research-article

Who did what? Who said that?: Collaid: an environment for capturing traces of collaborative learning at the tabletop

Authors:

Roberto Martínez,

Anthony Collins,

Kalina YacefAuthors Info & Claims

ITS '11: Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces

Pages 172 - 181

https://doi.org/10.1145/2076354.2076387

Published: 13 November 2011 Publication History

Abstract

Tabletops have the potential to provide new ways to support collaborative learning generally and, more specifically, to aid people in learning to collaborate more effectively. To achieve this potential, we need to gain understanding of how to design tabletop environments so that they capture relevant information about collaboration processes so that we can make it available in a form that is useful for learners, their teachers and facilitators. This paper draws upon research in computer supported collaborative learning to establish a set of principles for the design of a tabletop learning system. We then show how these have been used to design our Collaid (Collaborative Learning Aid) environment. Key features of this system are: capture of multi-modal data about collaboration in a tabletop activity using a microphone array and a depth sensor; integration of these data with other parts of the learning system; transforming the data into visualisations depicting the processes that occurred during the collaboration at the table; and sequence mining of the interaction logs. The main contributions of this paper are: our design guidelines to build the Collaid environment and the demonstration of its use in a collaborative concept mapping learning tool applying data mining and visualisations of collaboration.

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Cited By

Ni CLin CDykeman C(2023)Exploring Multimodality with Online Peer-Facilitated Experiential Learning in Group Work TrainingThe Journal for Specialists in Group Work10.1080/01933922.2023.225114148:4(299-316)Online publication date: 11-Sep-2023
https://doi.org/10.1080/01933922.2023.2251141
Osakwe IChen GFan YRakovic MLi XSingh SMolenaar IBannert MGašević D(2023)Reinforcement learning for automatic detection of effective strategies for self-regulated learningComputers and Education: Artificial Intelligence10.1016/j.caeai.2023.1001815(100181)Online publication date: 2023
https://doi.org/10.1016/j.caeai.2023.100181
Gao SYan SZhao HNathan AGao SYan SZhao HNathan A(2021)Emerging ApplicationsTouch-Based Human-Machine Interaction10.1007/978-3-030-68948-3_7(179-229)Online publication date: 26-Mar-2021
https://doi.org/10.1007/978-3-030-68948-3_7
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Index Terms

Who did what? Who said that?: Collaid: an environment for capturing traces of collaborative learning at the tabletop
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Touch screens
    2. Interaction paradigms
      1. Graphical user interfaces

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cover image ACM Conferences

ITS '11: Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces

November 2011

295 pages

ISBN:9781450308717

DOI:10.1145/2076354

General Chairs:
Jun Rekimoto
The University of Tokyo / Sony CSL, Japan
,
Hideki Koike
University of Electro-Communications, Japan
,
Kentaro Fukuchi
Meiji University, Japan
,
Program Chairs:
Yoshifumi Kitamura
Tohoku University, Japan
,
Daniel Wigdor
University of Toronto, Canada

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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New York, NY, United States

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Published: 13 November 2011

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ITS'11

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SIGCHI

ITS'11: Interactive Tabletops and Surfaces

November 13 - 16, 2011

Kobe, Japan

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Overall Acceptance Rate 119 of 418 submissions, 28%

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Cited By

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https://doi.org/10.1080/01933922.2023.2251141
Osakwe IChen GFan YRakovic MLi XSingh SMolenaar IBannert MGašević D(2023)Reinforcement learning for automatic detection of effective strategies for self-regulated learningComputers and Education: Artificial Intelligence10.1016/j.caeai.2023.1001815(100181)Online publication date: 2023
https://doi.org/10.1016/j.caeai.2023.100181
Gao SYan SZhao HNathan AGao SYan SZhao HNathan A(2021)Emerging ApplicationsTouch-Based Human-Machine Interaction10.1007/978-3-030-68948-3_7(179-229)Online publication date: 26-Mar-2021
https://doi.org/10.1007/978-3-030-68948-3_7
Paquette LBosch N(2020)The Invisible Breadcrumbs of Digital LearningHandbook of Research on Digital Learning10.4018/978-1-5225-9304-1.ch019(302-316)Online publication date: 2020
https://doi.org/10.4018/978-1-5225-9304-1.ch019
Amarasinghe IHernandez-Leo DMichos KVujovic M(2020)An Actionable Orchestration Dashboard to Enhance Collaboration in the ClassroomIEEE Transactions on Learning Technologies10.1109/TLT.2020.302859713:4(662-675)Online publication date: 1-Oct-2020
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Renaud Kvan Biljon Jde Villiers CSmuts H(2019)A Framework to Maximise the Communicative Power of Knowledge VisualisationsProceedings of the South African Institute of Computer Scientists and Information Technologists 201910.1145/3351108.3351111(1-10)Online publication date: 17-Sep-2019
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Di Mitri DSchneider JKlemke RSpecht MDrachsler HHsiao SCunningham JMcCarthy KLynch GBrooks CFerguson RHoppe U(2019)Read Between the LinesProceedings of the 9th International Conference on Learning Analytics & Knowledge10.1145/3303772.3303776(51-60)Online publication date: 4-Mar-2019
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Rich KStrickland CBinkowski TMoran CFranklin D(2018)K--8 learning trajectories derived from research literatureACM Inroads10.1145/31835089:1(46-55)Online publication date: 30-Jan-2018
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