Towards a Pragmatic and Theory-Driven Framework for Multimodal Collaboration Feedback

Maurice Boothe, Collin Yu, Armanda Lewis, Xavier Ochoa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an overarching framework for automated collaboration feedback that bridges theory and tool as well as technology and pedagogy. This pragmatic and theory-driven framework guides our thinking by outlining the components involved in converting theoretical collaboration constructs into features that can be automatically extracted and then converted into actionable feedback. Focusing on the pedagogical components of the framework, the constructs are validated by mapping them onto a selection of multi-disciplinary collaboration frameworks. The resulting behavioral indicators are then applied to measure collaboration in a sample scenario and those measurements are then used to exemplify how feedback analytics could be calculated. The paper concludes with a discussion on how those analytics could be converted into feedback for students and the next steps needed to advance the technological part of the framework.

Original languageEnglish (US)
Title of host publicationLAK 2022 - Conference Proceedings
Subtitle of host publicationLearning Analytics for Transition, Disruption and Social Change - 12th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages507-513
Number of pages7
ISBN (Electronic)9781450395731
DOIs
StatePublished - Mar 21 2022
Event12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022 - Virtual, Online, United States
Duration: Mar 21 2022Mar 25 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022
Country/TerritoryUnited States
CityVirtual, Online
Period3/21/223/25/22

Keywords

  • collaboration analytics
  • learning collaboration
  • teaching collaboration

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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