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

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).