Predicting Collaboration based on Students' Pauses in Online CSCL Conversations

Sibel Denisleam (Molomer); Mihai Dascalu; Stefan Trausan-Matu

Predicting Collaboration based on Students' Pauses in Online CSCL Conversations

Sibel Denisleam (Molomer)
, Mihai Dascalu
, Stefan Trausan-Matu

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

As Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to traditional educational scenarios, the need for automated tools capable of evaluating active participation and collaboration among peers in online discussions increases. In this study, we validate a quantitative model of predicting involvement in CSCL chats based on student’s pauses throughout the timeline of the conversation. Starting from a corpus of 10 chat conversations, our proposed model explains 55% of the variance in terms of student participation and 42% in terms of collaboration, although relying on simple quantitative indices.

Original language	English
Pages (from-to)	83-92
Journal	Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science
Volume	79
Issue number	2
Publication status	Published - Oct 2017
Externally published	Yes

Keywords

Computer Supported Collaborative Learning
pause analysis
fluency
speed
automatic evaluation of participation and collaboration

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Predicting Collaboration based on Students' Pauses_pdfFinal published version, 620 KBLicence: CC BY-NC-ND

https://www.researchgate.net/publication/320430956_Predicting_collaboration_based_on_students'_pauses_in_online_CSCL_conversationsLicence: CC BY-NC-ND

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European Union
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Project: Research

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Denisleam (Molomer), S., Dascalu, M., & Trausan-Matu, S. (2017). Predicting Collaboration based on Students' Pauses in Online CSCL Conversations. Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science, 79(2), 83-92. https://www.researchgate.net/publication/320430956_Predicting_collaboration_based_on_students'_pauses_in_online_CSCL_conversations

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title = "Predicting Collaboration based on Students' Pauses in Online CSCL Conversations",

abstract = "As Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to traditional educational scenarios, the need for automated tools capable of evaluating active participation and collaboration among peers in online discussions increases. In this study, we validate a quantitative model of predicting involvement in CSCL chats based on student{\textquoteright}s pauses throughout the timeline of the conversation. Starting from a corpus of 10 chat conversations, our proposed model explains 55\% of the variance in terms of student participation and 42\% in terms of collaboration, although relying on simple quantitative indices.",

keywords = "Computer Supported Collaborative Learning, pause analysis, fluency, speed, automatic evaluation of participation and collaboration",

author = "\{Denisleam (Molomer)\}, Sibel and Mihai Dascalu and Stefan Trausan-Matu",

year = "2017",

month = oct,

language = "English",

volume = "79",

pages = "83--92",

journal = "Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science",

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Denisleam (Molomer), S, Dascalu, M & Trausan-Matu, S 2017, 'Predicting Collaboration based on Students' Pauses in Online CSCL Conversations', Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science, vol. 79, no. 2, pp. 83-92. <https://www.researchgate.net/publication/320430956_Predicting_collaboration_based_on_students'_pauses_in_online_CSCL_conversations>

Predicting Collaboration based on Students' Pauses in Online CSCL Conversations. / Denisleam (Molomer), Sibel; Dascalu, Mihai; Trausan-Matu, Stefan.
In: Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science, Vol. 79, No. 2, 10.2017, p. 83-92.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Predicting Collaboration based on Students' Pauses in Online CSCL Conversations

AU - Denisleam (Molomer), Sibel

AU - Dascalu, Mihai

AU - Trausan-Matu, Stefan

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N2 - As Computer Supported Collaborative Learning (CSCL) gains a broader usage as a viable alternative to traditional educational scenarios, the need for automated tools capable of evaluating active participation and collaboration among peers in online discussions increases. In this study, we validate a quantitative model of predicting involvement in CSCL chats based on student’s pauses throughout the timeline of the conversation. Starting from a corpus of 10 chat conversations, our proposed model explains 55% of the variance in terms of student participation and 42% in terms of collaboration, although relying on simple quantitative indices.

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KW - Computer Supported Collaborative Learning

KW - pause analysis

KW - fluency

KW - speed

KW - automatic evaluation of participation and collaboration

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JO - Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science

JF - Polytechnical University of Bucharest. Scientific Bulletin. Series C: Electrical Engineering and Computer Science

IS - 2

ER -

Predicting Collaboration based on Students' Pauses in Online CSCL Conversations

Abstract

Keywords

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