【作 者】：
孙立会， 刘思远， 李曼曼
【关 键 词 】：
人工智能； 计算思维； 儿童编程教育； 学校化； 政策建议
【栏 目】：
历史与国际比较
【中文摘要】：
与学校体系、学科相融合是人工智能时代儿童编程教育的发展图景。文章以日本文部科学省开展“儿童编程教育发展必要条件”调查为研究对象，以数据分析形式探讨了儿童编程教育学校化的困难与应对措施。研究发现：日本推行儿童编程教育的困难主要有信息不足、人才不足与预算不足，推行困难随实施程度的深入由信息不足向预算不足转变；时间不足、教师负担过重也是重要的阻碍因素。其应对措施体现在制定规划纲要与开展培训相统一，实现编程技术、教学方法和心理辅导相统一，纳入正常课程体系与教材教法建设相统一，多元支持体系与细化内容相统一四个方面。在此基础上，提出推进我国儿童编程教育深度发展的建议：在政策层面，制定规划纲要、搭建发展平台；在理论层面，要明确儿童编程教育的社会价值、强化一线教师对儿童编程教育的重视、正确认识并遵循儿童编程教育发展规律；在学校实践层面，强化儿童编程教育理念宣传、教材编制、师资培训、外部合作、评价标准，在学习国际经验的同时立足本土创新。
【英文摘要】：
With the emergence of a series of problems concerning moral, security and data management in learning analytics, the study of learning analytics policy has attracted great attention of researchers in various countries. In order to verify that SHEILA framework plays a guiding role in the formulation of China's learning analytics policy, based on literature research, this paper starts from the practicality of SHEILA framework, and summarizes the challenges in the field of learning analytics at home and abroad, as well as the application of SHEILA framework. Meanwhile, this paper carries out a comparative analysis of four European higher education institutions that have applied the SHEILA framework to develop learning analytics policies. The results show that ethical and safety issues as well as institutional and management issues are the main challenges in the development of learning analytics in China. The SHEILA framework can provide evidence to support policy-making, assess the quality of existing learning analytics initiatives, promote dialogues among key stakeholders and provide information for the policy-making process. Finally, based on the practical application of SHEILA framework, this study proposes that the application of SHEILA framework in China needs to focus on the assessment of the readiness of learning analytics, the responsibilities of stakeholders and institutional data management, the school leadership of organizing informatization, and experience sharing and case promotion, which provides theoretical guidance for the policy-making of learning analytics in China.