Preparing High School Students for Careers in Machine Learning through Mentored Scientific Research

人工智能(AI)在STEM和跨行业迅速变得无处不在，教育领域正在努力解决如何最好地向K12受众教授AI概念。与此同时，人工智能专业人士群体缺乏多样性，将女性和有色人种排除在一个充满活力的经济部门之外，也没有一条向上流动的道路。同样重要的是，缺乏不同的视角可能会使基于有偏见的算法和有偏见的数据集的歧视性做法自动化。十多年来，美国自然历史博物馆的科学研究指导计划是一项STEM劳动力发展计划，为来自服务不足人群的纽约市高中生提供了与科学家密切合作的经验，通过研究机会和指导增加了进入科学领域和职业的机会。在这个项目中，博物馆将与麻省理工学院合作开展一个为期三年的研究项目，通过为高中生创造机会学习和应用机器学习(ML)来解决自然科学中的科学问题，从而在这个成熟的计划中进行创新。该项目通过提高学生对人工智能和ML的技能和知识，促进对人工智能和计算要求高的STEM职业的认识，并培养对这些领域的积极态度，为需要对人工智能和ML有深入了解的工作场所准备一个多样化的学生群体。该项目由学生和教师创新技术体验计划(ITEST)资助，该计划支持的项目是建立对实践、计划要素、背景和过程的理解，有助于提高学生对科学、技术、工程和数学(STEM)以及信息和通信技术(ICT)职业的知识和兴趣。通过该项目，120名学生将参加一个为期四周的暑期学院，专门关注发展技能和对ML应用和职业的理解，其中30名学生将在整个学年与使用ML的科学家一起在研究实验室工作。将使用基于设计的研究方法来开发和完善夏季研究所，该研究所由一个由科学教育工作者、科学家、人工智能专家和项目校友组成的团队提供信息。学生参与者将从主要服务于黑人、西班牙裔/拉丁裔和第一代大学学生的合作伙伴组织中专门招募。一项混合方法的研究将收集关于学生获得ML知识和技能、对人工智能的态度和认知、以及人工智能职业意识和兴趣的数据，使用事前调查工具、人工制品回顾、半结构化观察和访谈。研究成果将通过会议、文章和社交媒体传播。课程和研究工具将公开提供并随时可扩展，利用纽约市科学研究指导联盟，该联盟由24个研究和文化机构组成，每年为500名学生提供服务。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。

Artificial Intelligence (AI) is quickly becoming ubiquitous in STEM and across industries, and the education field is grappling with how best to teach AI concepts to K12 audiences. Simultaneously, the AI professional community suffers from a lack of diversity that excludes women and people of color from a dynamic section of the economy and a path for upward mobility. Equally important, a lack of diverse perspectives can risk automating discriminatory practices based on biased algorithms and biased data sets. For over a decade, the Science Research Mentoring Program, a STEM workforce development initiative of the American Museum of Natural History, has provided New York City high school students from underserved populations with the experience of working closely with scientists, increasing access to science fields and careers through research opportunities and mentorship. In this project, the Museum, in partnership with the Massachusetts Institute of Technology, will undertake a three-year research project to innovate within this well-established program by creating opportunities for high school students to learn and apply machine learning (ML), a subset of AI, to scientific problems in the natural sciences. The project responds to the imperative to prepare a diverse student body for a workplace that will require a sophisticated understanding of AI and ML by advancing students' skills and knowledge of ML, promoting awareness of AI and computationally-demanding STEM careers, and fostering positive dispositions towards these fields. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.Through this project, 120 students will participate in a four-week Summer Institute specifically focused on developing skills and understanding of ML applications and careers, and 30 of these students will subsequently work in research labs over the academic year with scientists who use ML. A design-based research approach will be used to develop and refine the Summer Institute informed by a team consisting of science educators, scientists, AI experts, and program alumni. Student participants will be recruited specifically from partner organizations that primarily serve Black, Hispanic/Latinx, and first-generation college-bound students. A mixed-method research study will gather data on students' acquisition of ML knowledge and skills, attitudes toward and perceptions of AI, and AI career awareness and interest using pre-post survey instruments, artifact review, semi-structured observations, and interviews. Research findings will be disseminated through conferences, articles, and social media. The curriculum and research tools will be publicly available and readily scalable, leveraging the New York City Science Research Mentoring Consortium, a network of 24 research and cultural institutions serving 500 students annually.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.