Convergence Accelerator Phase I (RAISE): Competency Catalyst

融合加速器第一阶段 (RAISE)：能力催化剂

• 批准号: 1937068
• 负责人: Stephen Harmon
• 金额: $ 49.98万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937068&HistoricalAwards=false
• 关键词: Convergence; Accelerator; Phase; RAISE; Competency

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact/potential benefit of this Convergence Accelerator Phase I project is the ability to educate and reskill America's workforce as 5G, Artificial Intelligence (AI), automation, big data, and cloud technology are replacing existing jobs with ones requiring new skills ranging from soft skills to rapidly evolving STEM specialties. The project will leverage infrastructure from national competency-based credentialing, education, training, and workforce development initiatives to develop an AI-based tool that will permit schools, employers, and training programs to deploy competency-based approaches with relative ease and without sacrificing local context and vocabulary. The project team includes educators, data scientists, software developers, workforce specialists, policy makers, and data professionals. The open source / open data tools developed will digitally connect educational programs to job market demands in ways that allow students and educators to adjust their programs to current and future needs in real time and allow local employers to align their needs with national demands and to influence the supply side of the talent pipeline. These tools will be used to improve education, counseling, reskilling, and hiring in a cross-sector multidisciplinary network, starting with dozens of educational institutions and hundreds of employers in the financial/tech market in the state of Georgia. This Convergence Accelerator Phase I project advances the state-of-the-art in applying AI, open data, and analytics to competency-based education and workforce development. It contributes to the fields of computational linguistics, open data, and competency management while facilitating new methods for analyzing and aligning the job market with formal and informal training and education. AI algorithms will be developed for extracting demand-side skills and competencies from job descriptions, documents, and published competency models and for interpreting them in local educational or workforce contexts. Techniques include an array of semantic and text analysis methods; the use of domain-specific ontologies; and combining concept, entity, and relation detection algorithms (e.g., variants on bidirectional Convolutional Neural Networks with Long Short-Term Memory) with word and concept embedding layers to classify skills. All data will be exposed as linked open data with associated concept schema for further contextualization and with data governance that meets employer, educator and user requirements. The project will engage employer/education partnerships to design end-user dashboards that produce competency-based views of local and national job markets, of education and training experiences, and to pilot methods for improving the responsiveness and effectiveness of educational programs to job market needs.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.

NSF融合加速器支持以团队为基础的多学科努力，以应对国家重要性的挑战，并在不久的将来展示可交付成果的潜力。 这个融合加速器第一阶段项目的更广泛的影响/潜在好处是能够教育和重新培训美国的劳动力，因为5G，人工智能（AI），自动化，大数据和云技术正在用需要新技能的工作取代现有的工作，从软技能到快速发展的STEM专业。该项目将利用国家基于能力的资格认证、教育、培训和劳动力发展计划的基础设施，开发一种基于人工智能的工具，使学校、雇主和培训计划能够相对轻松地部署基于能力的方法，而不会牺牲当地的背景和词汇。项目团队包括教育工作者、数据科学家、软件开发人员、劳动力专家、政策制定者和数据专业人员。开发的开源/开放数据工具将以数字方式将教育计划与就业市场需求联系起来，使学生和教育工作者能够根据真实的需求调整他们的计划，并使当地雇主能够将他们的需求与国家需求相结合，并影响人才管道的供应方。这些工具将用于改善跨部门多学科网络中的教育，咨询，再培训和招聘，从格鲁吉亚州金融/科技市场的数十家教育机构和数百家雇主开始。这个融合加速器第一阶段项目推进了将人工智能，开放数据和分析应用于基于能力的教育和劳动力发展的最新技术。它有助于计算语言学，开放数据和能力管理领域，同时促进分析和调整就业市场与正式和非正式培训和教育的新方法。人工智能算法将被开发用于从职位描述、文档和已发布的能力模型中提取需求方技能和能力，并在当地教育或劳动力环境中对其进行解释。技术包括一系列语义和文本分析方法;使用领域特定的本体;以及组合概念、实体和关系检测算法（例如，具有长短期记忆的双向卷积神经网络的变体），具有单词和概念嵌入层来分类技能。所有数据都将作为链接的开放数据公开，并带有相关的概念模式，以供进一步情境化，并带有满足雇主、教育工作者和用户要求的数据治理。该项目将使雇主/教育伙伴关系参与设计最终用户仪表板，以产生关于地方和国家就业市场、教育和培训经验、该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的评估来支持。影响审查标准。