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

这一小型企业创新研究第一阶段项目旨在通过发展教学和教育系统以及评估技术，提高制造业劳动力的技能和知识，并最大限度地利用资源，用于再培训和重新雇用制造业劳动力。具体地说，它旨在解决RAKING中的计算问题，该方法(1)具有为制造业增强电子学习的证明潜力，(2)能够及时优化制造业培训资源，(3)将缩水行业员工的技能集与增长行业员工的技能集相匹配，以减少或防止失业，(4)确定成功的职业道路，以及(5)准确评估复杂的科学和工程技能。拟议的筛选方法旨在大幅减少分析在制造业劳动力中收集的经验数据所需的时间和资源。当将该方法与学习系统相结合时，制造商将能够针对K-16级别的劳动力发展努力。该方法旨在解决大规模的RAING问题，并可应用于多个学科，使用RAING解决需要计算密集型方法的问题(例如，优化制药和药品制造行业销售代表的培训资源；通过互联网支持科学相关学科的协作学习和教学)。

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).