Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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This study examines the reliability and accuracy of large language models (LLMs) for automated classroom observation using the World Bank's TEACH Primary framework. As education systems increasingly explore AI-based tools to scale teacher feedback and professional development, empirical validation of these systems is critical. Using a corpus of 12 primary classroom videos, we compared 8618 AI-generated evaluations from eight LLM endpoints against consensus-based ratings from certified TEACH experts. To account for model stochasticity, each model produced 10 independent evaluations per video–element pair. Reliability was assessed using variability and inter-rater consistency indicators,...

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