国际中文课堂教学模式识别理论的构建与实践研究
Construction of a Recognition Theory of Teaching Patterns in International Chinese Language Classrooms and its Implementation
郭媛媛 1李吉梅2
作者信息
- 1. 北京语言大学,中国 北京 100083;北京华文学院,中国 北京 102206
- 2. 北京语言大学,中国 北京 100083
- 折叠
摘要
国际中文教师的专业发展是提升教学质量的关键.本文以赋能教师反思为目标,以国际中文教育课堂文本数据为基础,首先创新性地提出了一个多层面的国际中文课堂教学模式识别框架,实现了对课堂教学宏观结构和微观互动的精确建模.然后基于大语言模型,设计了自动识别国际中文课堂教学模式的方法,验证了该方法的有效性,并分析了大语言模型应用于课堂教学模式识别的优势与挑战,揭示了人工智能在教学模式识别和教育数据挖掘方面的应用潜力.本文提出的课堂教学模式识别框架对国际中文教师的课堂教学设计和课后反思具有指导和借鉴意义,设计实现的模式识别方法可有效提升课堂分析的智能化程度,助力课堂分析的数字化转型.
Abstract
The professional development of international Chinese language teachers is crucial for im-proving teaching quality.Based on the international Chinese language classroom discourse texts,this paper aims to empower such teachers through reflections.Firstly,it innovatively proposes a multi-fac-eted framework for identifying teaching models in international Chinese language classrooms,achieving the precise modeling of both macro-classroom structures and micro-level interactions.Then,using the large language models,it designs a method for automatically identifying teaching models in international Chinese language classrooms,verifies the effectiveness of this method,and analyzes the advantages and challenges of applying the large language models to the recognition of classroom teach-ing models.It reveals the potential of artificial intelligence in teaching model recognition and educa-tional data mining.The identification framework of the classroom teaching model proposed in this pa-per provides guidance and reference for the classroom teaching design and post-class reflection of in-ternational Chinese language teachers.The designed model recognition method can effectively enhance the intelligence level of classroom analysis,supporting the digital transformation of classroom analy-sis.
关键词
国际中文教育/大语言模型/课堂话语/教学模式/课堂教学分析Key words
international Chinese language education/large language models/classroom discourse/teaching patterns/classroom teaching analysis引用本文复制引用
基金项目
教育部中外语言交流合作中心国际中文教育研究重点课题(2023)(23YH02B)
中央高校基本科研业务费专项(22YJ080004)
国家新文科项目(2021180006)
出版年
2024
NETL
NSTL
万方数据