Collaborative Research: Interpersonal Coordination and Coregulation during Collaborative Problem Solving

协作研究:协作解决问题过程中的人际协调和共同调节

基本信息

  • 批准号:
    1660877
  • 负责人:
  • 金额:
    $ 83.63万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-04-15 至 2017-08-31
  • 项目状态:
    已结题

项目摘要

Collaborative problem solving (CPS) is an essential skill in our increasingly connected and globalized world. Yet, there is a paucity of knowledge on how to define, measure, and develop this skill, especially in the context of STEM learning. A team of investigators from Notre Dame University, Florida State University, and Arizona State University will seek to discover how interpersonal interactions arise and influence CPS processes and outcomes in digital STEM learning environments. The research will focus on groups of high school and college students collaborating virtually within a STEM educational game called Physics Playground. The hypothesis is that CPS effectiveness can be improved by providing real-time automated feedback on the ongoing collaboration. The investigators will collect an array of data, ranging from individual physiological measures to learning outcome measures to group communication patterns. Their goal is to improve the design of future CPS learning environments, making them more enjoyable, engaging, and effective. The project is funded by the EHR Core Research (ECR) program, which supports work that advances the fundamental research literature on STEM learning.The research will involve dyads and triads collaborating virtually within a learning environment called Physics Playground, a STEM educational game. Data will be collected in both the lab and classroom, using a diverse sample of high school and college students from three sites across the U.S. The team will integrate data from a range of sources including modeling of small group problem solving and collaborative learning and from the modeling of low-level data from eye tracking, facial feature tracking, psychophysiology, and linguistic/paralinguistic speech analysis. Additionally, the team will study the moderating effects of task constraints and group composition on CPS processes and outcomes. A further goal is to model dynamic CPS processes using nonlinear time series analyses and multimodal deep recurrent neural networks. The computational models will be integrated into the learning environment to test the hypothesis that CPS outcomes can be improved by providing automated feedback on unfolding collaborative processes. Thus, by blending basic experimental research, multisensor-multimodal analysis, computational modeling, and dynamic computerized intervention, the researchers will attempt to make foundational theoretical, methodological, and technological advances.
协作解决问题(CPS)是我们日益联系和全球化的世界中的一项基本技能。然而,关于如何定义,衡量和发展这种技能的知识很少,特别是在STEM学习的背景下。来自圣母大学、佛罗里达州立大学和亚利桑那州立大学的一组调查人员将寻求发现人际互动如何产生并影响数字STEM学习环境中的CPS过程和结果。这项研究将集中在高中和大学生群体中,他们在一个名为“物理游乐场”的STEM教育游戏中进行虚拟合作。假设CPS的有效性可以通过提供实时自动反馈来提高正在进行的协作。研究人员将收集一系列数据,从个人生理指标到学习结果指标,再到群体沟通模式。他们的目标是改善未来CPS学习环境的设计,使其更愉快,更具吸引力和有效性。该项目由EHR核心研究(ECR)计划资助,该计划支持推进STEM学习基础研究文献的工作。该研究将涉及在名为Physics Playground的学习环境中进行虚拟协作的二元组和三元组,这是一款STEM教育游戏。数据将在实验室和教室收集,使用来自美国三个地点的高中生和大学生的不同样本,该团队将整合来自一系列来源的数据,包括小组问题解决和协作学习的建模,以及来自眼动跟踪,面部特征跟踪,心理生理学和语言学/非语言学语音分析的低级别数据的建模。此外,该小组将研究任务限制和小组组成对CPS过程和结果的调节作用。另一个目标是使用非线性时间序列分析和多模态深度递归神经网络对动态CPS过程进行建模。计算模型将被集成到学习环境中,以测试CPS的成果可以通过提供自动反馈展开协作过程来改善这一假设。因此,通过混合基础实验研究,多传感器多模态分析,计算建模和动态计算机化干预,研究人员将试图使基础理论,方法和技术进步。

项目成果

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Sidney D'Mello其他文献

Sidney D'Mello的其他文献

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{{ truncateString('Sidney D'Mello', 18)}}的其他基金

Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-enabled Formative Feedback for Job-Embedded Learning
协作研究 [FW-HTF-RL]:通过人工智能支持的工作嵌入学习形成性反馈增强教师实践的未来
  • 批准号:
    2326170
  • 财政年份:
    2023
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
RAPID: Longitudinal Modeling of Teams and Teamwork during the COVID-19 Crisis
RAPID:COVID-19 危机期间团队和团队合作的纵向建模
  • 批准号:
    2030599
  • 财政年份:
    2020
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
AI Institute: Institute for Student-AI Teaming
人工智能学院:学生人工智能团队学院
  • 批准号:
    2019805
  • 财政年份:
    2020
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Cooperative Agreement
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
  • 财政年份:
    2019
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
AI-DCL: Collaborative Research: EAGER: Understanding and Alleviating Potential Biases in Large Scale Employee Selection Systems: The Case of Automated Video Interviews
AI-DCL:协作研究:EAGER:理解和减轻大规模员工选拔系统中的潜在偏见:自动视频面试的案例
  • 批准号:
    1921087
  • 财政年份:
    2019
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
Modeling Brain and Behavior to Uncover the Eye-Brain-Mind Link during Complex Learning
模拟大脑和行为以揭示复杂学习过程中的眼-脑-心联系
  • 批准号:
    1920510
  • 财政年份:
    2019
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Continuing Grant
EXP: Collaborative Research: Cyber-enabled Teacher Discourse Analytics to Empower Teacher Learning
EXP:协作研究:基于网络的教师话语分析,增强教师学习能力
  • 批准号:
    1735793
  • 财政年份:
    2017
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
Collaborative Research: Interpersonal Coordination and Coregulation during Collaborative Problem Solving
协作研究:协作解决问题过程中的人际协调和共同调节
  • 批准号:
    1745442
  • 财政年份:
    2017
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Continuing Grant
EXP: Attention-Aware Cyberlearning to Detect and Combat Inattentiveness During Learning
EXP:注意力感知网络学习,用于检测和克服学习过程中的注意力不集中
  • 批准号:
    1748739
  • 财政年份:
    2017
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant
WORKSHOP: Doctoral Consortium at the 2016 ACM User Modeling, Adaptation and Personalization Conference (UMAP 2016)
研讨会:2016 年 ACM 用户建模、适应和个性化会议上的博士联盟 (UMAP 2016)
  • 批准号:
    1642486
  • 财政年份:
    2016
  • 资助金额:
    $ 83.63万
  • 项目类别:
    Standard Grant

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Collaborative Research: Interpersonal Pathways to Radicalization & Deradicalization
合作研究:激进化的人际途径
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