EAGER: Developing AI Literacy Interventions to Teach Fundamental Concepts in AI

EAGER：开发人工智能素养干预措施来教授人工智能的基本概念

• 批准号: 2022502
• 负责人: Irene Lee
• 金额: $ 30万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2022502&HistoricalAwards=false
• 关键词: EAGER; Developing; AI; Literacy; Interventions

Artificial Intelligence (AI) has emerged as a foundational technology that impacts on every sector of the economy and every corner of society. AI’s rapid expansion across fields and industries and its dramatic impact on the economy and national security necessitate developing a workforce knowledgeable and capable of working with AI. There is an urgent need to research K-12 students’ capacity to learn AI concepts and processes and how best to support their development of AI skills and career interests. Meanwhile, broadening participation in AI is an important need in AI workforce development. Engaging students from underrepresented groups in AI education can help ensure that the design, development, and utilization of AI technologies are inclusive and equitable. The objective of this project is to build field-advancing knowledge about 1) appropriate measurements and instruments to assess middle school students’ concept knowledge, awareness of AI and perceptions about AI, and career orientation; and 2) whether and how students are able to learn key AI concepts and become more interested in AI and related careers. This knowledge will be generated through investigating the learning outcomes and efficacy of an AI curriculum in informal learning contexts with students from diverse backgrounds, including Hispanic/Latinx and African American learners. The project specifically addresses middle school students (ages 11-13) because the middle school years are a critical time for students to begin exploring careers related to their interests. In order to develop a diverse AI workforce, it is important to expose students to the wide range of applicability of AI and the career options it confers. Many of the AI learning activities produced through the project are not dependent on the availability of computers, contributing to multiple pathways for broadening access to and engagement in AI learning experiences for underserved students who do not have consistent access to Internet services . 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.Researchers will focus on four research questions: 1) What are students’ perceptions and attitudes towards AI and how do they change, if at all, as a result of the interventions? 2) What knowledge and skills do students develop through the interventions? 3) What kinds of interactions between youth and curriculum materials, tools, and peers facilitate students’ conceptual development? and 4) What connections do students make, if any, between the skills they learn and application of those skills in various STEM and computer science careers and fields? The project team will use a design based research approach in conducting expert reviews, focus groups, and a pilot test to iteratively test and refine the curriculum, measures, and assessments. The team will then conduct an efficacy study to collect and analyze data to generate estimates of the impact of the intervention on youths’ perceptions of and attitudes toward AI, learning of concepts in AI, and career adaptability. Additionally, video and interaction analyses, cognitive interviews, and case studies with thematic analyses will be used to gain an understanding of student engagement with the AI activities; student interactions that facilitated learning such as interactions between students and curriculum materials, students and tools, and students and their peers; and the best strategies to support them to pursue AI related careers. The project’s deliverables include: the Developing AI LIteracy (DAILy) curriculum; the Attitudes Toward AI, AI Concept Inventory and AI Career Futures surveys; and the research findings. The project’s outcomes will build the knowledge base on appropriate measurements and instruments, students’ learning processes, how and to what extent students can learn AI concepts in middle school, and the efficacy of the intervention with an audience of underrepresented youth. The research has potential to advance the field of AI education by contributing to the definition of AI literacy, forming the basis for subsequent research on learning trajectories in K-12 AI education, and generating understandings that are foundational to developing education programs that will prepare a workforce knowledgeable and capable of working with AI.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.

