生成式人工智能赋能教学设计分析:需求、方法和发展  

Generative Artificial Intelligence Empowers Instructional Design Analysis:Needs,Methods,and Prospects

作　　者：穆肃[1,2] 陈孝然 周德青 MU Su;CHEN Xiaoran;ZHOU Deqing(Institute of Artificial Intelligence in Education,South China Normal University,Guangzhou,510631,China;School of Information Technology in Education,South China Normal University,Guangzhou510631,China)

机构地区：[1]华南师范大学教育人工智能研究院,广东广州510631 [2]华南师范大学教育信息技术学院,广东广州510631

出　　处：《开放教育研究》2025年第1期61-72,共12页Open Education Research

基　　金：2024年国家社会科学基金一般项目“教师数字胜任力伴随式智能测评研究”(BCA240050)。

摘　　要：教学目标、教学方法、教学内容、教学环境与资源、教学评价等教学设计环节的决策质量直接影响教学活动效果。当前教学设计“人类制品”与“人工制品”普遍存在设计过程和结构程序化、偏离教师设计初衷和学生个性学习需求、数字技术运用不足与适切性不高、忽视情感投入与师生交互不足等问题。本研究在分析现实需求的基础上,借鉴四要素教学设计模型提出“学为中心:助力素养与思维培育”的理念指向和“生成式人工智能促进分析持续生成”的技术指向;构建了包含分析任务分解与规划、内容存储与记忆、功能实现与拓展、决策准确与可信四个环节的教学设计智能分析实践框架,并提供了相应实例;最后基于发展战略分析理性认识生成式人工智能赋能教学设计分析的应用挑战,展望主客观并重贯通的“师—机”协同教学设计智能分析的发展机会。The quality of decisions in various aspects of instructional design,such as teaching objectives,methods,content,environment and resources,strategies,and evaluation,directly affects the effectiveness of teaching activities.Currently,both“human-created”and“AI-created”instructional design products have problems in their procedural design processes and structures with insufficient and inappropriate use of digital technology,neglecting emotional investment and teacher-student interaction,that deviate from the original instructional design intention and students'individual learning needs.Thus,this study utilizes the four-element instructional design model to develop a theoretical concept of learner-centeredness to support the cultivation of critical thinking and a technology-oriented approach of generative artificial intelligence to promote continuous generation of analysis.Subsequently,a practical framework of intelligent analysis of instructional design is constructed,which includes four aspects:Analysis task decomposition and planning,content storage and memory,realization and expansion of analytical ability,and accuracy and credibility of optimal decision-making.The study proposes a practical framework exemplified by two examples:The general large language model and special agent instructional design analysis.Finally,based on the development strategy analysis,we rationally understand the application challenges of generative AI enabling instructional design analysis,and look forward to the development opportunities of"teachermachine"collaborative instructional design intelligent analysis that combines subjective and objective.

关 键 词：生成式人工智能 教学设计 教学设计分析 可行方法 风险挑战 

分 类 号：G421[文化科学—课程与教学论]