Research Initiation: Advanced Modeling of Metacognitive Problem Solving and Group Effectiveness in Collaborative Engineering Teams
研究启动:协作工程团队中元认知问题解决和团队有效性的高级建模
基本信息
- 批准号:2208680
- 负责人:
- 金额:$ 19.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-12-01 至 2022-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Most engineering professionals acquire their technical skills through academic curricula. However, in order to succeed in fulfilling the missions of their professions, graduating engineers require a broader set of professional skills. Problem-solving, metacognitive awareness, teamwork, and mindsets supporting sustainability are 21st century skills that help engineers solve complex problems. These professional skills also allow engineers to work effectively in collaborative teams. This project aims to investigate how engineering students develop their professional skills and provide an approach for measuring and quantifying these skills. Undergraduate engineering students will work individually and in groups to solve real-life manufacturing problems while their professional skills are assessed and enhanced. In order to optimize team performance, the conflicts and errors that occur during the problem solving process will be minimized. By acquiring these skills, engineering students will become effective problem solvers and will be prepared to address complex problems in their work environment. Extensive academic and industry dissemination and outreach will be used to bolster the broader impact of project findings.This initiative will develop a new integrated approach to understanding professional skills in the engineering student population and determine if students are attending to the correct elements while solving engineering problems, both in individual and group settings. Physical simulations and virtual reality testbeds will be used to study metacognitive problem-solving and group effectiveness in collaborative teams. The testbeds will help to pinpoint what the students are paying attention to during the learning process as the low-level attention is measured through eye-tracking and application of psychological theories of learning and attention. The project will then develop analytical models to optimize team performance. The analytical models will combine conflict & error algorithms and statistical modeling methods to describe this learning process and identify where improvements can be made. The models will provide valuable insights into the metacognitive decision-making process. By studying eye movements (using eye-tracking), a deeper understanding of metacognition and factors affecting it can be achieved. Because eye movements are indicative of attention, this will allow determination of what information is being attended to, and ultimately processed, by students engaged in the process. By comparing physical simulations with virtual reality environments, this research will provide insights into the applicability of virtual reality technologies in the education domain. Research activities will be integrated into undergraduate courses to support problem-solving skill development. The research will contribute to the economic growth and security of our nation by enhancing the well-being, innovation, and creative problem-solving skills of undergraduate engineering students. This in turn will positively impact our society, academic environment, as well as manufacturing, service and healthcare industries.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.
