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

从历史上低收入、种族、民族、性别代表和第一代个人在STEM教育项目和数据科学和人工智能（AI）等STEM职业中的代表性不足可以看出，STEM劳动力的多样性仍然是一个挑战。ExLENT-AI实习项目将为数据科学和人工智能新兴技术领域中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，以扩大不同个人了解这些领域并有可能在这些领域工作的机会。北卡罗莱纳州立大学将与达美航空公司、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周的实习项目。实习包括每周的现场研讨会、现实世界的行业指导、工作见习以及与合作伙伴一起完成真实的任务。ExLENT-AI的目标是：1)在体验式学习中利用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循证实习计划；3)加强与适当的利益相关者的伙伴关系，以建立一个综合的协作网络，以最好地支持参与者；4)通过辅导和其他社区建设活动，为同侪建立学习者社区；5)准备参与者获得相关的人工智能能力、知识和技能；6)支持参与者完成求职过程，并将他们安置到人工智能领域的新职业中。ExLENT-AI实习项目将利用十项基于证据的最佳实践，有效地提供体验式学习，并吸引/留住来自历史上服务不足和代表性不足背景的参与者。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)有组织的课程活动的课程作业；4)翻转课堂模式的课堂作业交付；5)团队合作和小组/队列参与话语和知识应用；6)持续参与实习，让个人从事具有真实行业背景的真实任务；7)聘请导师；8)清晰地表达和评估学习目标；9)激励和奖励（如津贴和证书）的使用；通过职业指导和求职支持来提供指导。该项目将广泛促进社会相关成果的实现，包括在人工智能领域发展多样化、具有全球竞争力的新兴技术劳动力。这一项目模式将得到充分发展，并将培养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，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，项目团队将拥有一种机制，继续为不同群体提供访问、机会和授权，以继续维持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，以增加他们对新兴技术领域的兴趣和职业途径。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。

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.