Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course
Article Status
Published
Authors/contributors
- Demszky, Dorottya (Author)
- Liu, Jing (Author)
- Hill, Heather C. (Author)
- Jurafsky, Dan (Author)
- Piech, Chris (Author)
Title
Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course
Abstract
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.
Institution
Annenberg Institute at Brown University
Date
Sat, 06/03/2023 - 12:00
Language
en
Short Title
Can Automated Feedback Improve Teachers’ Uptake of Student Ideas?
Accessed
01/02/2024, 13:54
Library Catalogue
Extra
Publication Title: EdWorkingPapers.com
Citation
Demszky, D., Liu, J., Hill, H. C., Jurafsky, D., & Piech, C. (2023). Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial In a Large-Scale Online Course. Annenberg Institute at Brown University. https://edworkingpapers.com/ai21-483
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