I-Corps: Assessing Capabilities of Adaptive Learning for Predicting and Optimizing Local School-to-Workforce Talent Management Pipelines

I-Corps：评估自适应学习预测和优化当地学校到劳动力人才管理渠道的能力

• 批准号: 1954696
• 负责人: Gayathri Narasimham
• 金额: $ 5万
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1954696&HistoricalAwards=false
• 关键词: Corps; Assessing; Capabilities; Adaptive; Learning

The broader impact/commercial potential of this I-Corps project is to better prepare local economies for the uncertain future of work. Research has shown that when young adults have early exposure to the labor market through jobs and internships they are more likely to succeed in school, attain stable employment and earn higher wages as adults. However, youth employment in the U.S. has dropped significantly over the past four decades, and there are currently over 13.5 million young adults ages 18-24 who are out of school and out of work. Being disconnected at this critical age has major risks for chronic unemployment and lifetime lower earnings and costs local economies and tax dollars an estimated $940 k per youth. The proposed technology will strengthen school to workforce pipelines across U.S. cities by integrating project-based learning and adaptive learning algorithms to deliver, track, incentivize and personalize local talent development. Our intervention has the potential to better streamline and retain young adults through local workforce pipelines and thus have positive returns for schools, employers and local economies. This I-Corps project involves the integration of adaptive learning and game based-mechanics to personalize and adapt a project-based learning 21st century workforce readiness intervention designed for young adults ranging from ages 14-24. In early pilot tests in classrooms and experience work-based learning settings, this intervention has shown promising potential to improve participants’ demonstrable skills and competencies and support of self-directed goals. Based on past research, the integration of adaptive learning algorithms and game-based mechanics is hypothesized to maximize in-person training hours for group dialogue and collective troubleshooting, provide personalized monitoring and recommendations for talent development, and promote improved satisfaction, retention and performance of most at-risk and underperforming learners. Over time, the data collected should have strong predictive capabilities to better inform and strengthen the talent pipeline.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

I-Corps项目的更广泛影响/商业潜力是使当地经济更好地为不确定的未来工作做好准备。研究表明，当年轻人通过工作和实习早期接触劳动力市场时，他们更有可能在学校取得成功，获得稳定的工作，并在成年后获得更高的工资。然而，在过去的40年里，美国的青年就业率大幅下降，目前有超过1350万18-24岁的年轻人既没有上学，也没有工作。在这个关键年龄断网会造成长期失业和终身低收入的重大风险，并给当地经济和税收造成损失，估计每个年轻人的损失为94万美元。拟议中的技术将通过整合基于项目的学习和自适应学习算法来提供、跟踪、激励和个性化当地人才发展，从而加强美国城市从学校到劳动力的管道。我们的干预有可能通过当地劳动力管道更好地简化和留住年轻人，从而为学校、雇主和当地经济带来积极回报。这个I-Corps项目将适应性学习和基于游戏的机制整合在一起，为14-24岁的年轻人设计了一个基于项目的学习21世纪劳动力准备干预。在教室的早期试点测试和以工作为基础的体验学习环境中，这一干预措施显示出改善参与者可展示的技能和能力以及支持自我导向目标的良好潜力。基于过去的研究，我们假设将自适应学习算法和基于游戏的机制相结合，以最大限度地提高小组对话和集体故障排除的现场培训时间，为人才发展提供个性化监控和建议，并提高大多数风险和表现不佳的学习者的满意度、保留率和绩效。随着时间的推移，收集的数据应该具有强大的预测能力，以更好地为人才管道提供信息和加强。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。