Scaling Teacher Professional Learning Through Automated Feedback: An Evaluation in K-12 Classrooms

Automated feedback provides a scalable approach to supporting teacher reflection and teaching practice. However, there is limited evidence on how these technologies impact multiple dimensions of teacher and student outcomes in authentic school settings. This mixed-methods study evaluated the implementation and short-term impacts of a 4–-5 week pilot providing K–-12 teachers with professional learning and automated feedback on teaching practices via the TeachFX application. We examined TeachFX’s impact on teacher well-being, teaching practice, classroom talk, and student engagement. Findings indicate that automated feedback is associated with reduced teacher burnout, improved self-efficacy, and increased perceptions of student engagement. Impacts on teaching practices were mixed, demonstrating both increases and decreases throughout the intervention period and varied by context. Results also suggested a shift from teacher discourse towards more student discourse over the course of the intervention. These findings suggest the potential of automated feedback to support teacher well-being and inform instructional changes, while highlighting areas for further research on sustaining and broadening practice improvements.