CAREER: A collaboration coach with effective intervention strategies to optimize group performance.

许多员工质疑工作场所会议的有效性，尽管它们对协作决策很重要。有时与会者难以集中注意力，或者一个人主导了整个谈话；在这两种情况下，生产率都在下降。召开会议和促进所有人有效参与的能力受到主观和不可量化因素的影响，如关系动态、性别偏见和接受批评的意愿。这项研究将探索是否有可能通过使用非个人实体——计算机——来进行小组会议，并提供现场和会后反馈，使参与者能够保持主题，平等参与，并密切倾听彼此，同时生成有关过程的分析。本研究将开发的框架可以作为提高会议效率和有效性的工具，同时为患有阿斯伯格综合症或社交恐惧症的个体提供设计干预措施的可能性，这些个体很难在群体环境中坚持自己的观点。在会议期间提供实时反馈需要实时识别和分析感知到的数据，但是实时反馈只有在其解释不会给参与者带来认知负荷时才有价值。这项研究将有助于设计有效而不分散注意力的实时反馈。项目的研究结果也将适用于在线学习的背景，在这种情况下，计算机促进者可以平等地吸引每个学生。除了标准化考试成绩外，计算机还可以对学生提问、有效参与和保持积极态度的能力进行客观分析。认可学生的努力可能会对他们的分数产生积极影响。项目发现可以帮助虚拟助手（如Alexa或谷歌Home）通过适当和尊重的干预策略调解对话，此外，它们还可以深入了解性别和种族多样性在提高团队绩效方面所起的作用。人类行为的相互作用（例如，面部表情、语调、语言、打断、参与率和轮流）被认为是微妙的，有时是矛盾的，而且经常令人困惑。这些行为可能是高度个人特定的，如果要自动利用这些行为进行有效的会议调解，则可能需要具有实时性能的临时建模。虽然原始感测数字在开发算法基准时很有用，但它们对用户的价值很少。这项研究将使用以人为中心的计算原理来可视化、解释和揭示原始行为数据的见解。特别是，以下研究问题将在在线视频会议的背景下使用以人为中心的方法来解决：1)存在哪些可能的调解策略，以避免对人类参与者造成破坏和不尊重；2)哪种最有帮助：现场反馈，会后反馈，两者结合，还是根本没有反馈；3)我们能否实施自动化流程以提高会议效率？4)反馈是否能以可衡量的方式改善团队绩效？该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Many employees question the effectiveness of workplace meetings, despite their importance to collaborative decision-making. Sometimes attendees have trouble staying focused, or else one individual dominates the conversation; in both cases, productivity is down. The ability to conduct a meeting and foster effective participation by all is influenced by subjective and unquantifiable factors such as relationship dynamics, gender biases, and willingness to accept criticism. This research will explore whether it may be possible to avoid these complications by using an impersonal entity - the computer - to conduct group meetings and provide both live and post-meeting feedback that enables participants to stay on topic, take part equally, and listen closely to one another, all while generating analytics about the process. The framework that will be developed in this research may serve as a tool for improving meeting efficiency and effectiveness, while opening up the possibility of designing interventions for individuals with Asperger syndrome or social phobia who find it difficult to assert themselves in group settings. Providing live feedback during a meeting will require real-time recognition and analysis of the sensed data, but live feedback is only valuable when its interpretation does not impose a cognitive overload on the participants. This research will make contributions on designing live feedback that is effective yet not distractive. Project findings will also be applicable in the context of online learning, where a computer facilitator could engage every student equally. In addition to standardized test scores, computers can also create objective analytics on, for example, students' ability to ask questions, participate effectively and maintain a positive attitude. Recognizing students for their effort may positively impact their scores. Project findings may help virtual assistants (such as Alexa or Google Home) mediate conversations with appropriate and respectful intervention strategies, and in addition they may yield insights into the role played by gender and racial diversity in improving team performance. The interplay of human behaviors (e.g., facial expression, tone of voice, language, interruptions, participation rates, and turn-taking) is considered subtle, sometimes contradictory, and often confusing. These behaviors can be highly individual-specific, and may require temporal modeling with real-time performance if they are to be harnessed automatically for effective meeting mediation. While the raw sensed numbers are useful when developing algorithm benchmarks, they add very little value for users. This research will use principles of human centric computing to visualize, interpret and reveal insights from raw behavioral data. In particular, the following research questions will be addressed using human-centric approaches in the context of online video conferencing: 1) What possible mediation strategies exist that avoid being disruptive and disrespectful to human participants; 2) Which is most helpful: live feedback, post-meeting feedback, a combination of both, or no feedback at all; 3) Can we implement an automated process to facilitate meeting productivity; and 4) Does feedback improve group performance in any measurable way?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.