Advancing computational grounded theory for audiovisual data from mathematics classrooms

Cynthia D'Angelo, Elizabeth Dyer, Christina Krist, Josh Rosenberg, Nigel Bosch

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

Abstract

This poster will discuss early findings from a project that is developing theory-based approaches to combine computational methods and qualitative grounded theory in order to analyze classroom video data of middle school mathematics classrooms. These early findings involve the feasibility of using out-of-the-box implementations of video and audio processing algorithms for analysis of video and audio data, focusing on methods to capture instances of collaboration and student-teacher interactions.

Original languageEnglish (US)
Title of host publication14th International Conference of the Learning Sciences
Subtitle of host publicationThe Interdisciplinarity of the Learning Sciences, ICLS 2020 - Conference Proceedings
EditorsMelissa Gresalfi, Ilana Seidel Horn
PublisherInternational Society of the Learning Sciences (ISLS)
Pages2393-2394
Number of pages2
ISBN (Electronic)9781732467286
DOIs
StatePublished - 2020
Event14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 - Nashville, United States
Duration: Jun 19 2020Jun 23 2020

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume4
ISSN (Print)1573-4552

Conference

Conference14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020
Country/TerritoryUnited States
CityNashville
Period6/19/206/23/20

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Education

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