Developing K-12 Education Guidelines for Artificial Intelligence

制定 K-12 人工智能教育指南

基本信息

批准号：
1846073
负责人：
David Touretzky
金额：
$ 22.57万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-03-15 至 2022-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1846073&HistoricalAwards=false
关键词：
Developing 12 Education Guidelines Artificial

项目摘要

This project will advance efforts of the Innovative Technology Experiences for Students and Teachers (ITEST) program to better understand and promote practices that increase student motivations and capacities to pursue careers in fields of science, technology, engineering, or mathematics (STEM) by developing guidelines for teaching and learning about artificial intelligence (AI) in K-12 school settings. Though AI is a quickly emerging field of research with broad applications in the STEM workforce and industry generally, there are few curriculum standards or educational guidelines for introducing pre-college students to fundamental knowledge and skills relating to the field of AI. This project will address the emerging need for greater guidance in this field by bringing together specialists in AI from academia and industry with specialists representing K-12 education to draft guidelines for teaching and learning about AI across the grade bands of K-12 schools. The draft guidelines will then be reviewed by a larger interest group representing specialists in AI and computer science, as well as representatives of K-12 educators more broadly and the general public. Feedback from this larger interest group will be used to refine the guidelines for broader dissemination. In addition to developing initial guidelines for AI education at the pre-college level, the project will create an online directory of resources that can be used by K-12 teachers to develop instructional experiences in AI for their students.The project team is working in association with the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) to model AI guidelines after CSTA's K-12 Computer Science Standards released in 2017. The project Steering Team includes members of AAAI and CSTA, as well as broad representation of AI scholars nationwide and experienced K-12 teachers across all grade bands. Efforts are being made to ensure that culturally relevant resources are identified and readily available to support implementation of the forthcoming guidelines with all student populations nationwide. The project team includes a Steering Committee that guides the project, and a larger Working Group consisting of experienced K-12 teachers at all grade levels and AI specialists representing academia and industry. An Advisory Group representing AI education nationally and internationally will provide additional guidance to the project. The project will employ mailing lists, a project website, and social media to engage the broader community of interested scholars, educators, researchers, and members of the general 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.

该项目将推进学生和教师创新技术体验 (ITEST) 计划的工作，通过制定指导方针，更好地理解和推广提高学生在科学、技术、工程或数学 (STEM) 领域追求职业的动力和能力的实践用于在 K-12 学校环境中教授和学习人工智能 (AI)。尽管人工智能是一个快速新兴的研究领域，在 STEM 劳动力和行业中得到广泛应用，但很少有课程标准或教育指南可以向大学预科学生介绍与人工智能领域相关的基础知识和技能。该项目将汇集学术界和工业界的人工智能专家与代表 K-12 教育的专家，起草 K-12 学校各年级的人工智能教学指南，以满足该领域日益增长的加强指导的需求。然后，代表人工智能和计算机科学专家以及更广泛的 K-12 教育工作者和公众代表的更大利益团体将审查该指南草案。来自这个更大的利益集团的反馈将用于完善指导方针以进行更广泛的传播。除了为大学预科阶段的人工智能教育制定初步指南外，该项目还将创建一个在线资源目录，K-12 教师可以使用该目录为学生开发人工智能教学经验。该项目团队正在与人工智能促进协会 (AAAI) 和计算机科学教师协会 (CSTA) 合作，根据 CSTA 2017 年发布的 K-12 计算机科学标准制定人工智能指南。该项目指导团队包括 AAAI 和CSTA 以及全国范围内具有广泛代表性的人工智能学者和各个年级的经验丰富的 K-12 教师。我们正在努力确保确定并随时提供与文化相关的资源，以支持全国所有学生群体实施即将出台的指导方针。该项目团队包括一个指导该项目的指导委员会，以及一个更大的工作组，该工作组由经验丰富的各年级 K-12 教师以及代表学术界和工业界的人工智能专家组成。代表国内和国际人工智能教育的咨询小组将为该项目提供额外指导。该项目将采用邮件列表、项目网站和社交媒体来吸引更广泛的感兴趣的学者、教育工作者、研究人员和公众。该奖项反映了 NSF 的法定使命，并通过使用以下评估方法被认为值得支持：基金会的智力价值和更广泛的影响审查标准。