Using AI to advance elementary teacher instruction
Impact Storyteller
Impact Storyteller Name
Peter Youngs, PI
Project summary
We have developed models that can automatically classify activity structures and teaching activities in videos of elementary mathematics instruction. We drew on data that had been collected for a previous NSF study in Virginia, Michigan, and Connecticut.
What are the real world impacts of your project?
The models we developed will make it easier for:
- elementary teachers to analyze their mathematics instruction
- instructional coaches, principals, and teacher educators to support elementary teachers in teaching mathematics
- researchers to analyze videos of elementary mathematics instruction in an efficient way
How has your project contributed to STEM education more generally?
We have published articles based on our findings in instructional technology/computer science and education journals and in electrical and computer engineering journals.
Would this project have been possible without EDU funding?
No.
ECR Project
Project Website
Funding Type
ECR:Core
