Inteligencia artificial y satisfacción académica en educación superior rural peruana: Análisis bibliométrico en Apurímac, 2018-2025

Artificial Intelligence and Academic Satisfaction in Peruvian Rural Higher Education: Bibliometric Analysis in Apurímac, 2018-2025

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Introducción: La inteligencia artificial (IA) se ha convertido en una de las transformaciones más relevantes de la educación contemporánea, debido a su capacidad para automatizar procesos y reconfigurar la enseñanza, el aprendizaje, la evaluación y el acompañamiento estudiantil en la educación superior. Su expansión plantea especial interés en contextos rurales, donde persisten brechas de conectividad y acceso tecnológico. Objetivo: Realizar un análisis bibliométrico de la producción científica sobre inteligencia artificial y satisfacción académica en la educación superior pública, con énfasis en el contexto rural de Apurímac, Perú, durante el periodo 2018-2025. Metodología: Se desarrolló una investigación cuantitativa, descriptiva, no experimental y transversal. La búsqueda se realizó en Scopus mediante un procedimiento estructurado basado en el protocolo PRISMA. Se analizaron 381 documentos depurados según DOI, autoría y afiliación. La producción científica fue procesada mediante VOSviewer y Bibliometrix para elaborar mapas de coautoría, coocurrencia y rendimiento científico. Resultados: Los hallazgos evidenciaron un crecimiento sostenido de la producción científica sobre IA y satisfacción académica, pasando de 2 publicaciones en 2018 a 120 en 2025. El análisis de redes permitió identificar tendencias de colaboración y núcleos temáticos relacionados con la personalización del aprendizaje, innovación educativa y transformación digital. Sin embargo, los contextos rurales presentan desafíos asociados con conectividad, infraestructura y preparación docente. Conclusiones: La inteligencia artificial presenta potencial para favorecer la personalización del aprendizaje y fortalecer la experiencia académica en la educación superior. No obstante, su aprovechamiento en contextos rurales como Apurímac requiere políticas orientadas a la equidad digital, ampliación de la conectividad y formación docente continua para garantizar una implementación inclusiva y sostenible.
Introduction: Artificial intelligence (AI) has become one of the most significant transformations in contemporary education due to its capacity to automate processes and reshape teaching, learning, assessment, and student support in higher education. Its expansion has generated particular interest in rural contexts, where connectivity and technological access gaps persist. Objective: To conduct a bibliometric analysis of scientific production on artificial intelligence and academic satisfaction in public higher education, with an emphasis on the rural context of Apurímac, Peru, during the 2018-2025 period. Methodology: A quantitative, descriptive, non-experimental, cross-sectional study was conducted. The search was performed in Scopus using a structured procedure based on the PRISMA protocol. A total of 381 documents, screened according to DOI, authorship, and affiliation, were analyzed. Scientific production was processed using VOSviewer and Bibliometrix to generate co-authorship, co-occurrence, and scientific performance maps. Results: The findings revealed sustained growth in scientific production on AI and academic satisfaction, increasing from 2 publications in 2018 to 120 in 2025. Network analysis identified collaboration trends and thematic clusters related to personalized learning, educational innovation, and digital transformation. However, rural contexts face challenges associated with connectivity, infrastructure, and teacher preparedness. Conclusions: Artificial intelligence has the potential to promote personalized learning and strengthen the academic experience in higher education. Nevertheless, its effective use in rural contexts such as Apurímac requires policies focused on digital equity, expanded connectivity, and continuous teacher training to ensure inclusive and sustainable implementation.

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Rios Contreras, R., Serrano Quispe, F., Quispe Atoccsa, J. A., & Contreras Cortez, S. (2026). Inteligencia artificial y satisfacción académica en educación superior rural peruana: Análisis bibliométrico en Apurímac, 2018-2025. Revista Tribunal, 6(17), 1-19. https://doi.org/10.59659/revistatribunal.v6i17.580
Número
Vol. 6 Núm. 17 (2026): Tribunal. Revista en Ciencias de la Educación y Ciencias Jurídicas. Octubre – Diciembre 2026
Sección
Artículos de Revisión
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Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.

Cómo citar

Rios Contreras, R., Serrano Quispe, F., Quispe Atoccsa, J. A., & Contreras Cortez, S. (2026). Inteligencia artificial y satisfacción académica en educación superior rural peruana: Análisis bibliométrico en Apurímac, 2018-2025. Revista Tribunal, 6(17), 1-19. https://doi.org/10.59659/revistatribunal.v6i17.580

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