scopus, Web of Science, and IEEE Xplore yielded 710 records, of which 67 met the established criteria. The results show literature dominated by descriptive studies, predominantly ChatGPT, which report benefits in motivation and productivity, although without conclusive evidence of improvements in academic performance. The research is concentrated in a few countries, with a lack of Latin American publications. In conclusion, the use of generative artificial intelligence offers promising pedagogical potential, but its effectiveness depends on its critical integration with teaching practices and the generation of more robust experimental studies that allow for the establishment of solid and generalizable evidence.
The rapid expansion of generative artificial intelligence has sparked growing interest in its educational applications, especially in areas requiring logical reasoning and abstraction. The objective of this systematic review was to analyze the impact of generative artificial intelligence on university student learning, as well as on lesson planning by faculty. The PRISMA guidelines were applied, defining inclusion and exclusion criteria based on PICO and PCC questions. A search of Scopus, Web of Science, and IEEE Xplore yielded 710 records, of which 67 met the established criteria. The results show literature dominated by descriptive studies, predominantly ChatGPT, which report benefits in motivation and productivity, although without conclusive evidence of improvements in academic performance. The research is concentrated in a few countries, with a lack of Latin American publications. In conclusion, the use of generative artificial intelligence offers promising pedagogical potential, but its effectiveness depends on its critical integration with teaching practices and the generation of more robust experimental studies that allow for the establishment of solid and generalizable evidence.
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Palabras clave
Inteligencia artificial generativa, ChatGPT, Educación Superior, Enseñanza de matemáticas, Enseñanza de programación
