Collaborative Research: FW-HTF-RM: Intelligent Facilitation for Teams of the Future via Longitudinal Sensing in Context

合作研究：FW-HTF-RM：通过上下文中的纵向感知为未来团队提供智能协助

• 批准号: 1928612
• 负责人: Sidney D'Mello
• 金额: $ 33.81万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928612&HistoricalAwards=false
• 关键词: Collaborative; Research; FW; HTF; RM

In the information workplace of the future, teamwork will become increasingly critical and teamwork itself will be redefined. Teams will need to develop better skills in handling complex problems as routine work will be increasingly delegated to artificial intelligence (AI) technologies such as personal digital assistants. Teams will need to rapidly adapt to fluid membership and changing work structures with the growing gig economy, and as new workers enter the workforce bringing new cultural practices. Individuals will need to be able to perform effectively in heterogeneous teams as the workforce becomes more diverse and as globalization increases. The future of teamwork will require integration of technological advances to facilitate team performance, yet we are largely relying on tools and techniques from the 20th century for team facilitation. This project will develop and validate an intelligent (AI-based) team facilitator for information work utilizing sensing and dynamic intervention to promote better team coordination, higher performance, and ultimately lower worker burnout. The intelligent team facilitator will serve as a blueprint for a broad set of domains beyond information work, including medical care teams, control room settings, crisis management, and manufacturing, where team skills will be needed for interacting with AI, robots, and new technologies. The facilitator can also be used for training underrepresented groups to succeed in the workforce, a national priority. The present project utilizes sensor technologies for tracking team behavior in information workplaces in addition to traditional methods of studying teams using observations and self- reports. Longitudinal precision tracking of teams in situ with a suite of sensors can provide objective measures, can scale, and will enable a deep understanding of how teams respond to changing contexts, how teams form and integrate new members, and how they develop rhythms of teamwork. This project examines team diversity broadly, considering demographics, attitudes, circadian rhythms and personal responsibilities. The first aim of this project is to develop models of critical team states and processes (e.g., team cohesion, team coordination, team mood/affect), based on unobtrusive, continual, longitudinal sensing of physiology, behavior, and communication in a real-world context along with measures of individual differences to understand factors that lead to team effectiveness. This project will use risk mitigation strategies to safeguard privacy and security of data. The second aim of this project is to use those insights to develop an intelligent (AI-based) team facilitator. Performance of teams who use the intelligent team facilitator will be experimentally compared against matched controls in a longitudinal in situ study. The results will contribute to a new understanding on how 21st century teams can manage complexity, how team heterogeneity can lead to team effectiveness, and will identify successful strategies for team adaptability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在未来的信息工作场所中，团队合作将变得越来越重要，团队合作本身将得到重新定义。团队将需要发展更好的技能来处理复杂问题，因为常规工作将越来越多地委派给人工智能（AI）技术，例如个人数字助理。 随着零工经济的增长，团队将需要迅速适应流动的成员资格和不断变化的工作结构，并且随着新工人进入劳动力，带来了新的文化实践。 随着劳动力变得更加多样化，随着全球化的增加，个人将需要能够在异质团队中有效地表现。团队合作的未来将需要整合技术进步以促进团队绩效，但是我们在很大程度上依靠20世纪的工具和技术来进行团队促进。该项目将开发并验证一个智能（基于AI）的团队主持人，利用感应和动态干预措施来促进更好的团队协调，更高的表现，并最终降低工人的倦怠。智能团队的主持人将作为信息工作以外的广泛领域的蓝图，包括医疗团队，控制室环境，危机管理和制造业，与AI，机器人和新技术进行互动需要团队技能。主持人还可以用于培训代表性不足的团体，以在国家优先事项中取得成功。本项目还利用传感器技术来跟踪信息工作场所中的团队行为，除了使用观察和自我报告研究团队的传统方法。纵向精确跟踪与一套传感器的原位团队可以提供客观的措施，可以扩展，并能够深入了解团队如何应对不断变化的环境，团队如何形成和整合新成员以及如何发展团队合作的节奏。该项目考虑了人口统计学，态度，昼夜节律和个人职责，广泛研究了团队的多样性。该项目的第一个目的是基于对现实环境中的生理学，行为和沟通的不引人注目的，持续的，纵向感知的措施，以及了解导致团队有效性的因素，基于对生理学，行为和沟通的持续性，持续的，行为和沟通的模型（例如团队的凝聚力，团队协调，团队情绪/情感），基于对团队差异的措施。该项目将使用降低风险策略来保护数据的隐私和安全性。该项目的第二个目的是利用这些见解来开发智能（基于AI）的团队主持人。在一项纵向现场研究中，将在实验上将使用智能团队主持人的团队的表现与匹配的对照进行比较。结果将有助于对21世纪团队如何管理复杂性，团队异质性如何提高团队有效性的新理解，并将确定成功的团队适应性策略。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的审查标准来通过评估来通过评估来支持的。

项目成果

Toward Robust Stress Prediction in the Age of Wearables: Modeling Perceived Stress in a Longitudinal Study With Information Workers

• DOI: 10.1109/taffc.2022.3188006
• 发表时间: 2022-10-01
• 期刊: IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
• 影响因子: 11.2
• 作者: Booth, Brandon M.;Vrzakova, Hana;D'Mello, Sidney K.
• 通讯作者: D'Mello, Sidney K.

Emotional regularity: associations with personality, psychological health, and occupational outcomes

情绪规律：与人格、心理健康和职业结果的关联

• DOI: 10.1080/02699931.2021.1968797
• 发表时间: 2021
• 期刊: Cognition and Emotion
• 影响因子: 2.6
• 作者: D’Mello, Sidney K.;Gruber, June
• 通讯作者: Gruber, June

Designing an Interactive Visualization System for Monitoring Participant Compliance in a Large-Scale, Longitudinal Study

设计交互式可视化系统，用于监测大规模纵向研究中参与者的依从性

• DOI: 10.1145/3411763.3443436
• 发表时间: 2021
• 期刊: CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
• 作者: Talkad Sukumar, Poorna;Breideband, Thomas;Martinez, Gonzalo J.;Caruso, Megan;Rose, Sierra;Steputis, Cooper;D'Mello, Sidney;Mark, Gloria;Striegel, Aaron
• 通讯作者: Striegel, Aaron

Recurrence Quantification Analysis of Eye Gaze Dynamics During Team Collaboration

团队协作过程中眼睛注视动态的循环量化分析

• DOI: 10.1145/3576050.3576113
• 发表时间: 2023
• 期刊: ACM
• 作者: Moulder, Robert;Booth, Brandon;Abitino, Angelina;D'Mello, Sidney
• 通讯作者: D'Mello, Sidney

'Location, Location, Location': An Exploration of Different Workplace Contexts in Remote Teamwork during the COVID-19 Pandemic

“位置，位置，位置”：对 COVID-19 大流行期间远程团队合作中不同工作场所环境的探索

• DOI: 10.1145/3579504
• 发表时间: 2023
• 期刊: Proceedings of the ACM on Human-Computer Interaction: Computer Supported Collaborative Work
• 作者: Breideband, Thomas;Moulder, Robert Glenn;Martinez, Gonzalo J.;Caruso, Megan;Mark, Gloria;Striegel, Aaron D.;D'Mello, Sidney
• 通讯作者: D'Mello, Sidney