Collaborative Research: Integrating Language-Based AI Across the High School Curriculum to Create Diverse Pathways to AI-Rich Careers
合作研究:将基于语言的人工智能整合到高中课程中,为人工智能丰富的职业创造多样化的途径
基本信息
- 批准号:2241670
- 负责人:
- 金额:$ 30.08万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-06-01 至 2026-05-31
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Artificial Intelligence (AI) is transforming numerous industries and generating enormous wealth. K-12 is the critical stage for youth to develop knowledge of and interest in AI. This project will leverage the interdisciplinarity of AI to create learning opportunities for secondary students from diverse backgrounds. Focusing on natural language-based AI, this project will develop and research a novel AI Across the Curriculum program that integrates AI concepts and practices into the existing high school curriculum. The project team will develop and test a two-hour introductory module and three five-hour modules for mathematics, English language arts (ELA), and history, as well as a 60-hour professional development program for teachers to develop the competencies required to implement the modules. Teachers in math, ELA, and history will implement the modules in a coordinated fashion to offer learning experiences that are coherent across the different disciplines to their students. During the project, 12 teachers and 900 students will directly benefit from participation in the program. The output of the project will advance national prosperity through AI workforce development by enabling high schools to provide high-quality AI education to all students, especially African Americans, Latinx, and females, who are the underrepresented and underserved groups in the field of AI. The project will be led by an interdisciplinary team of AI developers and educators, STEM and humanities educators, learning scientists and designers, and experts on diversity, equity, and inclusion at the Concord Consortium, Carnegie Mellon University, and North Carolina State University. The team will partner with the San Joaquin County Office of Education in California and the Maryland Center for Computing Education and work closely with two school districts, one in CA and one in MD, that serve student populations underrepresented and underserved in the field of AI. Researchers will address three research questions: 1) How do students’ social and disciplinary identities shape their participation in learning of AI knowledge and AI-rich careers? Guided by the intersectional identity theory, the project will capture eight focal students’ learning processes with repeated interviews, video, audio, and screencast recordings, and computer logs. These data will be analyzed using the personal narratives framework and ethnomethodological and conversation-analytic approaches. 2) What and how are new ideas generated by teachers as they seek to coordinate their efforts to integrate AI across the curriculum? Based on the community of practice theory, the project will capture teachers’ idea generation and transaction processes with Professional Development (PD) recordings, online communications, and interviews. These data will be analyzed using the idea authorship framework. 3) To what extent, for whom, and under what conditions does the AI Across the Curriculum program support students to develop knowledge of and interest in AI-rich careers? The demographic and academic backgrounds of 900 students and 12 teachers will be collected via surveys to determine the impact of this approach. An AI & Machine Learning Core Concepts Questionnaire and an AI-Rich Careers Questionnaire will be administered before and after the curriculum. These data will be analyzed quantitatively to determine to what extent, for whom, and under what conditions the modules are beneficial. Through research publications and professional learning resources, the project will increase the capacity of educators and researchers to advance AI education. All technologies, curriculum modules, assessments, and PD materials will be freely available to the public.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)正在改变众多行业,并创造巨大财富。K-12是青少年培养人工智能知识和兴趣的关键阶段。该项目将利用人工智能的跨学科性,为来自不同背景的中学生创造学习机会。该项目专注于基于自然语言的人工智能,将开发和研究一种新颖的AI Across the Curriculum项目,将人工智能概念和实践整合到现有的高中课程中。项目团队将开发和测试一个两小时的入门模块和三个五小时的数学、英语语言艺术(ELA)和历史模块,以及一个60小时的教师专业发展计划,以培养实施这些模块所需的能力。数学、ELA和历史教师将以协调的方式实施这些模块,为学生提供跨不同学科的连贯学习体验。在项目期间,12名教师和900名学生将直接受益于参与该项目。该项目的成果将通过人工智能劳动力发展促进国家繁荣,使高中能够向所有学生,特别是非洲裔美国人、拉丁裔和女性提供高质量的人工智能教育,这些学生在人工智能领域的代表性和服务不足。该项目将由一个跨学科团队领导,该团队由人工智能开发人员和教育工作者、STEM和人文教育工作者、学习科学家和设计师,以及来自康科德联盟、卡内基梅隆大学和北卡罗来纳州立大学的多样性、公平和包容专家组成。该团队将与加利福尼亚州圣华金县教育办公室和马里兰州计算教育中心合作,并与两个学区密切合作,一个在加利福尼亚州,一个在马里兰州,这两个学区为人工智能领域代表性不足和服务不足的学生群体提供服务。研究人员将解决三个研究问题:1)学生的社会和学科身份如何影响他们参与学习人工智能知识和人工智能丰富的职业?在交叉认同理论的指导下,该项目将通过重复访谈、视频、音频和截屏录音以及计算机日志记录八个重点学生的学习过程。这些数据将使用个人叙事框架、民族方法学和对话分析方法进行分析。2)当教师寻求协调他们的努力,将人工智能整合到整个课程中时,他们会产生哪些新想法,以及如何产生新想法?基于实践社区理论,该项目将通过专业发展(PD)录音、在线交流和访谈来捕捉教师的想法产生和交易过程。这些数据将使用创意作者框架进行分析。3)人工智能跨课程项目在多大程度上,为谁,以及在什么条件下支持学生发展对人工智能丰富的职业的知识和兴趣?将通过调查收集900名学生和12名教师的人口统计和学术背景,以确定该方法的影响。课程前后将分别进行人工智能和机器学习核心概念问卷和人工智能丰富职业问卷调查。将对这些数据进行定量分析,以确定这些模块在多大程度上、对谁有益以及在什么条件下有益。通过研究出版物和专业学习资源,该项目将提高教育工作者和研究人员推进人工智能教育的能力。所有的技术、课程模块、评估和PD材料都将免费提供给公众。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。
项目成果
期刊论文数量(0)
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会议论文数量(0)
专利数量(0)
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Carolyn Rose其他文献
The peer-led Honest, Open, Proud program to decrease the impact of mental illness stigma among German military personnel: randomized controlled trial
- DOI:
10.1007/s00127-025-02960-x - 发表时间:
2025-07-22 - 期刊:
- 影响因子:3.500
- 作者:
Nicolas Rüsch;Christian Helms;Jana Hörger;Burkhard Höhle;Hendryk Bernert;Patric Muschner;Carolyn Rose;Patrick W. Corrigan;Nadine Mulfinger;Peter Zimmermann;Gerd-Dieter Willmund - 通讯作者:
Gerd-Dieter Willmund
Equine-assisted psychotherapy with traumatized couples-improvement of relationship quality and psychological symptoms.
