Abstract
Inclusion in mathematics education is strongly tied to discourse rich classrooms, where students ideas play a central role. Talk moves are specific discursive practices that promote inclusive and equitable participation in classroom discussions. This paper describes the development of the TalkMoves application, which provides teachers with detailed feedback on their usage of talk moves based on accountable talk theory. Building on our recent work to automate the classification of teacher talk moves, we have expanded the application to also include feedback on a set of student talk moves. We present results from several deep learning models trained to classify student sentences into student talk moves with performance up to 73% F1. The classroom data used for training these models were collected from multiple sources that were pre-processed and annotated by highly reliable experts. We validated the performance of the model on an out-of-sample dataset which included 166 classroom transcripts collected from teachers piloting the application.
Supported by National Science Foundation under Grant No. 1837986: The TalkBack Application: Automating Analysis and Feedback to Improve Mathematics Teachers’ Classroom Discourse.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)
Hand, V.: Seeing culture and power in mathematical learning: toward a model of equitable instruction. Educ. Stud. Math. 80(1), 233–247 (2012). https://doi.org/10.1007/s10649-012-9387-9
Khisty, L.L., Chval, K.B.: Pedagogic discourse and equity in mathematics: when teachers’ talk matters. Math. Educ. Res. J. 14(3), 154–168 (2002). https://doi.org/10.1007/BF03217360
Liu, Y., et al.: RoBERTa: a robustly optimized BERT pretraining approach. arXiv preprint arXiv:1907.11692 (2019)
Michaels, S., O’Connor, C., Resnick, L.B.: Deliberative discourse idealized and realized: accountable talk in the classroom and in civic life. Stud. Philos. Educ. 27(4), 283–297 (2008). https://doi.org/10.1007/s11217-007-9071-1
Moschkovich, J.: Principles and guidelines for equitable mathematics teaching practices and materials for English language learners. J. Urban Math. Educ. 6(1), 45–57 (2013)
O’Connor, C., Michaels, S.: Supporting teachers in taking up productive talk moves: the long road to professional learning at scale. Int. J. Educ. Res. 97, 166–175 (2019)
O’Connor, C., Michaels, S., Chapin, S.: Scaling down to explore the role of talk in learning: from district intervention to controlled classroom study. In: Socializing Intelligence Through Academic Talk and Dialogue, pp. 111–126 (2015)
Suresh, A., Sumner, T., Huang, I., Jacobs, J., Foland, B., Ward, W.: 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 (2018)
Suresh, A., Sumner, T., Jacobs, J., Foland, B., Ward, W.: Automating analysis and feedback to improve mathematics teachers’ classroom discourse. Proc. AAAI Conf. Artif. Intell. 33, 9721–9728 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Suresh, A. et al. (2021). Using AI to Promote Equitable Classroom Discussions: The TalkMoves Application. In: Roll, I., McNamara, D., Sosnovsky, S., Luckin, R., Dimitrova, V. (eds) Artificial Intelligence in Education. AIED 2021. Lecture Notes in Computer Science(), vol 12749. Springer, Cham. https://doi.org/10.1007/978-3-030-78270-2_61
Download citation
DOI: https://doi.org/10.1007/978-3-030-78270-2_61
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-78269-6
Online ISBN: 978-3-030-78270-2
eBook Packages: Computer ScienceComputer Science (R0)