"Is It My Turn?"

Author:

Benk Michaela1,Weibel Raphael P.1,Feuerriegel Stefan2,Ferrario Andrea1

Affiliation:

1. ETH Zurich, Zurich, Switzerland

2. LMU Munich, Munich, Germany

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.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Reference75 articles.

1. Richard Arias-Hernández , Linda T. Kaastra , Tera M. Green , and Brian D. Fisher . 2011. Pair analytics: Capturing reasoning processes in collaborative visual analytics . 44th Hawaii International Conference on System Sciences ( 2011 ), 1--10. Richard Arias-Hernández, Linda T. Kaastra, Tera M. Green, and Brian D. Fisher. 2011. Pair analytics: Capturing reasoning processes in collaborative visual analytics. 44th Hawaii International Conference on System Sciences (2011), 1--10.

2. Simon Attfield , Gabriella Kazai , Mounia Lalmas , and Benjamin Piwowarski . 2011 . Towards a science of user engagement (Position Paper) . In WSDM Workshop on User Modelling for Web Applications ( Hong Kong, China). 9--12. Simon Attfield, Gabriella Kazai, Mounia Lalmas, and Benjamin Piwowarski. 2011. Towards a science of user engagement (Position Paper). In WSDM Workshop on User Modelling for Web Applications (Hong Kong, China). 9--12.

3. Benjamin Bach , Maxime Cordeil , Ulrich Engelke , Barrett Ens , Marcos Serrano , and Wesley Willett . [n.,d.]. Interaction design & prototyping for immersive analytics . In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk). 1--8. Benjamin Bach, Maxime Cordeil, Ulrich Engelke, Barrett Ens, Marcos Serrano, and Wesley Willett. [n.,d.]. Interaction design & prototyping for immersive analytics. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk). 1--8.

4. Navigating joint projects with dialogue

5. Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3