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AI-driven assessment of human tutor training performance correlates with real-life tutoring quality; bridges the gap between training metrics and classroom practice.

Synthesis

AI-Driven Assessment of Human Tutors: Linking Training Performance to Real-Life Practice investigates ai-driven assessment of human tutor training performance correlates with real-life tutoring quality; bridges the gap between training metrics and classroom practice. This work connects to existing research on intelligent-tutoring-systems by demonstrating that Abstract:There exist numerous tutor training platforms. However, few provide AI-driven training and evaluation for human tutors based on real-life performance. We present an AI-driven system that assesses both open responses during training and authentic real-life tutoring. Unlike platforms that onl....

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  • Citation

    Danielle R. Thomas, Marie Cynthia Abijuru Kamikazi, Clara Brandt, Conrad Borchers, Kenneth R. Koedinger (2026). AI-Driven Assessment of Human Tutors: Linking Training Performance to Real-Life Practice. arXiv:2606.18617.