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、能力强的劳动力队伍。迫切需要研究 K-12 学生学习人工智能概念和流程的能力，以及如何最好地支持他们的人工智能技能和职业兴趣的发展，同时，扩大对人工智能的参与是人工智能劳动力的重要需求。吸引学生的发展。人工智能教育中代表性不足的群体可以帮助确保人工智能技术的设计、开发和利用具有包容性和公平性。该项目的目标是建立有关以下方面的领域先进知识：1）评估中学生的适当测量和工具。概念知识、对人工智能的认识和对人工智能的看法以及职业方向；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变得更感兴趣。人工智能课程在非正式学习环境中的有效性该项目专门针对中学生（11-13 岁），因为中学时期是学生开始探索与其兴趣相关的职业的关键时期。培养多元化的人工智能劳动力，让学生接触人工智能的广泛适用性及其赋予的职业选择非常重要，通过该项目产生的许多人工智能学习活动不依赖于计算机的可用性，从而有助于实现人工智能的发展。扩大人工智能的获取和参与的多种途径为无法持续访问互联网服务的服务不足的学生提供学习体验 该项目由学生和教师创新技术体验 (ITEST) 计划资助，该计划支持有助于加深对实践、计划要素、背景和流程的理解的项目。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。研究人员将重点关注四个研究问题：1）学生对人工智能的看法和态度是什么，以及如何看待这些问题。他们会改变，如果在2) 学生通过干预获得了哪些知识和技能？ 3) 青少年与课程材料、工具和同伴之间的哪些互动促进了学生的概念发展？项目团队将使用基于设计的研究方法来迭代进行专家评审、焦点小组和试点测试测试和完善课程、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，以估计干预措施对年轻人对人工智能的看法和态度、人工智能概念的学习、职业适应性的影响，以及主题分析的案例研究。将用于了解学生与人工智能活动的互动，以促进学习，例如学生与课程材料、学生与工具以及学生与同伴之间的互动，以及支持他们追求的最佳策略；人工智能相关的职业。可交付成果包括：发展人工智能素养（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；以及该项目的成果将建立基于适当的测量和工具、学生的学习过程的知识库。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年轻人进行干预的效果。该研究有可能通过促进人工智能素养的定义、形成人工智能教育领域的发展。为后续 K-12 人工智能教育学习轨迹研究奠定基础，并形成理解，这些理解是开发教育计划的基础，这些计划将培养知识渊博且能够使用人工智能的劳动力。该奖项反映了 NSF 的法定使命，并被认为是值得的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来提供支持。

项目成果

Developing Middle School Students' AI Literacy

培养中学生人工智能素养

• DOI: 10.1145/3408877.3432513
• 发表时间: 2021-03-03
• 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
• 通讯作者: 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: 2021-01
• 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

The Contour to Classification Game

分类游戏的轮廓

• 发表时间: 2021-05
• 期刊: Proceedings of the AAAI Conference on Artificial Intelligence
• 作者: Lee, Irene;Ali, Safinah
• 通讯作者: Ali, Safinah

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

什么是 GAN？：向中学生介绍生成对抗网络

• DOI: 10.1609/aaai.v35i17.17821
• 发表时间: 2021-05-18
• 作者: Safinah Ali;Daniella DiPaola;C. Breazeal
• 通讯作者: C. Breazeal

Exploring Generative Models with Middle School Students

与中学生一起探索生成模型

• DOI: 10.1145/3411764.3445226
• 发表时间: 2021-05-06
• 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
• 通讯作者: C. Breazeal