Data Science in Education

Automated feedback provides a scalable approach to supporting teacher reflection and improving instruction. 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 a 4-5 week pilot of providing professional learning and automated feedback to K-12 teachers. We examined its impact on teacher well-being, teaching practice, classroom talk, and student engagement.

Findings indicate that automated feedback is associated with reductions in teacher burnout, improvements in self-efficacy, and increased perceptions of student engagement. Impacts on teaching practices were mixed: teachers increased their use of specific praise and wait time but decreased their use of open-ended questions and pressing students for reasoning. 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.