大多数工程专业人员通过学术课程获得技术技能。然而,为了成功地履行其职业使命,毕业工程师需要更广泛的专业技能。解决问题,元认知意识,团队合作和支持可持续发展的思维方式是21世纪的技能,可以帮助工程师解决复杂的问题。这些专业技能还使工程师能够在协作团队中有效地工作。本项目旨在调查工科学生如何发展他们的专业技能,并提供一种测量和量化这些技能的方法。本科工程专业的学生将单独和小组工作,以解决现实生活中的制造问题,而他们的专业技能进行评估和提高。为了优化团队绩效,解决问题过程中发生的冲突和错误将最小化。通过获得这些技能,工程专业的学生将成为有效的问题解决者,并将准备在他们的工作环境中解决复杂的问题。广泛的学术和行业传播和推广将被用来加强项目研究结果的更广泛的影响。这一举措将开发一种新的综合方法来了解工程专业学生群体的专业技能,并确定学生在解决工程问题时是否注意到了正确的元素,无论是在个人还是小组设置。物理模拟和虚拟现实测试平台将被用来研究元认知问题解决和协作团队的群体效率。测试平台将有助于确定学生在学习过程中关注的内容,因为低水平的注意力是通过眼动跟踪和学习和注意力心理学理论的应用来测量的。然后,该项目将开发分析模型,以优化团队绩效。分析模型将结合联合收割机冲突错误算法和统计建模方法来描述这种学习过程,并确定可以进行改进的地方。这些模型将为元认知决策过程提供有价值的见解。通过研究眼动(使用眼动追踪),可以更深入地了解元认知及其影响因素。由于眼球运动是注意力的指示,这将允许确定参与该过程的学生正在关注并最终处理什么信息。通过比较物理模拟与虚拟现实环境,本研究将提供虚拟现实技术在教育领域的适用性的见解。研究活动将被纳入本科课程,以支持解决问题的技能发展。这项研究将有助于经济增长和我们国家的安全,通过提高福祉,创新和创造性的解决问题的技能本科工程专业学生。这反过来将对我们的社会、学术环境以及制造业、服务业和医疗保健行业产生积极影响。该奖项反映了NSF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。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Sensor-based modeling of problem-solving in virtual reality manufacturing systems
虚拟现实制造系统中基于传感器的问题解决建模
- DOI:10.1016/j.eswa.2022.117220
- 发表时间:2022
- 期刊:
- 影响因子:8.5
- 作者:Zhu, Rui;Aqlan, Faisal;Zhao, Richard;Yang, Hui
- 通讯作者:Yang, Hui
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Faisal Aqlan其他文献
Applying Product Manufacturing Techniques to Teach Data Analytics in Industrial Engineering: A Project Based Learning Experience
应用产品制造技术教授工业工程中的数据分析:基于项目的学习体验
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Faisal Aqlan;Joshua C. Nwokeji - 通讯作者:
Joshua C. Nwokeji
Optimal Cholera Vaccine Allocation Policies in Developing Countries: A Case Study
发展中国家霍乱疫苗的最佳分配政策:案例研究
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
A. G. Qasem;Abdulrahman Shamsan;Faisal Aqlan - 通讯作者:
Faisal Aqlan
A risk-based optimization framework for integrated supply chains using genetic algorithm and artificial neural networks
使用遗传算法和人工神经网络的基于风险的集成供应链优化框架
- DOI:
10.1016/j.ijpe.2019.107569 - 发表时间:
2020 - 期刊:
- 影响因子:12
- 作者:
N. Nezamoddini;A. Gholami;Faisal Aqlan - 通讯作者:
Faisal Aqlan
Job shop planning and scheduling of reconfigurable manufacturing systems
- DOI:
10.1007/s12063-025-00551-2 - 发表时间:
2025-04-30 - 期刊:
- 影响因子:5.300
- 作者:
Jad Imsetif;Nasim Nezamoddini;Faisal Aqlan - 通讯作者:
Faisal Aqlan
Sensor-Based Virtual Reality for Clinical Decision Support in the Assessment of Mental Disorders
基于传感器的虚拟现实用于精神障碍评估中的临床决策支持
- DOI:
10.1109/cog47356.2020.9231896 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Bryant Niederriter;Alice Rong;Faisal Aqlan;Hui Yang - 通讯作者:
Hui Yang
Faisal Aqlan的其他文献
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{{ truncateString('Faisal Aqlan', 18)}}的其他基金
REU Site in Advanced Manufacturing and Supply Chain
REU 先进制造和供应链基地
- 批准号:
2244119 - 财政年份:2023
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
Collaborative Research: An Extended Reality Factory Innovation for Adaptive Problem-solving and Personalized Learning in Manufacturing Engineering
协作研究:制造工程中自适应问题解决和个性化学习的扩展现实工厂创新
- 批准号:
2302833 - 财政年份:2023
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
Integrating Undergraduate Learning in Engineering and Business to Improve Manufacturing Education
将工程和商业本科学习相结合以改善制造教育
- 批准号:
2211066 - 财政年份:2022
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
Collaborative Research: Replication of a Community-Engaged Educational Ecosystem Model in Rust Belt Cities
合作研究:在铁锈地带城市复制社区参与的教育生态系统模式
- 批准号:
2111377 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Continuing Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
- 批准号:
2055384 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
- 批准号:
2204719 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
GOALI: Stochastic Optimization Framework for Energy-Smart Re/Manufacturing Systems
GOALI:能源智能再造/制造系统的随机优化框架
- 批准号:
2038325 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
RET Site in Manufacturing Simulation and Automation
制造仿真和自动化中的 RET 站点
- 批准号:
2204601 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
Collaborative Research: Replication of a Community-Engaged Educational Ecosystem Model in Rust Belt Cities
合作研究:在铁锈地带城市复制社区参与的教育生态系统模式
- 批准号:
2152282 - 财政年份:2021
- 资助金额:
$ 19.99万 - 项目类别:
Continuing Grant
Integrating Undergraduate Learning in Engineering and Business to Improve Manufacturing Education
将工程和商业本科学习相结合以改善制造教育
- 批准号:
2021303 - 财政年份:2020
- 资助金额:
$ 19.99万 - 项目类别:
Standard Grant
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