Dynamics of Visual Attention in Multiparty Collaborative Problem Solving using Multidimensional Recurrence Quantification Analysis
Dynamics of Visual Attention in Multiparty Collaborative Problem Solving using Multidimensional Recurrence Quantification Analysis
复制标题
使用多维递归量化分析多方协作解决问题中的视觉注意动态
DOI：
10.1145/3290605.3300572
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
D'Mello, Sidney K.
中科院分区：
文献类型：
--
作者：
Vrzakova, Hana;Amon, Mary Jean;Stewart, Angela E.;D'Mello, Sidney K.
多方协作解决问题--这是21世纪劳动力的一个日益重要的背景--在远程尝试时会导致社会和行为信号的退化，导致结果不太理想。我们研究团队在协作解决问题任务中视觉注意力的多维模式，着眼于利用洞察力来改善协作界面。57名新手(组成19个三合会)参与了一项具有挑战性的编程任务(代码我的世界一小时)，他们使用带有屏幕共享的视频会议软件。为了发现个体级别的凝视-用户界面耦合(团队成员的注意力与用户界面变化的协调性)和团队级别凝视-用户界面规律性(团队集体注意力在用户界面变化的背景下的动态变化)的模式，我们分别应用了跨维度和多维重复量化分析。个体的眼睛凝视与正在进行的屏幕活动显著相关，而团队的凝视规律表现出显著的模式，这表明团队的注意力具有重复模式。这些测量预测了专家编码的构建共享知识以及协商和协调(但不维持团队功能)的协作过程，并与任务分数相关(r=.425)。他们还预测了个人对团队绩效和协作过程的主观看法，但不预测个人的学习或团队的任务分数。我们讨论了我们的发现对智能协作界面设计的影响。
Multiparty collaborative problem solving - an increasingly important context in the 21st century workforce - suffers from a degradation of social and behavioral signals when attempted remotely, resulting in suboptimal outcomes. We investigate teams' multidimensional patterns of visual attention during a collaborative problem-solving task with an eye for leveraging insights to improve collaborative interfaces. Fifty-seven novices (forming 19 triads) engaged in a challenging programming task (Minecraft Hour of Code) using videoconferencing software with screen sharing. To discover patterns of individual-level gaze-UI coupling(coordination of a teammate's attention with respect to changes in the user interface) and team-level gaze-UI regularity (dynamics of teams' collective attention in context with changes in the user interface), we applied cross- and multidimensional recurrence quantification analyses, respectively. Individuals' eye gaze was significantly coupled with the ongoing screen activity whereas teams displayed significant patterns of gaze regularity, suggesting repetitive patterns in teams' attention. These measures predicted expert-coded collaborative processes of constructing shared knowledge and negotiation and coordination (but not maintaining team function) and correlated with task score (r = .425). They also predicted individually assessed subjective perceptions of team performance and the collaboration process, but not individual's learning or team's task scores. We discuss implications of our findings for the design of intelligent collaborative interfaces.
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