Collaborative behavior, performance and engagement with visual analytics tasks using mobile devices

Author:

Chen Lei,Liang Hai-NingORCID,Lu Feiyu,Papangelis Konstantinos,Man Ka Lok,Yue Yong

Abstract

Abstract Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visualizations. This research investigates the use of co-located collaborative visualizations in mobile devices, how users working with two different modes of interaction and view (Shared or Non-Shared) and how being placed at various position arrangements (Corner-to-Corner, Face-to-Face, and Side-by-Side) affect their knowledge acquisition, engagement level, and learning efficiency. A user study is conducted with 60 participants divided into 6 groups (2 modes $$\times$$ × 3 positions) using a tool that we developed to support the exploration of 3D visual structures in a collaborative manner. Our results show that the shared control and view version in the Side-by-Side position is the most favorable and can improve task efficiency. In this paper, we present the results and a set of recommendations that are derived from them.

Funder

Xian Jiaotong-Liverpool University

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Cited by 11 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

1. What And How Together: A Taxonomy On 30 Years Of Collaborative Human-Centered XR Tasks;2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR);2023-10-16

2. Side-by-Side vs Face-to-Face: Evaluating Colocated Collaboration via a Transparent Wall-sized Display;Proceedings of the ACM on Human-Computer Interaction;2023-04-14

3. CubeMuseum AR: A Tangible Augmented Reality Interface for Cultural Heritage Learning and Museum Gifting;International Journal of Human–Computer Interaction;2023-02-06

4. Effect of display platforms on spatial knowledge acquisition and engagement: an evaluation with 3D geometry visualizations;Journal of Visualization;2022-10-13

5. Information System User's Collaboration Network Embeddedness and Behavioral Performance;2022 the 5th International Conference on Information Management and Management Science;2022-08-26

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