SBIR Phase I: A platform to connect underserved and underrepresented communities to science, technology, engineering and mathemetics (STEM) careers

SBIR 第一阶段：一个将服务不足和代表性不足的社区与科学、技术、工程和数学 (STEM) 职业联系起来的平台

• 批准号: 2232689
• 负责人: Gina Coburn
• 金额: $ 27.5万
• 依托单位: NERRATIVE TECHNOLOGY INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2232689&HistoricalAwards=false
• 关键词: SBIR; Phase; platform; connect; underserved

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in providing more access to educational pathways, and equitable opportunities for learning, professional development, and career growth to marginalized student communities. The project proposes the development and implementation of a digital human element to meet the needs of these impacted individuals. The project is not such organizations, but also to create pathways to equitable opportunities for those coming from marginalized communities to participate in some of the most innovative learning modalities, while studying for some of the most promising STEM careers. The intellectual merit of this project lies in the use of big data and machine learning in personality and skills measurement. The artificial intelligence algorithms will be juxtaposed onto game mechanics to facilitate ease of use due to the familiarity with other existing user interfaces. The interface has a complex and dynamic personality profiling engine. The research will deliver standards and methodologies, evaluate existing exchange formats, improve accuracy metrics for neural networks, and deliver an initial digital human prototype. The technology will create a Data Lake containing professions, skills, certificate requirements, social media profiles, resumes, recorded interviews, and other online activities that are shared by the users for establishing personalized, artificial intelligence (AI)-supported career growth profiles. Information in the Data Lake will be curated to facilitate the development of personalized career development strategies. A Delta Lake model will be used to continuously stream data with improved data quality to drive the personalization requirements of both the digital human and the user.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.

小型企业创新研究(SBIR)第一阶段项目的更广泛/商业影响是为边缘化的学生社区提供更多的教育途径，以及平等的学习、专业发展和职业成长机会。该项目建议开发和实施数字人元素，以满足这些受影响个人的需要。该项目不是针对这些组织，而是为那些来自边缘社区的人创造平等机会，让他们参加一些最具创新性的学习方式，同时学习一些最有前途的STEM职业。这个项目的智力价值在于使用大数据和机器学习来衡量个性和技能。由于对其他现有用户界面的熟悉，人工智能算法将并列在游戏机制上，以便于使用。该界面有一个复杂而动态的个性剖析引擎。这项研究将提供标准和方法，评估现有的交换格式，改进神经网络的精度指标，并提供初步的数字人体原型。这项技术将创建一个数据湖，其中包含职业、技能、证书要求、社交媒体档案、简历、录制的面试和其他在线活动，供用户共享，以建立个性化的、人工智能(AI)支持的职业成长档案。将对数据湖中的信息进行整理，以促进制定个性化的职业发展战略。Delta Lake模型将用于以改进的数据质量持续传输数据，以推动数字人类和用户的个性化需求。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。