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"Is It My Turn?": Assessing Teamwork and Taskwork in Collaborative Immersive Analytics

Published: 11 November 2022 Publication History

Abstract

Immersive analytics has the potential to promote collaboration in machine learning (ML). This is desired due to the specific characteristics of ML modeling in practice, namely the complexity of ML, the interdisciplinary approach in industry, and the need for ML interpretability. In this work, we introduce an augmented reality-based system for collaborative immersive analytics that is designed to support ML modeling in interdisciplinary teams. We conduct a user study to examine how collaboration unfolds when users with different professional backgrounds and levels of ML knowledge interact in solving different ML tasks. Specifically, we use the pair analytics methodology and performance assessments to assess collaboration and explore their interactions with each other and the system. Based on this, we provide qualitative and quantitative results on both teamwork and taskwork during collaboration. Our results show how our system elicits sustained collaboration as measured along six distinct dimensions. We finally make recommendations how immersive systems should be designed to elicit sustained collaboration in ML modeling.

Supplementary Material

ZIP File (v6cscw2479aux.zip)
Supplemental material contains: 1) Questionnaires used to collect user feedback and performance assessments; 2) Additional results from questionnaires, which have not been included in the paper.
MP4 File (v6cscw2479.mp4)
Supplemental video

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  • (2024)A Systematic Literature Review of User Evaluation in Immersive AnalyticsComputer Graphics Forum10.1111/cgf.1511143:3Online publication date: 10-Jun-2024

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      cover image Proceedings of the ACM on Human-Computer Interaction
      Proceedings of the ACM on Human-Computer Interaction  Volume 6, Issue CSCW2
      CSCW
      November 2022
      8205 pages
      EISSN:2573-0142
      DOI:10.1145/3571154
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      Published: 11 November 2022
      Published in PACMHCI Volume 6, Issue CSCW2

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      Author Tags

      1. augmented reality
      2. collaboration
      3. immersive analytics
      4. interpretability
      5. machine learning

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      • (2024)A Systematic Literature Review of User Evaluation in Immersive AnalyticsComputer Graphics Forum10.1111/cgf.1511143:3Online publication date: 10-Jun-2024

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