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An analysis of conversational volatility during telecollaboration sessions for second language learning

Dey-Plissonneau, Aparajita, Lee, Hyowon orcid logoORCID: 0000-0003-4395-7702, Liu, Mingming orcid logoORCID: 0000-0002-8988-2104, Patel, Vyoma, Scriney, Michael orcid logoORCID: 0000-0001-6813-2630 and Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389 (2022) An analysis of conversational volatility during telecollaboration sessions for second language learning. In: 8th International Conference on Higher Education Advances (HEAd’22), 14-17 June 2022, Valencia, Spain. ISBN 978-84-1396-003-6

Abstract
Tandem telecollaboration is a pedagogy used in second language learning where mixed groups of students meet online in videoconferencing sessions to practice their conversational skills in their target language. We have built and deployed a system called L2 Learning to support post-session review and self-reflection on students’ participation in such meetings. We automatically compute a metric called Conversational Volatility which quantifies the amount of interaction among participants, indicating how dynamic or flat the conversations were. Our analysis on more than 100 hours of video recordings involving 28 of our students indicates that conversations do not get more dynamic as meetings progress, that there is a wide variety of levels of interaction across students and student groups, and the speaking in French appears to have more animated conversations than speaking in English, though the reasons for that are not clear.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:PP. 644-652
Uncontrolled Keywords:Telecollaboration; Second Language Learning; Conversational Dialogue, Videoconferencing.
Subjects:Computer Science > Artificial intelligence
Computer Science > Multimedia systems
Computer Science > Digital video
Humanities > French language
Humanities > Language
Humanities > Video recordings
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Applied Language and Intercultural Studies
Research Institutes and Centres > INSIGHT Centre for Data Analytics
Published in: 8th International Conference on Higher Education Advances (HEAd’22), Proceedings. . Editorial Universitat Politècnica de València. ISBN 978-84-1396-003-6
Publisher:Editorial Universitat Politècnica de València
Official URL:https://doi.org/10.4995/HEAd22.2022.14466
Copyright Information:© 2022 The Authors.
Funders:Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289_P2 (Insight SFI Research Centre for Data Analytics), co-funded by the European Regional Development Fun
ID Code:27059
Deposited On:21 Jun 2022 12:54 by Alan Smeaton . Last Modified 17 Nov 2023 14:04
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