Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions
Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions
复制标题
人工智能（AI）在幼儿教育中的应用：课程设计和未来方向
DOI：
10.1016/j.caeai.2022.100072
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Yuchun Zhong
中科院分区：
文献类型：
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作者：
Jiahong Su;Yuchun Zhong
随着人工智能（AI）带来的社会技术的快速发展，未来对人工智能工作者的需求将增加。培养下一代的人工智能能力并教育他们如何使用和使用人工智能至关重要。以前关于人工智能的研究主要集中在中学和大学教育;然而，关于幼儿教育中人工智能课程的研究很少。针对幼儿园人工智能课程标准化的缺乏，本研究采用由四个关键要素组成的框架，即（1）目的、目标、目的或结果声明，（2）主题、领域或内容，（3）方法或程序，（4）评价和评估，对幼儿园人工智能课程进行了研究。我们建议通过三种能力来实现AI素养：AI知识，AI技能和AI态度。事实证明，使用社交机器人作为学习伙伴和可编程工件有助于帮助幼儿掌握人工智能原理。我们还发现哪种教学方法对学生的学习影响最大。根据调查结果，我们建议未来的人工智能教育采用基于问题的学习方式。
With the rapid technological development of society brought on by Artificial Intelligence (AI), the demand for AI-literate workers will increase in the future. It is critical to develop the next generation's AI competencies and educate them about how to work with and use AI. Previous studies on AI were predominantly focused on secondary and university education; however, research on the Artificial Intelligence curriculum in early childhood education is scarce. Due to the lack of conformity on the standardisation of AI curriculum for early childhood education, this study examines the AI curriculum for kindergarten children using the framework which consists of four key components, including (1) aims, goals, objectives, or declarations of outcome, (2) subject matter, domains, or content, (3) methods or procedure, (4) evaluation and assessment. We recommend that AI literacy be achieved by three competencies: AI Knowledge, AI Skill, and AI Attitude. The employment of a social robot as a learning companion and programmable artifact was proven to be helpful in assisting young children in grasping AI principles. We also discovered which teaching methods had the most greatest influence on students' learning. We recommend problem-based learning for future AI education based on the findings.
黑人之于罪犯就像白人之于警察：检测和消除词嵌入中的多类偏差
DOI：
--
发表时间：
2019
期刊：
2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL
影响因子：
--
作者：
Manzini, Thomas;Lim, Yao Chong;Tsvetkov, Yulia;Black, Alan W
通讯作者：
Black, Alan W