对受创伤的夫妇进行马辅助心理治疗——改善关系质量和心理症状。
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:2.2
- 作者:
G. Willmund;P. Zimmermann;Christina Alliger;Alexander Varn;Christian Fischer;Ilka Parent;Andreas Sobottka;R. Bering;Carolyn Rose;A. Ströhle;Kai Köhler - 通讯作者:
Kai Köhler
Effects of Social Presence and Social Role on Help-Seeking and Learning
社会存在和社会角色对寻求帮助和学习的影响
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
Iris Howley;Takayuki Kanda;Kotaro Hayashi;Carolyn Rose - 通讯作者:
Carolyn Rose
Making a difference: Analytics for quality knowledge-building conversation
有所作为:高质量知识构建对话的分析
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Frank de Jong;Joan van den Ende;Hennie van Heijst;Yoshiaki Matsuzawa;Paul Kirschner;Jianwei Zhang;Mei-Hwa Chen;Feng Chen;Carolyn Rose;Erick Velazquez Godinez;Sylvie Ratte;Bodong Chen;Carol Chan;Jan van Aalst;Christine Yang;Jun Oshima;Cindy - 通讯作者:
Cindy
Carolyn Rose的其他文献
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{{ truncateString('Carolyn Rose', 18)}}的其他基金
Injecting Learning into Work: Enhancing Career Advancement through Transformation of Professional Development in Technical Career Paths
将学习融入工作:通过技术职业道路的专业发展转变来促进职业发展
- 批准号:
1917955 - 财政年份:2019
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
ICLS 2018 Rethinking Learning in the Digital Age in ICLS Doctoral Consortium and Early Career Workshops
ICLS 2018 ICLS 博士联盟和早期职业研讨会重新思考数字时代的学习
- 批准号:
1820520 - 财政年份:2018
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
Collaborative Research: Human-Technology Partnership Supporting Career Path Exploration and Navigation
协作研究:支持职业道路探索和导航的人类技术合作伙伴关系
- 批准号:
1822831 - 财政年份:2018
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
BIGDATA: Collaborative Research: F: Study of a Cyber-Enabled Social Computing Framework for Improving Practice in Online Computing Communities
BIGDATA:协作研究:F:研究网络驱动的社交计算框架,以改进在线计算社区的实践
- 批准号:
1546393 - 财政年份:2016
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
EXP: Collaborative Research: Fostering Ecologies of Online Learners through Technology Augmented Human Facilitation
EXP:协作研究:通过技术增强人类便利性培育在线学习者的生态
- 批准号:
1320064 - 财政年份:2013
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
CSCL 2013: Learning across Levels of Space, Time, and Scale Doctoral Consortium and Early Career Workshops
CSCL 2013:跨空间、时间和规模的学习博士联盟和早期职业研讨会
- 批准号:
1331135 - 财政年份:2013
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
Student Research Workshop in Computational Linguistics at the North American Association for Computational Linguistics and Human Language Technologies 2009 Conference
北美计算语言学和人类语言技术协会 2009 年会议上的计算语言学学生研究研讨会
- 批准号:
0907847 - 财政年份:2009
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
Dynamic Support for Virtual Math Teams
对虚拟数学团队的动态支持
- 批准号:
0835426 - 财政年份:2009
- 资助金额:
$ 30.08万 - 项目类别:
Continuing Grant
Exploring Adaptive Support for Virtual Math Teams
探索虚拟数学团队的自适应支持
- 批准号:
0723580 - 财政年份:2007
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
Calculategy: Exploring the Impact of Tutorial Dialogue Strategy in Shaping Student Behavior in Effective Tutorial Dialogue for Calculus
计算学:探索教程对话策略在有效微积分教程对话中塑造学生行为的影响
- 批准号:
0411483 - 财政年份:2004
- 资助金额:
$ 30.08万 - 项目类别:
Standard Grant
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Research on Quantum Field Theory without a Lagrangian Description
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