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Equity and bias in automated educational evaluation systems based on artificial intelligence

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  • Pamela Navarro Escobar

    (Centro de Investigación, Desarrollo e Innovación JYMNIJA, Oruro, Bolivia)

Abstract

Introduction: Equidad y sesgos en sistemas automatizados de evaluación educativa basados en inteligencia artificial is an emerging higher-education issue related to measurement quality, decision-making and learning experience. Objective: To systematically synthesize available evidence and identify patterns of effectiveness, methodological quality and implementation conditions. Method: A PRISMA-oriented systematic review was conducted on a consolidated academic corpus of 135 records; 7 studies met relevance and documentary sufficiency criteria. Results: Evidence was methodologically heterogeneous but converged on the need to align technology, constructs, feedback and educational decisions. Conclusions: Findings support evidence-informed adoption, institutional monitoring and continuous assessment of validity, equity and utility.

Suggested Citation

  • Pamela Navarro Escobar, 2025. "Equity and bias in automated educational evaluation systems based on artificial intelligence," Medicion y Evaluacion del Aprendizaje Inclusivo, Facultad de Derecho, Ciencias Politicas y Sociales de la Universidad Tecnica de Oruro, vol. 2(2), pages 1-16, July.
    • Handle: RePEc:cxn:evalua:v:2:y:2025:i:2:id:16
    DOI: 10.63688/aprendizaje.v2.i2.16
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