Research on the Use of Real-Time Tracking and Eye-Tracking Technology for Integrating Metacognition and Augmented Reality into Undergraduate Engineering Laboratories

利用实时跟踪和眼动追踪技术将元认知和增强现实融入本科工程实验室的研究

基本信息

  • 批准号:
    2202108
  • 负责人:
  • 金额:
    $ 85万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-07-01 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

This project aims to innovate Augmented Reality (AR) learning platforms in an undergraduate engineering laboratory. Recently, due to the COVID-19 pandemic, in-person engineering laboratories faced significant challenges in providing hands-on exercise. AR technology might be a solution to the current challenge. Unlike virtual reality, AR does not cover a physical world but mixes 3D virtual objects into physical objects to improve students’ laboratory experiences and spatial awareness. However, students faced difficulties navigating the AR device and have experienced a mismatch between computer-generated 3D images and physical objects while learning in an AR environment. To transform AR learning from a static and isolated experience into a dynamic self-study, this project includes research on using a real-time tracking sensor with a 3D full-body motion capture system to improve AR usability and detect student’s premature termination of learning using metacognitive monitoring feedback and eye-tracking technology. The primary goal of this project is to integrate real-time 3D motion and location tracking systems to meet a series of objectives to gain insight into scientific development and technological innovation in a location-based AR environment. The first objective is to create the next generation of an AR learning platform by integrating state-of-the-art indoor real-time location technology and a 3D full-body motion capture system. The second objective is to detect the early termination of learning by using metacognitive monitoring feedback and eye movement data. The researchers will apply advanced gaze behavior metrics, such as fractal analysis of pupil dilation and eye inter-fixation duration, to identify significant eye gaze behavior representing student’s premature termination of learning. The last objective is to implement the research findings to promote instructional improvement in an engineering laboratory on the impact of receiving metacognitive feedback on learning performance. The current project will address integrated research and education activities to enhance our knowledge of effective undergraduate engineering laboratory education using real-time 3D motion and location tracking capabilities.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.
该项目旨在在本科工程实验室中创新增强现实(AR)学习平台。最近,由于COVID-19疫情,现场工程实验室在提供实践练习方面面临重大挑战。AR技术可能是解决当前挑战的一种方法。与虚拟现实不同,AR不覆盖物理世界,而是将3D虚拟对象混合到物理对象中,以改善学生的实验室体验和空间意识。然而,学生们在导航AR设备时遇到了困难,并且在AR环境中学习时遇到了计算机生成的3D图像与物理对象之间的不匹配。为了将AR学习从静态和孤立的体验转变为动态的自我学习,该项目包括研究使用实时跟踪传感器和3D全身运动捕捉系统来提高AR可用性,并使用元认知监测反馈和眼动跟踪技术来检测学生过早终止学习。 该项目的主要目标是集成实时3D运动和位置跟踪系统,以满足一系列目标,从而在基于位置的AR环境中深入了解科学发展和技术创新。第一个目标是通过整合最先进的室内实时定位技术和3D全身运动捕捉系统来创建下一代AR学习平台。第二个目标是通过使用元认知监测反馈和眼动数据来检测学习的提前终止。研究人员将应用先进的凝视行为指标,如瞳孔扩张和眼睛相互注视持续时间的分形分析,以确定代表学生过早终止学习的重要眼睛凝视行为。最后一个目的是在一个工程实验室中实施研究结果,以促进接受元认知反馈对学习绩效的影响的教学改进。目前的项目将解决综合研究和教育活动,以提高我们的知识,有效的本科工程实验室教育使用实时三维运动和位置跟踪capability.This奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Jung Hyup Kim其他文献