人工智能（AI）已成为影响经济各个部门和社会各个角落的基础技术。人工智能在各个领域和行业的快速扩张及其对经济和国家安全的巨大影响，需要培养一支知识渊博、能够与人工智能合作的劳动力队伍。迫切需要研究K-12学生学习AI概念和过程的能力，以及如何最好地支持他们发展AI技能和职业兴趣。同时，扩大对人工智能的参与是人工智能劳动力发展的重要需求。让来自代表性不足群体的学生参与人工智能教育可以帮助确保人工智能技术的设计、开发和利用是包容和公平的。该项目的目标是建立关于以下方面的领域推进知识：1）适当的测量和工具，以评估中学生的概念知识，人工智能的意识和对人工智能的看法，以及职业导向; 2）学生是否以及如何能够学习关键的人工智能概念，并对人工智能和相关职业更感兴趣。这些知识将通过调查非正式学习环境中人工智能课程的学习成果和有效性与来自不同背景的学生，包括西班牙裔/拉丁裔和非洲裔美国学生产生。该项目专门针对中学生（11-13岁），因为中学阶段是学生开始探索与他们兴趣相关的职业的关键时期。为了培养多样化的人工智能劳动力，让学生了解人工智能的广泛适用性及其带来的职业选择是很重要的。通过该项目产生的许多人工智能学习活动并不依赖于计算机的可用性，这有助于为那些无法持续访问互联网服务的服务不足的学生提供多种途径，以扩大对人工智能学习体验的访问和参与。该项目由学生和教师创新技术体验（ITEST）计划资助，该计划支持建立对实践，计划元素，背景和过程的理解的项目，有助于增加学生对科学，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。研究人员将专注于四个研究问题：1）学生对人工智能的看法和态度是什么，如果干预的结果是改变的话，他们是如何改变的？2)学生通过干预发展了哪些知识和技能？3)青少年与课程材料、工具和同龄人之间的什么样的互动促进了学生的概念发展？以及4）学生在他们学习的技能与在各种STEM和计算机科学职业和领域中应用这些技能之间建立了什么联系？项目团队将使用基于设计的研究方法进行专家评审，焦点小组和试点测试，以反复测试和完善课程，措施和评估。然后，该团队将进行有效性研究，收集和分析数据，以估计干预对青少年对人工智能的看法和态度，人工智能概念的学习和职业适应性的影响。此外，视频和互动分析，认知访谈和案例研究与主题分析将被用来了解学生参与人工智能活动;促进学习的学生互动，如学生和课程材料，学生和工具，学生和他们的同龄人之间的互动;以及支持他们追求人工智能相关职业的最佳策略。该项目的可交付成果包括：开发人工智能文学（DAILy）课程;对人工智能的态度，人工智能概念清单和人工智能职业未来调查;以及研究结果。该项目的成果将建立知识基础，包括适当的测量和工具、学生的学习过程、学生如何以及在多大程度上可以在中学学习人工智能概念，以及对代表性不足的青少年进行干预的有效性。这项研究有可能通过对人工智能素养的定义做出贡献来推动人工智能教育领域的发展，为随后对K-12人工智能教育中学习轨迹的研究奠定基础，并产生理解，这是发展教育计划的基础，这些计划将培养一支知识渊博、有能力与人工智能合作的劳动力。该奖项反映了NSF的法定使命，并被认为值得通过以下方式获得支持：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。

项目成果

Developing Middle School Students' AI Literacy

• DOI: 10.1145/3408877.3432513
• 发表时间: 2021-03
• 期刊: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education
• 作者: Irene A. Lee;Safinah Ali;Helen Zhang;Daniella DiPaola;C. Breazeal

Adapting K-12 AI Learning for Online Instruction. 2nd International Workshop on Education in Artificial Intelligence K-12

将 K-12 人工智能学习应用于在线教学。

• 发表时间: 2021
• 期刊: Proceedings of German Journal of Artificial Intelligence 2/2021
• 作者: Ali, Safinah;DiPaola, Daniella;Lee, Irene;Jackson, David;Kiel, Jeff;Beal, Kerri;Zhang, Helen;Cheng, Yihong;Breazeal, Cynthia
• 通讯作者: Breazeal, Cynthia

What are GANs?: Introducing Generative Adversarial Networks to Middle School Students

• DOI: 10.1609/aaai.v35i17.17821
• 发表时间: 2021-05
• 作者: Safinah Ali;Daniella DiPaola;C. Breazeal

Exploring Generative Models with Middle School Students

• DOI: 10.1145/3411764.3445226
• 发表时间: 2021-05
• 期刊: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
• 作者: Safinah Ali;Daniella DiPaola;Irene A. Lee;Jenna Hong;C. Breazeal

The Contour to Classification Game

分类游戏的轮廓

• 发表时间: 2021
• 期刊: Proceedings of the AAAI Conference on Artificial Intelligence
• 作者: Lee, Irene;Ali, Safinah
• 通讯作者: Ali, Safinah