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Convergence HTF: Collaborative: Workshop on Convergence Research about Multimodal Human Learning Data during Human Machine Interactions

Convergence HTF: Collaborative: Workshop on Convergence Research about Multimodal Human Learning Data during Human Machine Interactions
融合 HTF:协作:人机交互过程中多模态人类学习数据的融合研究研讨会
批准号:
1854175
负责人:
Roger Azevedo
金额:
$1.25万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2019-08-31

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中文摘要
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英文摘要
Intelligent, interactive, and highly networked machines -- with which people increasingly share their autonomy and agency -- are a growing part of the landscape, particularly in regard to work. As automation today moves from the factory floor to knowledge and service occupations, insight and action are needed to reap the benefits in increased productivity and increased job opportunities, and to mitigate social costs. Such innovations also have significant implications and potential value for lifelong learning, skills assessments, and job training/retraining in an environment in which workforce demands are changing rapidly. The workshop supported by this award will promote the convergence of cognitive psychology, learning sciences, data science, computer science, and engineering disciplines to define key challenges and research imperatives of the nexus of humans, technology, and work with focus on human affect, motivation, metacognition, and cognition during learning and problem solving. Convergence is the deep integration of knowledge, theories, methods, and data from multiple fields to form new and expanded frameworks for addressing scientific and societal challenges and opportunities. This convergence workshop addresses the future of work at the human-technology frontier.The specific focus of this multi-phased workshop approach is to advance fundamental understanding of how to collect and analyze multimodal, multichannel sensor on human affect, motivation, metacognition, and cognition during learning and problem solving, and effectively integrate this data into actionable educational interventions in advanced learning technology environments (e.g., intelligent tutoring systems). The impacts of this research extend to a diverse range of learning environments, and job training and retraining opportunities. A multi-phased workshop approach will be used to explore the implications in multiple job sectors, and the outcomes will be broadly disseminated across geographic and disciplinary boundaries.
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FW-HTF-P: Augmenting Healthcare Professionals’ Training, Expertise Development, and Diagnostic Reasoning with AI-based Immersive Technologies in Telehealth
MetaDash: A Teacher Dashboard Informed by Real-Time Multichannel Self-Regulated Learning Data
Convergence HTF: Collaborative: Workshop on Convergence Research about Multimodal Human Learning Data during Human Machine Interactions
  • 批准号:
    1744351
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2017
  • 负责人:
    Roger Azevedo
  • 依托单位:
MetaDash: A Teacher Dashboard Informed by Real-Time Multichannel Self-Regulated Learning Data
  • 批准号:
    1660878
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $140.05万
  • 财政年份:
    2017
  • 负责人:
    Roger Azevedo
  • 依托单位:
国内基金
海外基金
转HTFα对脊髓继发性损伤和微循环重建的影响
  • 批准号:
    39970755
  • 项目类别:
    面上项目
  • 资助金额:
    13.0万元
  • 批准年份:
    1999
  • 负责人:
    毛伯镛
  • 依托单位: