
吴丹(1978- ),女,博士,教授,研究方向为信息组织与检索、人机交互 |
孙昕玦(1999- ),女,博士研究生,研究方向为人工智能素养、人机交互 |
收稿日期: 2024-07-05
网络出版日期: 2024-12-13
基金资助
国家自然科学基金重大研究计划培育项目“人机交互视角下数据与知识双驱动的可解释智能决策方法研究”(92370112)
湖北省自然科学基金创新群体项目“以人为本的人工智能创新应用”(2023AFA012)
Exploring Human-centered AI Literacy Education: Interpretation and Insights from UNESCO's AI Competency Framework for Teachers and Students
Received date: 2024-07-05
Online published: 2024-12-13
[目的/意义] 人工智能素养的提升已成为全球教育的重要议题,通过解读UNESCO教师和学生人工智能能力框架中的核心内容和关键能力,可以为教育者、政策制定者等主体提供具体的参考依据,以支持中国人工智能素养教育的落地实施,帮助学生和教师在智能时代中提升人工智能素养。 [方法/过程] 拆解UNESCO能力框架出台的前期相关政策积累以及相关制定背景,分析《学生人工智能能力框架》与《教师人工智能能力框架》的文本内容,以关键原则与框架主体两部分内容为核心对能力框架的内容进行解读。 [结果/结论] 基于能力框架所提供的经验,结合当下人工智能素养教育的实际情况,从主体价值、政策修葺、履践致远和未来应用4个方面为中国人工智能素养教育发展提供启示与建议参考。
关键词: 人工智能素养; 人工智能素养教育; 人工智能能力框架; 以人为本的人工智能观念
吴丹 , 孙昕玦 . 以人为本的人工智能素养教育探究:UNESCO教师和学生人工智能能力框架的解读与启示[J]. 农业图书情报学报, 2024 , 36(8) : 4 -19 . DOI: 10.13998/j.cnki.issn1002-1248.24-0644
[Purpose/Significance] Improving artificial intelligence (AI) literacy has emerged as a critical focus in global education, reflecting the growing significance of AI in today's society. This study aims to explore and interpret the core elements and key competencies articulated in the UNESCO AI Competency Framework for teachers and students, and to provide practical guidance for educators and policymakers, offering insights that can facilitate the systematic integration of AI literacy education. A comprehensive approach to AI education is needed to equip both students and teachers with the skills and knowledge necessary to navigate and thrive in an increasingly intelligent era. The results of this study are intended to support the formulation of effective pedagogical strategies, thereby contributing to the enhancement of AI literacy among educational stakeholders. [Method/Process] The study analyzes the preliminary policy foundations and background that led to the creation of the UNESCO AI Competency Framework. It analyzes the content of both the AI CFS and the AI CFT, focusing on key principles and framework structure to systematically interpret the framework's content. In particular, this study explores the policy context in which these frameworks were developed and examines how global educational goals and technological advances have influenced the articulation of AI competencies. By understanding the development and rationale behind the UNESCO AI Competency Framework, this study aims to provide a comprehensive overview that can support the development of effective AI literacy initiatives. It also highlights the connections between the intentions of the frameworks and the practical competencies required of educators and students, thereby contributing to a deeper understanding of how AI literacy can be meaningfully integrated into educational practice. [ [Results/Conclusions] Based on the experience provided by the competency framework and considering the current state of AI literacy education, this study offers insights and recommendations for developing AI literacy education in China from four perspectives: core values, policy refinement, practical application, and future implementation. Specifically, this study emphasizes that all educational stakeholders should work together to improve AI educational content and methods, and move toward a teacher-student-AI interaction model that empowers teachers, fosters student creativity, and integrates AI as a facilitator of personalized, flexible, and multidirectional learning. In terms of policy refinement, this study advocates for the creation of a supportive policy environment that addresses the unique challenges faced by educators and learners in the Chinese context. For practical application, the study provides actionable recommendations for integrating AI literacy into curricula, emphasizing project-based learning, hands-on experiences, and interdisciplinary approaches that foster a comprehensive understanding of AI concepts. Finally, in terms of future implementation, this study highlights the need for ongoing professional development for educators, such as the establishment of assessment mechanisms to monitor and evaluate the effectiveness of AI literacy programs over time.
表1 人工智能与未来学习项目系列行动Table 1 Series of activities on the artificial intelligence and the futures of learning project |
年份 | 类型 | 中文 | 英文 |
---|---|---|---|
2019 | 国际论坛 | 人工智能与教育国际会议:规划人工智能时代的教育——引领飞跃 | International Conference on Artificial Intelligence and Education: Planning Education in the AI Era: Lead the Leap |
2020 | 国际论坛 | 人工智能与教育的未来国际论坛:培养人工智能时代的能力 | International Forum on AI and the Futures of Education: Developing Competencies for the AI Era |
2021 | 国际论坛 | 人工智能与教育国际论坛:确保人工智能成为教育改革的共同利益 | International Forum on AI and Education: Ensuring AI as a Common Good to Transform Education |
2022 | 国际论坛 | 人工智能与教育国际论坛:引导人工智能赋能教师、变革教学 | International Forum on AI and Education: Steering AI to Empower Teachers and Transform Teaching |
2023 | 圆桌会议 | 教育领域生成式人工智能部长级圆桌会议 | Ministerial Roundtable on Generative AI in Education |
2021 | 知识产出 | 人工智能与教育:政策制定者指南 | AI and Education: Guidance for Policy-Makers |
2022 | 知识产出 | K-12人工智能课程:政府认可的人工智能课程规划 | K-12 AI Curricula: A Mapping of Government-Endorsed AI Curricula |
2023 | 知识产出 | 生成式人工智能在教育和研究中的应用指南 | Guidance for Generative AI in Education and Research |
2024 | 知识产出 | 学生人工智能能力框架 | AI Competency Framework for Students |
2024 | 知识产出 | 教师人工智能能力框架 | AI Competency Framework for Teachers |
表2 UNESCO面向教师的人工智能能力框架Table 2 UNESCO AI competency framework for teachers |
| | ||
---|---|---|---|
| | | |
1.以人为本的人工智能思维方式 | 人类主体性 | 人类责任 | AI社会责任 |
2.人工智能伦理 | 伦理原则 | 安全并负责任地使用 | 共同制定AI伦理规则 |
3.人工智能基础与应用 | 基础AI技术和应用 | AI应用能力 | 与AI共同创作 |
4.人工智能与教学方法 | AI辅助教学 | AI融入教学 | AI推动教学转型 |
5.人工智能支持教师专业发展 | AI支持终身职业发展 | AI增强组织化学习 | AI支持专业转型升级 |
表3 UNESCO面向学生的人工智能能力框架Table 3 UNESCO AI competency framework for students |
能力维度 | 进阶水平 | ||
---|---|---|---|
理解 | 应用 | 创造 | |
以人为本的人工智能思维方式 | 人类主体性 | 人类责任 | AI社会公民 |
人工智能伦理 | 具身伦理 | 安全并负责任地使用 | 伦理设计 |
人工智能技术和应用 | AI基础 | AI应用技能 | 创建AI工具 |
人工智能系统设计 | 问题界定 | 架构设计 | 迭代和反馈循环 |
表4 学生与教师人工智能能力培养指南结构Table 4 Structure of the guide for developing AI competencies in students and teachers |
| | | |
---|---|---|---|
学生能力 | 矩阵中的12项能力 | 教师能力 | 矩阵中的15项能力 |
课程目标(CURRICULAR GOALS,CG) | 人工智能课程、学习计划或培训应该包含的具体内容建议(eg.培养学生在评估人工智能系统对数据、算法和计算资源需求的技能) | 课程目标(CURRICULAR GOALS,CG) | 面向教师的培训活动与课程内容的目标设定参考(教师应该做……) |
教学方法参考(SUGGESTED PEDAGOGICAL METHODS) | 相关组织机构和教师可以考虑并使用的具体教学方法(eg.模拟《人工智能法案》法庭的庭上辩论) | 学习目标(LEARNING OBJECTIVES,LO) | 教师可以使用获得的人工智能能力进行的相关操作(教师可以做……) |
学习环境(LEARNING ENVIRONMENTS) | 可以为学生提供的进行人工智能素养学习的具体场景(eg.视频、在线AI工具、移动应用) | 情境活动(CONTEXTUAL ACTIVITIES) | 教师在不同情境中应展现可适应的态度与行为模式(教师需适应……) |
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