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

这个小企业创新研究（SBIR）第一阶段项目的更广泛/商业影响是为边缘化的学生群体提供更多的教育途径和公平的学习、专业发展和职业发展机会。该项目建议开发和实施数字人类元素，以满足这些受影响个人的需求。该项目不是这样的组织，而是为那些来自边缘化社区的人创造公平机会的途径，让他们参与一些最具创新性的学习方式，同时为一些最有前途的STEM职业学习。这个项目的智力价值在于将大数据和机器学习用于个性和技能测量。人工智能算法将与游戏机制并列，以方便使用，因为熟悉其他现有的用户界面。该界面具有复杂的动态人格分析引擎。该研究将提供标准和方法，评估现有的交换格式，提高神经网络的准确性指标，并提供初始的数字人体原型。该技术将创建一个数据湖，包含职业、技能、证书要求、社交媒体资料、简历、面试记录和其他在线活动，由用户共享，用于建立个性化的、人工智能（AI）支持的职业发展概况。数据湖中的信息将被整理，以促进个性化职业发展战略的发展。Delta Lake模型将用于连续流数据，提高数据质量，以驱动数字人和用户的个性化需求。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。

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.