Pivots: Enabling Access for Historically Underserved and Underrepresented Groups to Experiential Learning and Credentials in Artificial Intelligence

支点：让历史上服务不足和代表性不足的群体能够获得人工智能领域的体验式学习和证书

• 批准号: 2321633
• 负责人: Carla Johnson
• 金额: $ 100万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321633&HistoricalAwards=false
• 关键词: Pivots; Enabling; Access; Historically; Underserved

Diversity in the STEM workforce remains a challenge as evidenced by the historical underrepresentation of low-income, racial, ethnic, gender representation, and first-generation individuals in STEM education programs and in STEM careers such at data science and artificial intelligence (AI). The ExLENT-AI Externship project will provide experiential learning opportunities to people from historically underserved and underrepresented groups in the emerging technology fields of data science and AI to broaden access for diverse individuals to learn about and potentially work in careers in these areas. North Carolina State University will partner with Delta Air Lines, Lexmark, Charity Navigator, Randstad, and other industry organizations to collaborate on the design and implementation of the 40-week externship program. The externship is a combination of live, weekly workshop sessions and real-world, industry mentoring, job shadowing, and working on authentic tasks with partners. The objectives of ExLENT-AI are to: 1) leverage evidence-based best practices in experiential learning to attract diverse learners to emerging technology careers; 2) recruit individuals with from historically underserved and underrepresented groups to participate in the ExLENT-AI evidence-based externship program; 3) strengthen partnerships with appropriate stakeholders to develop an integrated, collaborative network to best support participants; 4) establish a community of learners for the cohorts through mentorship and other community-building activities; 5) prepare participants to gain relevant artificial intelligence competencies, knowledge, and skills; and 6) support participants through the job search process and placement into their new careers in artificial intelligence. The ExLENT-AI Externship project will leverage the use of ten evidence-based best-practices found to be effective in delivery of experiential learning and attracting/retaining participants from historically underserved and underrepresented backgrounds. These ten key practices include: 1) establishment of a STEM ecosystem, 2) use of the Collective Impact Model; 3) coursework that has structured curricular activities; 4) inverted classroom models for coursework delivery; 5) teamwork and group/cohort engagement in discourse and application of knowledge; 6) sustained involvement in externships where individuals are engaged in authentic tasks with real-world industry context; 7) engagement of mentors; 8) clear articulation and assessment of learning objectives; 9) use of incentives and rewards (e.g., stipends and certificates); and 10) guidance through career coaching and job search support. This project will contribute broadly to the achievement of societally relevant outcomes including the development of a diverse, globally competitive emerging technology workforce in artificial intelligence. This program model will be fully developed and will prepare 33 new individuals historically underserved and underrepresented in emerging technology careers, including women, first-generation college students, veterans, persons with disabilities, and racial/ethnic minorities. Additionally, through strong partnerships with industry, the project team will have a mechanism to continue to provide access, opportunity, and empowerment to diverse groups to continue a sustained talent pipeline and direct connections to careers. This project fits well within the NSF ExLENT program, supported by the NSF TIP and EDU Directorates, as it seeks to support experiential learning opportunities for individuals from diverse professional and educational backgrounds to increase their interest in, and their access to, career pathways in emerging technology fields.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.

STEM劳动力的多样性仍然是一个挑战，低收入，种族，民族，性别代表性和第一代个人在STEM教育计划和数据科学和人工智能（AI）等STEM职业中的历史代表性不足就是明证。ExLENT-AI Externship项目将为来自数据科学和人工智能新兴技术领域的历史上服务不足和代表性不足的群体的人们提供体验式学习机会，以扩大不同个人学习这些领域的机会。北卡罗来纳州州立大学将与达美航空、利盟、慈善领航员、任仕达和其他行业组织合作，共同设计和实施为期40周的实习计划。实习是现场，每周研讨会和现实世界的结合，行业指导，工作阴影，并与合作伙伴一起完成真实的任务。ExLENT-AI的目标是：1）利用体验式学习中基于证据的最佳实践，吸引不同的学习者从事新兴技术职业; 2）招募来自历史上服务不足和代表性不足的群体的个人参加ExLENT-AI基于证据的实习计划; 3）加强与适当利益相关者的合作伙伴关系，以开发一个综合的协作网络，为参与者提供最佳支持; 4）通过导师制和其他社区建设活动为学员建立学习者社区; 5）帮助学员获得相关的人工智能能力、知识和技能; 6）通过求职过程和人工智能新职业的安置为学员提供支持。ExLENT-AI Externship项目将利用十种基于证据的最佳实践，这些实践在提供体验式学习和吸引/留住来自历史上服务不足和代表性不足背景的参与者方面是有效的。这十个关键实践包括：1）建立STEM生态系统，2）使用集体影响模型; 3）具有结构化课程活动的课程作业; 4）用于课程作业交付的倒置课堂模型; 5）团队合作和小组/队列参与知识的话语和应用; 6）持续参与外部活动，其中个人参与真实的任务，具有真实的行业背景; 7）导师的参与; 8）明确表达和评估学习目标; 9）使用激励和奖励（例如，津贴和证书）; 10）通过职业辅导和求职支持提供指导。该项目将为实现与社会相关的成果做出广泛贡献，包括在人工智能领域发展多元化、具有全球竞争力的新兴技术劳动力。该计划模型将得到充分开发，并将为33名在新兴技术职业中历史上服务不足和代表性不足的新个人做好准备，包括女性，第一代大学生，退伍军人，残疾人和种族/少数民族。此外，通过与行业建立强有力的合作伙伴关系，项目团队将有一个机制，继续为不同群体提供访问，机会和授权，以继续持续的人才管道和与职业的直接联系。该项目非常适合NSF ExLENT计划，由NSF TIP和EDU董事会支持，因为它旨在为来自不同专业和教育背景的个人提供体验式学习机会，以增加他们对以下内容的兴趣和访问：该奖项反映了NSF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。