Developing and Analyzing a Modular, Online Mechatronics Curriculum with Hands-on Laboratories to Prepare the Skilled Manufacturing Workforce
Developing and Analyzing a Modular, Online Mechatronics Curriculum with Hands-on Laboratories to Prepare the Skilled Manufacturing Workforce
批准号:
1935708
负责人:
Karl Haapala
金额:
$184.42万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2024-12-31
中文摘要
该项目将有助于全国对受过良好教育的生产工程工程师和技术人员的需求。它将通过支持机电一体化在线课程的设计、开发和评估来做到这一点。该项目团队包括俄勒冈州立大学和克拉卡马斯社区学院的教育工作者,以及与行业和其他组织的合作伙伴关系。总体目标是开发一套包括面对面实验的在线课程模块。每个模块将培养特定机电一体化概念的能力。面对面的动手实验室将采用“盒子里的实验室”的方法,让学生可以选择在俄勒冈州立大学或在离自己所在地较近的社区大学进行实验室。课程模块将被组织成四个分组,可以堆叠在机电一体化课程中。这些分组将使两年制和四年制院校的学生以及在职专业人员能够获得机电一体化证书。该项目将调查模块课程和远程实验室如何影响学生的学习和成功。这项分析的结果将有助于了解提供高质量在线教育的最佳实践,以满足学生的专业目标以及机电和制造业的需求。该项目将帮助全国更多的学生接受机电一体化教育。该项目的总体目标是改善对生产工程至关重要的关键领域的现有和未来工程师和技术人员的准备。该项目将追求五个目标:1)确定和确认机电一体化的基本内容领域和学习目标;2)开发一个模块化在线计划,用于当前机电一体化领域的认证或再认证;3)扩大社区学院和大学生的专业认证以外的教育机会,并提供开放教育;4)研究和评估学生通过模块化课程和远程实验室的学习成果;以及5)为后续用户分发课程材料、性能分析方法和匿名数据。课程模块将进行组织和垂直整合,以提供机电一体化职业发展道路证书或机电一体化工程证书。将收集和分析有关学生与课程组件交互的数据,包括站点导航工作流、通过预测性分析实现的学生进度以及学习者参与度。感兴趣的具体变量包括:完成时间和完成率;总体成绩;学习者满意度;以及雇主满意度。将探索人口统计变量,以确定拟议的混合在线方法最适合谁。学生在远程实验中的表现将与传统实验中的学生进行比较,以确定远程选项是否为同等可行的替代方案。这项研究将为不同的学习者如何在模块化的课程中取得成功提供更多的见解。项目结果将通过教师培训、会议报告、同行评议出版物和为期一天的研讨会提供,以将该项目扩展到俄勒冈州以外的地区。该项目由NSF的EHR核心研究:生产工程教育和研究(ECR:PEER)计划资助,该计划旨在改善未来和现有生产工程专业人员的教育。它还旨在研究这些项目采用的创新教育战略的有效性。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project will contribute to the national need for well-educated engineers and technicians in production engineering. It will do so by supporting the design, development, and evaluation of online courses in mechatronics. The project team includes educators at Oregon State University and Clackamas Community College, as well as partnerships with industry and other organizations. The overall goal is to develop a set of online course modules that include in-person labs. Each module will build competence in a specific mechatronics concept. The in-person, hands-on labs will use a "lab-in-a-box" approach, which will give students the option of conducting labs at Oregon State University or at community colleges close to their own location. The course modules will be organized into four groupings that can be stacked within a mechatronics curriculum. These groupings will enable students at two-year and four-year institutions, as well as working professionals, to obtain certifications in mechatronics. The project will investigate how modular courses and remote labs influence student learning and success. The results of this analysis will contribute to understanding best practices for delivering a high-quality online education that meets the professional goals of students, as well as the needs of mechatronics and manufacturing industries. The project will help make mechatronics education more accessible to a wider range of students across the country.The overall goal of this project is to improve the preparation of current and prospective engineers and technicians in key fields that are important for production engineering. The project will pursue five objectives: 1) Identify and confirm essential content areas and learning objectives in mechatronics; 2) Develop a modular online program for certification or re-certification in current areas of mechatronics; 3) Expand educational opportunities beyond professional certification for community college and university students, and for open-education delivery; 4) Research and evaluate student learning outcomes resulting from the modular course delivery and remote laboratories; and 5) Distribute course materials, performance analysis methods, and anonymized data for subsequent users. The course modules will be structured and vertically integrated to offer a Mechatronics Career Pathway Certificate or a Mechatronics Engineering Certificate. Data about students' interaction with course components will be collected and analyzed, and will include site navigation workflows, student progress via predictive analytics, and learner engagement. Specific variables of interest will include: time and rate of completion; overall achievement; learner satisfaction; and employer satisfaction. Demographic variables will be explored to identify for whom the proposed hybrid online approach works best. Student performance in remote labs will be compared to that of students in traditional labs, to determine whether the remote options are equivalent and viable alternatives. The research will provide greater insights into how different learners achieve success within the modularized curriculum. Project results will be made available through faculty training, conference presentations, peer-reviewed publications, and a one-day workshop to scale the program beyond the state of Oregon. This project is funded by NSF's EHR Core Research: Production Engineering Education and Research (ECR: PEER) program, which seeks to improve the education of future and current professionals in production engineering. It also aims to study the effectiveness of the innovative educational strategies adopted by these projects.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.
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会议论文
Participant Support: 2023 Co-located International Advanced Manufacturing Conference (NAMRC/MSEC/LEM&P); New Brunswick, New Jersey; 12-16 June 2023
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批准号:2234055
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项目类别:Standard Grant
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资助金额:$4.96万
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财政年份:2022
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负责人:Karl Haapala
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依托单位:
NIST-ASTM-NSF-ASME Workshop on Challenges in Representing Manufacturing Processes for Systemic Sustainability Assessments - Student Travel; College Station, Texas; June 18-22, 2018
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批准号:1831141
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项目类别:Standard Grant
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资助金额:$3.91万
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财政年份:2018
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负责人:Karl Haapala
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依托单位:
Collaborative Research: Constructionism in Learning: Sustainable Life Cycle Engineering (CooL:SLiCE)
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批准号:1432774
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项目类别:Standard Grant
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资助金额:$24.57万
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财政年份:2014
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负责人:Karl Haapala
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依托单位:
CI-TEAM Demonstration Project: Collaborative Research - A Sustainable Product Development Collaboratory
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批准号:1041423
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项目类别:Standard Grant
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资助金额:$6.49万
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财政年份:2010
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负责人:Karl Haapala
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依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data
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批准号:60601030
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项目类别:青年科学基金项目
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资助金额:17.0万元
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批准年份:2006
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负责人:Axel Mosig
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依托单位: