RAPID: Exploring an AI Literacies Framework for Young Children: A Delphi Study

人工智能(AI)正在迅速改变社会，教育工作者和研究人员越来越清楚地看到，K-12学生必须为AI驱动的未来做好准备。需要研究的一个重要领域是5至8岁儿童的幼儿教育。人工智能对幼儿的潜在影响怎么强调都不为过：对语言发展、认知技能、感官和社会情感发展有着深远的影响，这些都是幼儿教育的整体目标。先前的研究表明，让幼儿接触人工智能是可行的，并可以对他们的人工智能知识和技能产生积极影响。这些研究往往只侧重于儿童如何学习人工智能，而没有充分考虑幼儿教育的整体目标和做法。迫切需要解决欧洲经委会人工智能教育中的这些问题，并确保早期人工智能学习是适当、有效和公平的。这项建议是为了回应尊敬的同事信函(DCL)：在正式和非正式环境中迅速加速K-12教育中的人工智能研究(NSF 23-097)，并由学生和教师创新技术体验(ITEST)计划资助的，该计划支持一些项目，这些项目建立对实践、计划要素、背景和过程的理解，有助于提高学生对科学、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。该项目将通过使用Delphi方法开发一个跨学科框架，用于欧洲经委会人工智能学习，这是一种汇聚专家对新兴主题的意见的迭代过程。将招募一个由来自人工智能、儿童发展和早期教育以及儿童与计算机交互三个领域的不同和包容的30名专家组成的小组。这些专家将探索人工智能的认知、情境和批判性框架的三个基本问题。(1)什么：最适合幼儿的AI学习目标和内容是什么？(2)谁：AI学习必须考虑哪些发展优势/约束和公平关切？以及(3)如何：我们如何有效和公平地引入人工智能？研究过程包括对研究团队准备和综合的材料进行三轮迭代的讨论、调查和审查。通过认知、情境和批判性框架以及从多学科的角度阐明欧洲经委会人工智能扫盲的基本概念和原则，由此产生的框架将有助于增进我们对幼儿如何发展与人工智能有关的知识和技能的理解，并为这一领域的未来努力提供信息，特别关注与边缘化和服务不足的社区具有特殊需要和文化相关性的个人。该项目的成果也有可能指导为幼儿制定适合年龄的课程和教学方法，并为评估和评估幼儿的人工智能素养提供基础。该奖项反映了NSF的法定使命，并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，被认为值得支持。

Artificial intelligence (AI) is rapidly transforming society, and it is becoming increasingly clear to educators and researchers that K-12 students must be prepared for an AI-driven future. One crucial area that requires research is early childhood education (ECE) for children aged 5 to 8 years old. The potential impact of AI on early childhood cannot be overstated: there are far-reaching implications for language development, cognitive skills, sensory perception, and social-emotional development, which are the holistic goals of ECE. Prior research suggests that exposing young children to AI is feasible and can have positive effects on their AI knowledge and skills. These studies often focus exclusively on how children learn with and about AI, without fully considering the holistic goals and practices of ECE. There is an urgent need to address such issues in ECE AI education and ensure early AI learning is appropriate, effective, and equitable. This proposal was received in response to the Dear Colleague Letter (DCL): Rapidly Accelerating Research on Artificial Intelligence in K-12 Education in Formal and Informal Settings (NSF 23-097) and 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.This project will develop an interdisciplinary framework for ECE AI learning by using the Delphi methodology, an iterative process of converging expert opinions on emerging topics. A panel of 30 experts of diverse and inclusive representation from three fields: AI, Child Development and Early Education, and Child-Computer Interaction will be recruited. These experts will explore three fundamental questions across cognitive, situated, and critical framing of AI. (1) What: What are the most appropriate AI learning goals and content for young children? (2) Who: What developmental advantages/constraints and equity concerns must be considered for AI learning? and (3) How: How can we introduce AI effectively and equitably? The research process involves three iterative rounds of discussion, survey, and review of materials prepared and synthesized by the research team. By articulating the underlying concepts and principles of AI literacies in ECE through cognitive, situated, and critical framing and from multidisciplinary perspectives, the resulting framework will help advance our understanding of how young children can develop knowledge and skills related to AI and inform future endeavors in this area, with particular attention to individuals with special needs and cultural relevance to marginalized and underserved communities. The outcome of the project also has the potential to guide the development of age-appropriate curricula and pedagogy for young children as well as provide a basis for assessing and evaluating AI literacies in young children.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.