Everyday AI for Youth: Investigating Middle School Teacher Education, Classroom Implementation, and the Associated Student Learning Outcomes of an Innovative AI Curriculum

青少年的日常人工智能：调查中学教师教育、课堂实施以及创新人工智能课程的相关学生学习成果

• 批准号: 2048746
• 负责人: Irene Lee
• 金额: $ 150万
• 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: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048746&HistoricalAwards=false
• 关键词: Everyday; AI; Youth; Investigating; Middle

Everyday Artificial Intelligence for Youth (EdAI) addresses the need to develop a diverse workforce with the knowledge and skills to work with Artificial Intelligence (AI). The ubiquity of AI technologies in industry and in daily life calls for accessible and age-appropriate AI preparation of all learners. Broadening participation in AI is important in ensuring that AI technologies of the future are founded on principles of inclusivity and equitability. In this project researchers at Massachusetts Institute of Technology and Boston College will recruit and prepare 40 middle school teachers from school districts across Florida, Illinois, and Virginia. Through partnerships with these districts and four youth serving organizations, STEAM Ahead, Boston College’s College Bound, Supercomputing Challenge, and CodeVA, the project will engage over 1200 youths in AI education and foster their interest in AI intensive industries of the future. The majority of the youths are from Black and Latinx families. The project will be built upon the Developing AI Literacy (DAILy) curriculum that interweaves AI concepts, ethics in AI, and AI career awareness. The curriculum has been previously pilot tested among middle schoolers in a summer program. The EdAI professional development (PD) program will take a multi-pronged approach offering an AI Book Club, Practicum, Teacher Network, and Hackathon. Researchers will investigate how this PD model supports teachers to learn, adopt, modify, and teach the DAILy curriculum in a wide range of classroom settings and how the teachers’ implementation of the curriculum impacts students’ learning. 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.In this project, four research questions will be investigated: 1): How can we best prepare a variety of teachers to use an innovative AI curriculum? What supports are necessary for teachers as learners and implementers of the curriculum? 2) What teaching practices are effective in supporting students’ learning of AI and related ethics and career issues? 3) What is the impact of variation in teaching practices and implementation settings on student learning? and 4) How and to what extent do teacher-led implementations of the DAILy curriculum impact student knowledge and interest in AI and AI-related careers? A design-based research approach will be employed to iteratively refine the teacher professional development program and the associated AI learning activities for both in-person and online contexts. The project will also develop and validate measurements and assessments of teachers’ perceptions of and attitudes towards AI, learning of AI concepts, and self-efficacy in teaching AI. The research will utilize a mixed methods design and collect quantitative data using attitudes toward AI surveys and AI knowledge and skills assessments from teachers and students as well as qualitative data including observations of teaching practices and interviews of teachers about their experiences of teaching AI. The findings will inform the AI education field of issues specific to expanding Black and Hispanic/Latinx participation in school-based AI education activities. The deliverables from the project include the EdAI program model, the teacher professional development program, the research findings on teachers’ learning and teaching of AI, and the effectiveness of the curriculum when implemented by middle school teachers in classrooms.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.

青年日常人工智能 (EdAI) 解决了培养具备人工智能 (AI) 知识和技能的多元化劳动力的需求。人工智能技术在工业和日常生活中无处不在，需要为易于理解且适合年龄的人工智能做好准备。扩大对人工智能的参与对于确保未来的人工智能技术建立在包容性和公平性的原则上非常重要。在这个项目中，麻省理工学院和波士顿学院的研究人员将招募和培养 40 名中学教师。通过与佛罗里达州、伊利诺伊州和弗吉尼亚州的学区以及四个青少年服务组织（STEAM Ahead、Boston College's College Bound、Supercomputing Challenge 和 CodeVA）合作，该项目将吸引 1200 多名青少年参与人工智能教育并培养他们的兴趣。大多数年轻人来自黑人和拉丁裔家庭，该项目将建立在人工智能素养（DAIly）课程的基础上，该课程将人工智能概念、人工智能伦理和人工智能交织在一起。该课程之前已在暑期项目中对中学生进行了试点测试，该项目将采取多管齐下的方式，提供人工智能图书俱乐部、实习、教师网络和黑客马拉松研究。该 PD 模型如何支持教师在广泛的课堂环境中学习、采用、修改和教授 DAIly 课程，以及教师实施课程如何影响学生的学习。该项目由学生创新技术体验资助。和老师(ITEST) 计划，支持旨在加深对实践、计划要素、背景和流程的理解的项目，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) 职业的知识和兴趣在这个项目中，将研究四个研究问题：1）：我们如何才能最好地为各种教师使用创新的人工智能课程做好准备？作为课程的学习者和实施者，教师需要哪些支持？有效支持学生学习人工智能及相关道德和职业问题？ 3) 教学实践和实施环境的变化对学生学习有什么影响？ 4) 教师主导的 DAIly 课程实施如何以及在多大程度上影响学生对人工智能和人工智能的知识和兴趣？该项目还将采用基于设计的研究方法来迭代完善教师专业发展计划以及相关的面对面和在线环境的人工智能学习活动。对人工智能的态度、对人工智能的学习该研究将采用混合方法设计和收集数据，利用教师和学生对定量人工智能调查和人工智能知识和评估技能的态度以及包括对教学实践的观察和访谈的定性数据。该项目的成果包括 EdAI 项目模型、教师等。专业发展计划、教师学与教的研究成果该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Online vs in-person professional learning communities: A qualitative comparison of teacher learning experiences

在线与面对面的专业学习社区：教师学习体验的定性比较

• 发表时间: 2023
• 期刊: Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023
• 作者: Moore, K. S.;Zhang, H.;Gupta, P.;Kuhlken, Z.;Li, H.;Lee, I.
• 通讯作者: Lee, I.

Ethics in Artificial Intelligence Education: Preparing Students to Become Responsible Consumers and Developers of AI.

人工智能教育中的道德：让学生成为负责任的人工智能消费者和开发者。

• 发表时间: 2023
• 期刊: Proceedings of the 2023 ASEE Annual Conference & Exposition.
• 作者: Zhang, H.;Lee, I.;Moore, K.;Ahmad Shah, S.
• 通讯作者: Ahmad Shah, S.

AI Book Club: An Innovative Professional Development Model for AI Education

AI读书俱乐部：人工智能教育创新的专业发展模式

• DOI: 10.1145/3478431.3499318
• 发表时间: 2022
• 期刊: SIGCSE Technical Symposium 2022
• 作者: Lee, Irene;Zhang, Helen;Moore, Kate;Zhou, Xiaofei;Perret, Beatriz;Cheng, Yihong;Zheng, Ruiying;Pu, Grace
• 通讯作者: Pu, Grace

Preparing teachers to teach artificial intelligence in classrooms: An exploratory study.

为教师在课堂上教授人工智能做好准备：一项探索性研究。

• 发表时间: 2023
• 期刊: Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023
• 作者: Zhang, H.;Lee, I.;Moore, K. S.
• 通讯作者: Moore, K. S.

Online vs in-person professional learning communities: A qualitative comparison of teacher learning experiences.

在线与面对面的专业学习社区：教师学习经验的定性比较。

• 发表时间: 2023
• 期刊: Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023
• 作者: Moore, K. S.;Zhang, H.;Gupta, P.;Kuhlken, Z.;Li, H.;Lee, I.
• 通讯作者: Lee, I.