Comparing Update Assessment Results in EMRs Between Inside and Outside the Patient Room in an Intensive Care Unit
比较重症监护室病房内外的电子病历更新评估结果
The effect of metacognitive monitoring feedback on performance in a computer-based training simulation
  • DOI:
    10.1016/j.apergo.2017.10.006
  • 发表时间:
    2018-02-01
  • 期刊:
  • 影响因子:
  • 作者:
    Jung Hyup Kim
  • 通讯作者:
    Jung Hyup Kim
Measuring Nursing Workload in an Intensive Care Unit Using NGOMSL Model
使用 NGOMSL 模型测量重症监护病房的护理工作量
  • DOI:
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sivamanoj Sreeramakavacham;Jung Hyup Kim;Laurel A. Despins
  • 通讯作者:
    Laurel A. Despins
How Metacognitive Monitoring Feedback Influences Workload in a Location-Based Augmented Reality Environment
元认知监控反馈如何影响基于位置的增强现实环境中的工作负载
Assessing the performance of visual identification tasks using time window-based eye inter-fixation duration
使用基于时间窗的眼睛相互注视持续时间评估视觉识别任务的性能
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jung Hyup Kim;Xinran Zhao;Wei Du
  • 通讯作者:
    Wei Du

Jung Hyup Kim的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

相似海外基金

The Lowdown - An AI-based medical device that uniquely combines clinical guidance with real user experience to support improved contraceptive understanding and use.
The Lowdown - 一种基于人工智能的医疗设备,将临床指导与真实用户体验独特地结合起来,以支持提高避孕药具的理解和使用。
  • 批准号:
    10103064
  • 财政年份:
    2024
  • 资助金额:
    $ 85万
  • 项目类别:
    Collaborative R&D
Opioid Use and Acute Suicide Risk: The Real-Time Influence of Trauma Context"
阿片类药物的使用和急性自杀风险:创伤背景的实时影响”
  • 批准号:
    10674342
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
Development of Extraction, Share and Use of Evidences from Real-world Educational Data
从现实世界的教育数据中提取、共享和使用证据的发展
  • 批准号:
    23H00505
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
    Grant-in-Aid for Scientific Research (A)
Quantifying neural variability and learning during real world brain-computer interface use
量化现实世界脑机接口使用过程中的神经变异和学习
  • 批准号:
    10838152
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
Real-time assessment of alcohol and drug use and development of immediate intervention model based on machine learning
基于机器学习的酒精和药物使用实时评估及即时干预模型开发
  • 批准号:
    23H03192
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Optimizing Use of Advanced Diabetes Technology for Self-Management in Adolescents with Type 1 Diabetes: Integration of Real-Time Glucose and Narrative Data
优化使用先进糖尿病技术对 1 型糖尿病青少年进行自我管理:实时血糖和叙述数据的集成
  • 批准号:
    10569293
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
Real time relapse risk scoring for Opioid Use Disorder (OUD) from clinical trial datasets
根据临床试验数据集对阿片类药物使用障碍 (OUD) 进行实时复发风险评分
  • 批准号:
    10585452
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
Real-world data: how can we use it for health technology assessment decision-making?
真实世界数据:我们如何将其用于卫生技术评估决策?
  • 批准号:
    ES/Y007514/1
  • 财政年份:
    2023
  • 资助金额:
    $ 85万
  • 项目类别:
    Fellowship
Cygnes Real: the first real-estate investment platform to use tokenisation, enabling fast, accessible and low cost fractional ownership of property
Cygnes Real:第一个使用代币化的房地产投资平台,实现快速、可访问且低成本的财产部分所有权
  • 批准号:
    10019107
  • 财政年份:
    2022
  • 资助金额:
    $ 85万
  • 项目类别:
    Collaborative R&D
Real-world complexities in opioid use disorder treatment: understanding family comorbidity, high-risk medication use, and costs related to treatment adherence and health outcomes
阿片类药物使用障碍治疗的现实复杂性:了解家庭合并症、高风险药物使用以及与治疗依从性和健康结果相关的成本
  • 批准号:
    10449784
  • 财政年份:
    2022
  • 资助金额:
    $ 85万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了