SBIR Phase I: Couragion STEM Career Literacy

This SBIR Phase I project will improve the awareness and perception of careers that require science, technology, engineering, and math (STEM) competencies. Career influencers such as parents, educators, and counselors are often not in the position to inform students of potential options and expose unnecessary bias. If kids understood the opportunities, they could pursue academic pathways to amass skills that better prepare them to enter the workforce. STEM competencies are in high-demand and many high-skill jobs sit vacant for long periods of time. This results in lost productivity and exorbitant recruiting fees to pluck qualified candidates from existing jobs. Our nation could be more successful with access to highly skilled resources, especially in the face of the retiring baby boomer population. Career exploration and readiness focused on helping individuals select rewarding and suitable degrees, training, and careers will increase the likelihood that individuals stay in those careers, exhibit greater creativity, and decrease the number of people who invest in education they never use. As more individuals are inspired to pursue STEM, taxpayers will benefit from increased innovation which in turn will provide tax dollars to invest in such things as healthcare, national security, education, or humanitarian assistance. The project will combine big data, perceived capacity building, continuous STEM programming, and self-reflection to create a commercialized STEM career and self-discovery application and companion data visualization tool. Together, the career application and visualization tool will boost the intent of students to pursue STEM competencies and careers and improve the retention, productivity, and innovation of STEM workers. The project will address the technical hurdles of amassing and managing massive amounts of structured and unstructured data, designing a notification and tracking mechanism to deliver students ongoing programming, developing a smart recommendation engine to drive the best fit STEM careers for students, performing database mining and predictive modeling and creating data visualizations to derive meaningful workforce development insights. The research team will design survey tools and conduct controlled experiments and usability tests to collect student data and business/education entity feedback. The team will analyze experimental, historical, and survey data to validate and refine the data models, scoring algorithms, and application content and functionality. The ultimate goals of the R&D and experiments are to validate that the resulting application, predictive models, scoring algorithms, and data visualizations have the desired result of boosting student outcomes regarding STEM intentions and pursuits.