Automated Feedback Improves Teachers’ Questioning Quality in Brick-and-Mortar Classrooms: Opportunities for Further Enhancement

Academic Article

Academic article reporting results from a randomized controlled trial on automated feedback designed to improve teachers’ questioning quality in K-12 classrooms.

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Purpose/Abstract

AI-powered professional learning tools that provide teachers with individualized feedback on their instruction have proven effective at improving instruction and student engagement in virtual learning contexts.

Despite the need for consistent, personalized professional learning in K-12 settings, the effectiveness of automated feedback tools in traditional classrooms remains less explored.

The authors present results from 224 Utah mathematics and science teachers who participated in a pre-registered randomized controlled trial conducted in partnership with TeachFX to assess the impact of automated feedback in K-12 classrooms.

The feedback targeted “focusing questions,” which are questions that probe students’ thinking by pressing for explanations and reflection.

Teachers opened emails containing the automated feedback about 53–65% of the time, and the feedback increased their use of focusing questions by 20% compared with the control group.

The feedback did not impact other teaching practices. Qualitative interviews with 13 teachers revealed mixed perceptions of the automated feedback. Some teachers appreciated the reflective insights, while others faced barriers such as skepticism about accuracy, data privacy concerns, and time constraints.

The findings highlight both the promise of automated professional learning tools and areas for improvement in implementing effective, teacher-friendly feedback systems in brick-and-mortar classrooms.

Citation
Demszky, D., Liu, J., Hill, H. C., Sanghi, S., & Chung, A. (2025). Automated feedback improves teachers’ questioning quality in brick-and-mortar classrooms: Opportunities for further enhancement. Computers & Education, 227, 105183. https://doi.org/10.1016/j.compedu.2024.105183

Areas researched: Teacher outcomes, Student Learning, Professional Learning, AI

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