Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage dialogic teaching practice that makes students feel heard. We conduct a randomized controlled trial in an online computer science course (n=1,136 instructors), to evaluate the effectiveness of our tool. We find that M-Powering Teachers improves instructors’ uptake of student contributions by 13% and present suggestive evidence that it also improves students’ satisfaction with the course and assignment completion. These results demonstrate the promise of M-Powering Teachers to complement existing efforts in teachers’ professional development.
randomized controlled trial, natural language processing, teaching practices, online learning
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