@inproceedings{80f67cdf644744e896464d19aaa28915,
title = "Advancing computational grounded theory for audiovisual data from mathematics classrooms",
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.",
author = "Cynthia D'Angelo and Elizabeth Dyer and Christina Krist and Josh Rosenberg and Nigel Bosch",
note = "Funding Information: This material is based upon work supported by the National Science Foundation under Grant No. DRL-1920796. Publisher Copyright: {\textcopyright} 2020 International Society of the Learning Sciences (ISLS). All rights reserved.; 14th International Conference of the Learning Sciences: The Interdisciplinarity of the Learning Sciences, ICLS 2020 ; Conference date: 19-06-2020 Through 23-06-2020",
year = "2020",
doi = "10.22318/icls2020.2393",
language = "English (US)",
series = "Computer-Supported Collaborative Learning Conference, CSCL",
publisher = "International Society of the Learning Sciences (ISLS)",
pages = "2393--2394",
editor = "Melissa Gresalfi and Horn, {Ilana Seidel}",
booktitle = "14th International Conference of the Learning Sciences",
}