人机共教:AIGC赋能国际中文新手教师智慧备课的新生态
Human-Machine Co-teaching:A New Ecology of AIGC Empowering Novice International Chinese-language Teachers with Intelligent Lesson Preparation
余江英 1杨晓珊 1郑开文1
作者信息
- 1. 云南大学 汉语国际教育学院,云南 昆明 650091
- 折叠
摘要
"人机共教"新生态的构建是国际中文教育智慧化转型的关键所在.本研究聚焦国际中文新手教师备课的五大难点及 AIGC 的破解之道:以 AIGC 大语言模型力破汉语本体知识储备难;以AIGC强内容框架力破教案速写难;以 AIGC多轮对话能力破创新教学设计难;以 AIGC 跨模态生成力破教学课件制作难;以 AIGC自然语言理解力破教学语言控制难.基于"人机共教"对比实验得知:基于"人机多轮对话",可激发教师教学设计灵感;基于"强内容生成",可大幅度提升教师备课效率,探索出了一条国际中文新手教师智慧备课的新路径,尝试开启"1+1>2"的"人机共教"新生态.
Abstract
The construction of a new ecosystem of"human-machine co-teaching"is the key to the in-telligent transformation of international Chinese language education.This study focuses on the five major difficulties faced by novice international Chinese language teachers in lesson preparation and the solutions to the use of AIGC:using the AIGC language model to overcome the difficulty in obtaining the subject-matter knowledge of the Chinese language,using the AIGC strong content framework to overcome the difficulty in quickly writing teaching plans,using the AIGC multi-round dialogic ability to overcome the difficulty in the innovative teaching design,using the AIGC cross-modal generative power to overcome the difficulty in producing teaching courseware,and using the AIGC natural lan-guage understanding power to overcome the difficulty in controlling the teaching language.The"hu-man-machine co-teaching"comparative experiments have the following conclusions:the"human-ma-chine multi-round dialogues"can inspire teachers to design efficient teaching methods,and the"strong-content generation"can much improve the efficiency of the teacher's lesson preparation,which is a new path for intelligent lesson preparation for novice international Chinese language teachers and an attempt at ushering in a"1+1>2"new ecosystem of"human-machine co-teaching".
关键词
人机共教/AIGC/国际中文教师/教学设计/智慧备课Key words
human-machine co-teaching/AIGC/international Chinese language teachers/teaching design/intelligent lesson preparation引用本文复制引用
基金项目
教育部一般项目(20XJCZH012)
&&(23YH15B)
云南省教育厅科研项目(2023)(2023Y0307)
出版年
2024
NETL
NSTL
万方数据