Math Discourse Linguistic Components (Cohesive Cues within a Math Discussion Board Discourse)

Michelle Banawan, Jinnie Shin, Renu Balyan, Walter L. Leite, Danielle S. McNamara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study presents the results of a computational discourse analysis of discussion threads within an online Math tutoring platform. This work is theoretically motivated by prior work that established the importance of linguistic and semantic features in the discourse in mathematics education. The end goal of this study is to understand the characteristics of language that is produced and used within a discussion board for math. The discussion board corpus comprises of posts from 4,720 students, teachers, and study experts who interacted within an online teaching and learning tutoring platform for math. Linguistic profiles of the discussion board discourse were estimated using Principal Component Analysis (PCA) based on Coh-Metrix linguistic features related to cohesion, language sophistication, and lexical characteristics. The PCA analysis yielded seven Math Discourse Linguistic Components, which collectively explained 49% of the variance in the dataset. Theoretical and conceptual validation of components revealed that the linguistic features align with the communication goal and the nature of mathematics. The linguistic profiles that characterized the discussion board discourse included referential cohesion, information density, instructional language, lexical variation, compare and contrast devices, explicit relations devices, and syntactic complexity. The dominance of cohesive cues within the linguistic profiles demonstrate the communication goals within the Math discourse such as elaboration, providing instruction, compare and contrast, establishing explicit relations, and presenting information. As such, these components characterize the Math Discussion Board discourse in terms of variations in cohesive and task-oriented cues within communication among students.

Original languageEnglish (US)
Title of host publicationL@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale
PublisherAssociation for Computing Machinery, Inc
Pages389-394
Number of pages6
ISBN (Electronic)9781450391580
DOIs
StatePublished - Jun 1 2022
Externally publishedYes
Event9th Annual ACM Conference on Learning at Scale, L@S 2022 - New York City, United States
Duration: Jun 1 2022Jun 3 2022

Publication series

NameL@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale

Conference

Conference9th Annual ACM Conference on Learning at Scale, L@S 2022
Country/TerritoryUnited States
CityNew York City
Period6/1/226/3/22

Keywords

  • coh-metrix
  • discussion boards
  • mathematics language profiles
  • online algebra learning
  • principal component analysis

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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