Abstract
Pair programmers utilizing more Exploratory (critical, constructive) talk has been shown to help students achieve a better mutual understanding of problems they are solving. In this paper, we investigate the promise of fine tuning a pretrained transformer-based machine learning model to classify utterances into Exploratory, Cumulative, and Disputational talk. The task of classifying utterances into different types of collaborative talk was approached as a multi-label text classification problem. This is the first successful automatic classification of utterances into the different types of collaborative talk.
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Acknowledgements
We would like to thank Zarifa Zakaria, Jessica Vandenberg, Jennifer Tsan, Danielle Cadieux Boulden, Collin F. Lynch, and Eric N. Wiebe from North Carolina State University, Raleigh, NC, USA and Kristy Elizabeth Boyer from University of Florida, Gainesville, FL, USA for granting us access to the dataset used in this paper.
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Ubani, S., Nielsen, R. (2022). Classifying Different Types of Talk During Collaboration. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. AIED 2022. Lecture Notes in Computer Science, vol 13356. Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_40
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