Development of Pre-Service Teacher Reflection Through the Use of Artificial Intelligence Feedback
Schenk, Lauren
Schenk, Lauren
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2025-05-19
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Abstract
This study explores the use of artificial intelligence (AI) and targeted reflection to enhance the teaching practices of pre-service teachers. Utilizing the ClassifAI software, pre-service teachers received objective feedback on key instructional components, such as opportunities to respond, teacher talk versus student talk, and the level and amount of questioning. The research aimed to assess the effectiveness of AI-driven feedback and targeted reflection questions in providing pre-service teachers with valuable, objective insights to reflect on their instructional methods. The results indicate that the integration of AI and structured reflection significantly improved participants' awareness of their teaching practices, with a marked increase in the use of higher-order questions and a greater variety of opportunities for student response. Additionally, participants reported using AI as a tool to track their growth, set teaching goals, and refine their instructional strategies. Despite challenges in the accuracy of AI analysis and the limitations of audio-based data collection, the study demonstrates the potential of AI to support reflective practice and professional development in teacher preparation programs.