Inteligencia artificial y sus implicancias en el contexto educativo: una revisión sistemática

Implications of artificial intelligence in the educational context: a systematic review

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Introducción: Los sistemas inteligentes se han consolidado como una fuerza transformadora en la educación global, lo que genera la necesidad de sintetizar la evidencia empírica disponible sobre su impacto axiológico y metodológico. Objetivo: Analizar las implicaciones educativas de la Inteligencia Artificial para identificar tendencias, convergencias y vacíos en su integración pedagógica, ética y operativa. Metodología: Revisión sistemática de diseño descriptivo, de acuerdo con el protocolo PRISMA. Se consultaron las bases de datos Scopus y Web of Science, al aplicar análisis de contenido con matriz de extracción de datos. Resultados: Se incluyeron 23 estudios; el 56,5% se publicó en 2025, el 26,1% en 2024 y el 17,4% en 2026. Se identificaron cuatro categorías temáticas: personalización del aprendizaje, evaluación e integridad académica, percepciones y ética, y formación docente. Se evidencia que esta tecnología ofrece personalización del aprendizaje y retroalimentación efectiva, pero enfrenta desafíos en evaluación compleja, integridad académica y brechas de confianza. Conclusión: Su eficiencia depende del diseño pedagógico, la capacitación especializada de los profesores y gobernanza ética. El enfoque híbrido, humano-Inteligencia Artificial, bajo supervisión experta es la vía más viable.
Introduction: Intelligent systems have become a transformative force in global education, generating a need to synthesize the available empirical evidence on their axiological and methodological impact. Objective: To analyze the educational implications of Artificial Intelligence in order to identify trends, convergences, and gaps in its pedagogical, ethical, and operational integration. Methodology: A descriptive systematic review was conducted, following the PRISMA protocol. The Scopus and Web of Science databases were consulted, applying content analysis with a data extraction matrix. Results: Twenty-three studies were included; 56.5% were published in 2025, 26.1% in 2024, and 17.4% in 2026. Four thematic categories were identified: personalized learning, assessment and academic integrity, perceptions and ethics, and teacher training. The study shows that this technology offers personalized learning and effective feedback, but faces challenges in complex assessment, academic integrity, and trust gaps. Conclusion: Its effectiveness depends on pedagogical design, specialized teacher training, and ethical governance. The hybrid human-Artificial Intelligence approach, under expert supervision, is the most viable path.

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Vásquez Díaz, V., Rafael Manya, A., & Bernal Guevara, A. (2026). Inteligencia artificial y sus implicancias en el contexto educativo: una revisión sistemática. Revista Tribunal, 6(17), 1-16. https://doi.org/10.59659/revistatribunal.v6i17.566
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

Vásquez Díaz, V., Rafael Manya, A., & Bernal Guevara, A. (2026). Inteligencia artificial y sus implicancias en el contexto educativo: una revisión sistemática. Revista Tribunal, 6(17), 1-16. https://doi.org/10.59659/revistatribunal.v6i17.566

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