International Prospects and Trends of Artificial Intelligence Education: A Content Analysis of Top-level AI Curriculum across Countries

Yujun Zhou, Zehui Zhan, Lu Liu, Jiayi Wan, Simai Liu, Xuanxuan Zou
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Abstract

This study intends to investigate the present situation of AI curriculum offered for grades K-12. We screened 11 representative countries and areas from six continents and assessed the content of their top K-12 AI courses in terms of teaching content and teaching implementation in order to comprehend the current state of K-12 AI courses in diverse nations. Provide some ideas and suggestions for the development of AI courses for students in grades K-12. (1) Countries may choose AI applications, AI influences in various aspects, AI ethics, machine learning, data, classification, reasoning, Identify, and other content to establish independent AI teaching content standards; or choose programming as the core teaching content/starting point; or integrate programming, data, AI, and other content related to improving students' computational thinking into computer/science/technology courses. (2) Project-based learning is still the primary way of instruction, along with a range of other approaches. There are four categories of available instructional resources, and there is an abundance of them. Most countries emphasize the evaluation of students' abilities and the results achieved in the learning process.
人工智能教育的国际前景与趋势:各国顶级人工智能课程内容分析
本研究旨在调查K-12年级人工智能课程的现状。我们筛选了来自六大洲的11个具有代表性的国家和地区,从教学内容和教学实施两方面对其K-12人工智能课程的顶级内容进行了评估,以了解不同国家K-12人工智能课程的现状。为K-12年级学生AI课程的开发提供一些想法和建议。(1)各国可选择AI应用、AI各方面影响、AI伦理、机器学习、数据、分类、推理、识别等内容,建立独立的AI教学内容标准;或者选择编程作为核心教学内容/起点;或者将编程、数据、人工智能和其他与提高学生计算思维相关的内容整合到计算机/科学/技术课程中。(2)以项目为基础的学习仍然是主要的教学方式,还有其他一些方法。现有的教学资源有四类,而且种类繁多。大多数国家都强调评价学生的能力和学习过程中取得的成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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