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Uso de Inteligencia Artificial en la Construcción de Pruebas: Una Guía Práctica
Javier Suárez-Álvarez1, Qiwei He2, Nigel Guenole3
1University of Massachusetts Amherst (USA).
Psicothema
|February 4, 2026
Resumen
La Inteligencia Artificial (IA) ofrece beneficios para la construcción de pruebas, pero requiere una implementación cuidadosa. Este estudio proporciona directrices para el uso responsable de la IA en el desarrollo y calibración de pruebas para garantizar la validez, fiabilidad y equidad.
Área de la Ciencia:
- Psicometría
- Inteligencia Artificial
- Evaluación Educativa
Sus antecedentes:
- La Inteligencia Artificial (IA) mejora la eficiencia y escalabilidad de la evaluación.
- La adopción de la IA en la construcción de pruebas es limitada entre investigadores y profesionales.
- Este estudio revisa las aplicaciones de la IA en la construcción de pruebas y propone directrices.
Objetivo del estudio:
- Revisar críticamente las aplicaciones actuales basadas en IA en la construcción de pruebas.
- Proponer directrices prácticas para la IA en el desarrollo y calibración de pruebas.
- Abordar los riesgos y maximizar los beneficios de la IA en la evaluación.
Principales métodos:
- Revisión exhaustiva de la literatura sobre IA en la construcción de pruebas.
- Enfoque en los procesos de desarrollo de ítems y calibración.
- Inclusión de ejemplos del mundo real para la implementación práctica.
Principales resultados:
- La evolución de las mejores prácticas para la IA en el desarrollo de pruebas requiere supervisión humana.
- La generación de ítems mediante IA requiere datos de calidad, alineación y validación.
- La calibración implica la validez del constructo, la ingeniería de indicaciones y la evaluación del ajuste del modelo.
Conclusiones:
- Se propone una guía práctica para la IA generativa en el desarrollo y calibración de pruebas.
- Las directrices abordan los desafíos de validez, fiabilidad y equidad.
- Promueve la implementación responsable y eficaz de la IA en la evaluación.
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