The TalkMoves Dataset: K-12 mathematics lesson transcripts annotated for teacher and student discursive moves

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Publications

[1] Jacobs, J., Scornavacco, K., Harty, C., Suresh, A., Lai, V. & Sumner, T. (accepted, 2022). Promoting rich discussions in mathematics classrooms: Using personalized, automated feedback to support reflection and instructional change. Teaching and Teacher Education journal, Elseiver.

[2] Scornavacco, K., Jacobs, J. & Harty, C. (under review). Automated feedback on discourse moves: Teachers’ perceived utility of a big data tool. Paper submitted to the annual conference of the American Educational Research Association.

[3] Suresh, A., Jacobs, J., Clevenger, C., Lai, V., Tan, C., Ward, W., Martin, J. & Sumner, T., (2021). Using AI to Promote Equitable Classroom Discussions: The TalkMoves Application. Paper accepted at the 2021 conference on Artificial Intelligence in Education (AIED '21).

[4] Suresh, A., Jacobs, J., Lai, V., Tan, C., Ward, W., Martin, J. & Sumner, T., (2021). Using transformers to provide teachers with personalized feedback on their classroom discourse: The TalkMoves Application. Paper accepted and presented at the Spring AAAI 2021 Symposium on Artificial Intelligence for K-12 Education.

[5] Suresh, A., Sumner, T., Jacobs, J., Foland, B., & Ward, W. (2019). Automating Analysis and Feedback to Improve Mathematics Teachers’ Classroom Discourse. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 33, pp. 9721-9728)

[6] Suresh, A., Sumner, T., Huang, I., Jacobs, J., Foland, B., & Ward, W. (2018). Using deep learning to automatically detect talk moves in teachers' mathematics lessons. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 5445-5447). IEEE.