Impacts of an AI-Enhanced Teacher Professional Learning Program on Math Instruction and Performance

Disengagement from mathematics during middle and high school is a widespread concern that contributes to lower academic achievement and diminished long-term participation in STEM fields. Research shows that students' beliefs about their ability to grow and improve—often referred to as growth mindsets—can significantly enhance motivation, persistence, and performance. However, classroom environments and teacher practices play a critical role in shaping these beliefs. This project evaluates a professional development program, Fellowship Using the Science of Engagement (FUSE), designed to help 6th through 9th grade math teachers adopt instructional practices that foster growth mindset-supportive learning environments. The program provides teachers with research-based insights into adolescent development, structured opportunities to revise their instructional language and feedback practices, and personalized guidance through AI-supported coaching. The study examines whether the FUSE program improves teacher mindsets, communication practices, and well-being, and whether these changes lead to increased student motivation, improved perceptions of classroom climate, and higher performance on state mathematics assessments.

Full Description

Disengagement from mathematics during middle and high school is a widespread concern that contributes to lower academic achievement and diminished long-term participation in STEM fields. Research shows that students' beliefs about their ability to grow and improve—often referred to as growth mindsets—can significantly enhance motivation, persistence, and performance. However, classroom environments and teacher practices play a critical role in shaping these beliefs. This project evaluates a professional development program, Fellowship Using the Science of Engagement (FUSE), designed to help 6th through 9th grade math teachers adopt instructional practices that foster growth mindset-supportive learning environments. The program provides teachers with research-based insights into adolescent development, structured opportunities to revise their instructional language and feedback practices, and personalized guidance through AI-supported coaching. The study examines whether the FUSE program improves teacher mindsets, communication practices, and well-being, and whether these changes lead to increased student motivation, improved perceptions of classroom climate, and higher performance on state mathematics assessments.

To evaluate the effectiveness of the FUSE program, the research team will conduct a large-scale randomized controlled trial across a representative sample of Texas public schools. Schools will be randomly selected and all 6th to 9th grade math teachers within each school will be eligible to participate. Participating teachers will be randomly assigned to either the FUSE intervention group or a placebo control group receiving unrelated professional development content. The FUSE program combines asynchronous instructional modules, live virtual coaching sessions, and AI-driven feedback tools to support teacher learning. Data will be collected throughout the academic year through teacher and student surveys, administrative records, and coded classroom video and audio recordings. Key outcomes will include teacher beliefs, instructional practices, emotional well-being, and retention, as well as student motivation, mindset, perceptions of instructional climate, and performance on standardized mathematics exams. The study will also examine how contextual factors such as school setting, teacher background, and classroom characteristics moderate program impact, with the goal of identifying the conditions under which professional learning interventions are most effective and scalable.

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