SBIR Phase I: eLearning --- Training and Enabling the Manufacturing Workforce: Computer Aided Decision Tools for Training and Assessment Optimization

SBIR 第一阶段：电子学习 --- 培训和支持制造劳动力：用于培训和评估优化的计算机辅助决策工具

• 批准号: 0637288
• 负责人: Chris Chiu
• 金额: --
• 依托单位: ACCU MEASUREMENT AND TESTING, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0637288&HistoricalAwards=false
• 关键词: SBIR; Phase; eLearning; Training; Enabling

This Small Business Innovation Research Phase I project sets out to improve the skills and knowledge of the manufacturing workforce and to maximize resources for retraining and reemploying the manufacturing workforce by means of the development of instructional and educational systems and assessment technology. Specifically, it sets out to solve a computational problem in raking, a methodology that (1) has a demonstrated potential to empower eLearning for the manufacturing industry, (2) can enable timely optimization of manufacturing training resources, (3) match skill sets of employees in shrinking industries to those in growing industries for purposes of unemployment reduction or prevention, (4) identify successful career paths, and (5) accurately assess complex science and engineering skills.. The proposed raking methodology aims to substantially reduce time and resources needed for analyzing empirical data collected in the manufacturing workforce. When integrating the methodology with learning systems, manufacturers will be able to target workforce development efforts at the K-16 level. The proposed methodology aims to solve large-scale raking problems and can be applied in multiple disciplines which use raking to solve problems needing computational intensive methodology (e.g., optimize training resources for sales representatives in the pharmaceutical and medicine manufacturing industry; empower collaborative learning and instruction of science related subjects via the Internet).

这项小型企业创新研究阶段I项目着手提高制造劳动力的技能和知识，并通过开发教学和教育系统和评估技术来最大程度地利用资源来培训和重新雇用制造业劳动力。具体而言，它着手解决耙式中的计算问题，这种方法（1）具有赋予制造行业的电子学习能力的潜力，（2）可以及时优化制造业培训资源，（3）员工在缩小行业中的员工匹配技能，以使成长中的行业缩小行业的行业，以降低工程学的降低或确定成功（4）的职业，并且（4）的职业和（4），（4），（4）（4）（4），（4），（4），（4），以及（4），以及（4），以及（4）的（4），（4）的行业，（4），（4）的行业（4）​​，并且（4）的行业（4）​​，以及（4）的行业（4）​​，并且（4）的行业（4）​​，以及（4）的行业。拟议的耙式方法旨在大大减少分析制造劳动力中收集的经验数据所需的时间和资源。当将方法与学习系统集成时，制造商将能够针对K-16级别的劳动力发展工作。拟议的方法旨在解决大规模的射击问题，并可以应用于多个学科中，这些学科使用耙子来解决需要计算密集型方法论的问题（例如，优化药物和医学制造业中销售代表的培训资源； Emppower; Emppower; Empower the Internet empower toppower与科学与科学与科学相关的学科的授权）。