摘要
随着人工智能发展国家战略和基础教育新课程改革的深入实施,我国中小学人工智能教育有了较快发展。然而,中小学人工智能教育仍面临课程定位模糊、教学内容碎片化、教学方法薄弱等诸多问题。人工智能教育有效的教与学模式包括:基于丰富教学模式的需求出发,从知识内容和物化成果分类的角度构建的4I教学模式,随后拓展为5I教学模式;针对项目式教学和研究性学习的不足,提出以逆向工程教学和纠错教学为代表的TRIP教学模式和“灯笼”模型;针对合作学习和竞争学习的应用问题,从学习方式变革的角度提出的配对学习和竞合学习模式;针对当前创新能力培养过程中的不足,通过引入“聚类教学”与“深度学习”理念构建的面向创新能力培养的4C教学模式及其修订版。中小学人工智能教育将具有如下特征,并面临一系列挑战:编程工具的低门槛化;教育对象的普及化;教育目标的思维化;教育内容的整合化;教育力量的社会化。
With the in-depth implementation of the national strategies of artificial intelligence development and the new curriculum reform of basic education,artificial intelligence education in China has developed rapidly.However,artificial intelligence education still confronts many hurdles in primary and secondary schools,such as ambiguous curriculum orientation,fragmented teaching contents and weak teaching methods,etc.Effective teaching and learning models of artificial intelligence education include:the 4 I teaching model and the expanded 5 I teaching model built from the perspective of knowledge content and classification of materialized results based on the need for a rich teaching model;the TRIP teaching model and“lantern”model represented by reverse engineering teaching and error correction teaching for the shortcomings of project-based teaching and research learning;the paired learning and competing learning models proposed from the perspective of learning style change to address the application of cooperative learning and competitive learning;and the 4 C teaching model and its revised version which are built for the cultivation of innovation ability by introducing the concepts of“clustering teaching”and“deep learning”to address the shortcomings in the current process of cultivating innovation ability.Artificial intelligence education in primary and secondary schools will show the following developments and face a series of challenges:the low threshold of programming tools;the popularization of educational objects;the thinking of educational goals;the integration of educational contents;and the socialization of educational forces.
作者
钟柏昌
刘晓凡
Zhong Baichang;Liu Xiaofan(School of Information Technology in Education,South China Normal University,Guangzhou,Guangdong 510631,China)
出处
《中国教育科学（中英文）》
CSSCI
2022年第3期22-40,共19页
Education Sciences in China
基金
华南师范大学哲学社会科学重大培育项目“促进学生创新能力培养的跨学科教育模式研究”(ZDPY2104)
。
关键词
人工智能教育
机器人教育
创客教育
artificial intelligence education
robotics education
creator education
