摘要
互动式、启发式和探究式课堂教学,即IHI课堂教学是新型课堂教学的重要体现。IHI课堂教学以建构主义理论为依据,以课堂对话为主要实现方式,以思维培养和创新能力提升为主要目标,与基础教育高质量发展要求和新时期人才培养目标具有较大的契合性。由于课堂互动涉及多元主体,课堂中的知识探究与建构过程更为复杂,思维进阶与认知演化规律具有内隐性,因此发展新型课堂教学更具有挑战性。人工智能技术为研究新型课堂教学模式、发展优质课堂提供了有效手段,有助于实现课堂教学全过程监测,掌握课堂教学深层规律,促进课堂教学精准评价。在技术实现路径上,作者团队创设了混合神经网络技术对课堂互动进行自动标注,发展了序列模式挖掘方法提炼课堂教学中的思维进阶和问题探究规律,借助图神经网络对新型课堂教学模式进行精准表征。在此基础上,本研究以200节义务教育阶段课例为例,证实了人工智能技术能够有效识别课堂教学特征,提炼课堂教学模式,使课堂教学中的师生互动更加有效,知识建构和问题探究路径更为多元,发挥了多重认知功能,体现了思维从低阶向高阶发展的规律。
Interactive, heuristic and inquiry classroom teaching(IHI classroom teaching) is an important embodiment of new classroom teaching. IHI classroom teaching is based on constructivism theory, with classroom dialogue as a main way to achieve, and the improvement of thinking skills and innovation ability as the main objective. The new teaching styles are aligenced well with the high-quality development of basic education and the goal of talent cultivation in the new era. Classroom interaction involves multiple subjects, the process of knowledge exploration and construction in the classroom is more complex, and the law of advanced thinking and cognitive evolution is implicit, rendering the development of new classroom teaching more challenging. Artificial intelligence technology provides an effective means to study new classroom teaching modes and promotes the transformation of classroom teaching. It helps to monitor the whole process of classroom teaching, master the deep laws of classroom teaching and promote the accurate evaluation of classroom teaching. In the path of technical realization, the author’s team has created a hybrid neural network technology for large-scale automatic annotation of classroom interaction, developed a sequential pattern mining method to refine the advanced rules of thinking in classroom teaching, and accurately characterized the new classroom teaching mode with the help of graph neural network. On this basis, this study takes 200 courses in compulsory education courses as an example, and proves that artificial intelligence technology can effectively identify the characteristics of classroom teaching and refine the classroom teaching mode. In high-level classroom teaching, the interaction between teachers and students is more effective, the paths of knowledge construction and problem exploration are more diverse. The high-quality classroom teaching plays multiple cognitive functions, and reflects the law of the development of thinking from low-level to high-level.
作者
宋宇
SONG Yu(School of Education,South China Normal University,Guangzhou,510631,China)
出处
《全球教育展望》
CSSCI
北大核心
2022年第10期19-29,共11页
Global Education
基金
国家自然科学基金项目“学习分析视角下面向高阶思维发展的课堂互动分析与评测”(项目编号:61907017)的研究成果。
关键词
人工智能
新型课堂教学
神经网络技术
规律挖掘
Artificial Intelligence
new classroom teaching
neural network technology
rule mining
