SBIR Phase I: Couragion STEM Career Literacy

这个SBIR第一阶段项目将提高对需要科学，技术，工程和数学（STEM）能力的职业的认识和看法。职业影响者，如父母，教育工作者和辅导员往往无法告知学生潜在的选择，并暴露不必要的偏见。如果孩子们了解这些机会，他们可以追求学术途径，积累技能，更好地为他们进入劳动力市场做好准备。STEM能力需求量很大，许多高技能工作长期空缺。这导致了生产力的损失和过高的招聘费用，从现有的工作岗位上挑选合格的候选人。我们的国家可以更成功地获得高技能的资源，特别是在面对退休的婴儿潮人口。职业探索和准备侧重于帮助个人选择有价值的和合适的学位，培训和职业将增加个人留在这些职业的可能性，表现出更大的创造力，并减少投资于他们从未使用过的教育的人数。随着越来越多的人受到启发而追求STEM，纳税人将从创新的增加中受益，这反过来又将提供税收资金来投资于医疗保健、国家安全、教育或人道主义援助等领域。该项目将结合大数据、感知能力建设、持续STEM编程和自我反思，以创建商业化的STEM职业和自我发现应用程序以及配套的数据可视化工具。联合收割机。职业应用程序和可视化工具将共同提高学生追求STEM能力和职业的意图，并提高STEM工作者的保留率，生产力和创新。该项目将解决积累和管理大量结构化和非结构化数据的技术障碍，设计通知和跟踪机制以提供学生正在进行的编程，开发智能推荐引擎以推动最适合学生的STEM职业，执行数据库挖掘和预测建模并创建数据可视化以获得有意义的劳动力发展见解。研究团队将设计调查工具，并进行受控实验和可用性测试，以收集学生数据和商业/教育实体的反馈。该团队将分析实验、历史和调查数据，以验证和完善数据模型、评分算法以及应用程序内容和功能。研发和实验的最终目标是验证所产生的应用程序，预测模型，评分算法和数据可视化具有提高学生在STEM意图和追求方面的成果的预期结果。

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.