TeamSlides: a Multimodal Teamwork Analytics dashboard for teacher-guided reflection in a physical learning space

Vanessa Echeverria, Lixiang Yan, Linxuan Zhao, Sophie Abel, Riordan Alfredo, Samantha Dix, Hollie Jaggard, Rosie Wotherspoon, Abra Osborne, Simon Buckingham Shum, Dragan Gasevic, Roberto Martinez-Maldonado

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

14 Citations (Scopus)

Abstract

Advancements in Multimodal Learning Analytics (MMLA) have the potential to enhance the development of effective teamwork skills and foster reflection on collaboration dynamics in physical learning environments. Yet, only a few MMLA studies have closed the learning analytics loop by making MMLA solutions immediately accessible to educators to support reflective practices, especially in authentic settings. Moreover, deploying MMLA solutions in authentic settings can bring new challenges beyond logistic and privacy issues. This paper reports the design and use of TeamSlides, a multimodal teamwork analytics dashboard to support teacher-guided reflection. We conducted an in-the-wild classroom study involving 11 teachers and 138 students. Multimodal data were collected from students working in team healthcare simulations. We examined how teachers used the dashboard in 22 debrief sessions to aid their reflective practices. We also interviewed teachers to discuss their perceptions of the dashboard's value and the challenges faced during its use. Our results suggest that the dashboard effectively reinforced discussions and augmented teacher-guided reflection practices. However, teachers encountered interpretation conflicts, sometimes leading to mistrust or misrepresenting the information. We discuss the considerations needed to overcome these challenges in MMLA research.

Original languageEnglish
Title of host publicationLAK 2024 Conference Proceedings - The Fourteenth International Conference on Learning Analytics & Knowledge
EditorsSrecko Joksimovic, Andrew Zamecnik
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages112-122
Number of pages11
ISBN (Electronic)9798400716188
DOIs
Publication statusPublished - 2024
EventInternational Learning Analytics & Knowledge Conference 2024 - Kyoto, Japan
Duration: 18 Mar 202422 Mar 2024
Conference number: 14th
https://dl.acm.org/doi/proceedings/10.1145/3636555 (Conference Proceedings)
https://www.solaresearch.org/events/lak/lak24/
https://ceur-ws.org/Vol-3667/ (LAK 2024 Workshop Proceedings)

Conference

ConferenceInternational Learning Analytics & Knowledge Conference 2024
Abbreviated titleLAK 2024
Country/TerritoryJapan
CityKyoto
Period18/03/2422/03/24
Internet address

Keywords

  • dashboards
  • MMLA
  • reflection
  • team dynamics
  • teamwork analytics
  • visualisation

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