Simulating collaborative discourse data

Zachari Swiecki; Cody Marquart; Brendan Eagan

Simulating collaborative discourse data

Zachari Swiecki, Cody Marquart, Brendan Eagan

Department of Human Centred Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Abstract

We present a method for simulating collaborative discourse in terms of the patterns of codes present in the data. We argue that simulation methods have a successful history in other areas of social science, and that these methods can-and should-be adopted to study collaborative processes. We describe a novel simulation method that we have developed and provide evidence of the validity of this method by statistically comparing our observed data to simulated data. Furthermore, we show that using simulated data yields insights about collaborative processes that we would have missed if we had only examined the observed data.

Original language	English
Title of host publication	CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022
Editors	Armin Weinberger, Wenli Chen, Davinia Hernandez-Leo, Bodong Chen
Place of Publication	Bloomington IN USA
Publisher	International Society of the Learning Sciences
Pages	83-90
Number of pages	8
ISBN (Electronic)	9781737330646
Publication status	Published - 2022
Event	International Conference on Computer-Supported Collaborative Learning 2022 - Online, Japan Duration: 6 Jun 2022 → 10 Jun 2022 Conference number: 15th https://2022.isls.org/programs/cscl/ (Website) https://2022.isls.org/proceedings/ (Proceedings)

Publication series

Name	Proceedings of International Conference of the Learning Sciences, ICLS
Publisher	International Society of the Learning Sciences (ISLS)
ISSN (Print)	1814-9316

Conference

Conference	International Conference on Computer-Supported Collaborative Learning 2022
Abbreviated title	CSCL 2022
Country/Territory	Japan
Period	6/06/22 → 10/06/22
Internet address	https://2022.isls.org/programs/cscl/ (Website) https://2022.isls.org/proceedings/ (Proceedings)

Keywords

collaborative problem solving
simulation and modeling

Cite this

Swiecki, Z., Marquart, C., & Eagan, B. (2022). Simulating collaborative discourse data. In A. Weinberger, W. Chen, D. Hernandez-Leo, & B. Chen (Eds.), CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022 (pp. 83-90). (Proceedings of International Conference of the Learning Sciences, ICLS). International Society of the Learning Sciences.

Swiecki, Zachari ; Marquart, Cody ; Eagan, Brendan. / Simulating collaborative discourse data. CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022. editor / Armin Weinberger ; Wenli Chen ; Davinia Hernandez-Leo ; Bodong Chen. Bloomington IN USA : International Society of the Learning Sciences, 2022. pp. 83-90 (Proceedings of International Conference of the Learning Sciences, ICLS).

@inproceedings{eb2136d0c8ad49e2bec7ab50b330552c,

title = "Simulating collaborative discourse data",

abstract = "We present a method for simulating collaborative discourse in terms of the patterns of codes present in the data. We argue that simulation methods have a successful history in other areas of social science, and that these methods can-and should-be adopted to study collaborative processes. We describe a novel simulation method that we have developed and provide evidence of the validity of this method by statistically comparing our observed data to simulated data. Furthermore, we show that using simulated data yields insights about collaborative processes that we would have missed if we had only examined the observed data.",

keywords = "collaborative problem solving, simulation and modeling",

author = "Zachari Swiecki and Cody Marquart and Brendan Eagan",

note = "Funding Information: This work was funded in part by the National Science Foundation (DRL-1661036, DRL-1713110, DRL-2100320), the Wisconsin Alumni Research Foundation, and the Office of the Vice Chancellor for Research and Graduate Education at the University of Wisconsin-Madison. The opinions, findings, and conclusions do not reflect the views of the funding agencies, cooperating institutions, or other individuals. Publisher Copyright: {\textcopyright} ISLS.; International Conference on Computer-Supported Collaborative Learning 2022, CSCL 2022 ; Conference date: 06-06-2022 Through 10-06-2022",

year = "2022",

language = "English",

series = "Proceedings of International Conference of the Learning Sciences, ICLS",

publisher = "International Society of the Learning Sciences",

pages = "83--90",

editor = "Armin Weinberger and Wenli Chen and Davinia Hernandez-Leo and Bodong Chen",

booktitle = "CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022",

url = "https://2022.isls.org/programs/cscl/, https://2022.isls.org/proceedings/",

}

Swiecki, Z, Marquart, C & Eagan, B 2022, Simulating collaborative discourse data. in A Weinberger, W Chen, D Hernandez-Leo & B Chen (eds), CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022. Proceedings of International Conference of the Learning Sciences, ICLS, International Society of the Learning Sciences, Bloomington IN USA, pp. 83-90, International Conference on Computer-Supported Collaborative Learning 2022, Japan, 6/06/22.

Simulating collaborative discourse data. / Swiecki, Zachari; Marquart, Cody; Eagan, Brendan.

CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022. ed. / Armin Weinberger; Wenli Chen; Davinia Hernandez-Leo; Bodong Chen. Bloomington IN USA : International Society of the Learning Sciences, 2022. p. 83-90 (Proceedings of International Conference of the Learning Sciences, ICLS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AU - Marquart, Cody

AU - Eagan, Brendan

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PY - 2022

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N2 - We present a method for simulating collaborative discourse in terms of the patterns of codes present in the data. We argue that simulation methods have a successful history in other areas of social science, and that these methods can-and should-be adopted to study collaborative processes. We describe a novel simulation method that we have developed and provide evidence of the validity of this method by statistically comparing our observed data to simulated data. Furthermore, we show that using simulated data yields insights about collaborative processes that we would have missed if we had only examined the observed data.

AB - We present a method for simulating collaborative discourse in terms of the patterns of codes present in the data. We argue that simulation methods have a successful history in other areas of social science, and that these methods can-and should-be adopted to study collaborative processes. We describe a novel simulation method that we have developed and provide evidence of the validity of this method by statistically comparing our observed data to simulated data. Furthermore, we show that using simulated data yields insights about collaborative processes that we would have missed if we had only examined the observed data.

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KW - simulation and modeling

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M3 - Conference Paper

AN - SCOPUS:85145549860

T3 - Proceedings of International Conference of the Learning Sciences, ICLS

SP - 83

EP - 90

BT - CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022

A2 - Weinberger, Armin

A2 - Chen, Wenli

A2 - Hernandez-Leo, Davinia

A2 - Chen, Bodong

PB - International Society of the Learning Sciences

CY - Bloomington IN USA

T2 - International Conference on Computer-Supported Collaborative Learning 2022

Y2 - 6 June 2022 through 10 June 2022

ER -

Swiecki Z, Marquart C, Eagan B. Simulating collaborative discourse data. In Weinberger A, Chen W, Hernandez-Leo D, Chen B, editors, CSCL Proceedings - 15th International Conference on Computer-Supported Collaborative Learning (CSCL) 2022. Bloomington IN USA: International Society of the Learning Sciences. 2022. p. 83-90. (Proceedings of International Conference of the Learning Sciences, ICLS).

Simulating collaborative discourse data

Abstract

Publication series

Conference

Keywords

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Cite this