Using deep learning to automatically detect talk moves in teachers'mathematics lessons

摘要

Currently, providing teachers with detailed feedback about their classroom discourse strategies requires highly trained observers to hand code transcripts of classroom recordings to identify talk moves and/or one-on-one expert coaching. Both approaches are time-consuming and expensive, require considerable human expertise, and do not scale to large numbers of teachers. We are currently developing an innovative application, the TalkBack application, a new type of teacher learning environment based on the automated analysis of classroom recordings. The TalkBack application will utilize a big data infrastructure for managing and analyzing classroom recordings, including an embedded automated talk move classifier. The application will provide teachers with a detailed record of the discourse strategies used in their lessons. A central premise of our research is that this type of personalized, automated feedback can dramatically enhance teacher learning and support improvements in their instruction.The project will exemplify how next-generation repositories of classroom recordings can be architected to support large-scale research by enabling automated analyses based on machine learning models.