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Modeling One-on-one Online Tutoring Discourse using an Accountable Talk Framework

  • Renu Balyan
  • , Tracy Arner
  • , Karen Taylor
  • , Jinnie Shin
  • , Michelle Banawan
  • , Walter L. Leite
  • , Danielle S. McNamara
  • Arizona State University
  • University of Florida

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The National Council of Teachers of Mathematics (NCTM) has been emphasizing the importance of teachers’ pedagogical communication as part of mathematical teaching and learning for decades. Specifically, NCTM has provided guidance on how teachers can foster mathematical communication that positively impacts student learning. A teacher may have different academic goals towards what needs to be achieved in a classroom, which require a variety of discourse-based tools that allow students to engage fully in mathematical thinking and reasoning. Accountable or academically productive talk is one such approach for classroom discourse that may ensure that the discussions are coherent, purposeful and productive. This paper discusses the use of a transformer model for classifying classroom talk moves based on the accountable talk framework. We investigate the extent to which the classroom Accountable Talk framework can be successfully applied to one-onone online mathematics tutoring environments. We further propose a framework adapted from Accountable Talk, but more specifically aligned to one-on-one online tutoring. The model performance for the proposed framework is evaluated and compared with a small sample of expert coding. The results obtained from the proposed framework for one-on-one tutoring are promising and improve classification performance of the talk moves for our dataset.

Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on Educational Data Mining, EDM 2022
Editors[given-name]Antonija Mitrovic, Nigel Bosch
PublisherInternational Educational Data Mining Society
ISBN (Print)9781733673631
DOIs
StatePublished - 2022
Event15th International Conference on Educational Data Mining, EDM 2022 - Durham, United Kingdom
Duration: Jul 24 2022Jul 27 2022

Publication series

NameProceedings of the International Conference on Educational Data Mining

Conference

Conference15th International Conference on Educational Data Mining, EDM 2022
Country/TerritoryUnited Kingdom
CityDurham
Period07/24/2207/27/22

Keywords

  • accountable talk framework
  • classroom discourse
  • one-on-one online tutoring
  • transfer learning

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