人工智能在教育个性化推荐中的应用
摘 要
随着信息技术的迅猛发展，教育领域正经历着深刻的变革。其中，教育个性化推荐作为提升教学质量和学习效率的重要手段，日益受到广泛关注。本研究深入探讨了人工智能在教育个性化推荐中的应用，首先概述了教育个性化推荐的概念、特征以及人工智能的基本原理，分析了两者之间的契合点。通过对国内外研究现状的梳理，总结了人工智能在教育个性化推荐中的典型应用案例，并指出了现有应用的优势与局限。在此基础上，本研究重点探讨了学习者画像构建技术、学习资源智能匹配算法以及推荐效果评估方法等关键技术。同时，还提出了人工智能在教育个性化推荐中的实施策略，包括数据采集与处理、系统架构设计以及教师角色转变与支持等方面。
关键词：人工智能 个性化学习 教育推荐系统 深度学习
Abstract
With the rapid development of information technology, the field of education is undergoing profound changes. Among them, the personalized educational recommendation, as an important means to improve the teaching quality and learning efficiency, has been increasingly attracted wide attention. This study deeply discusses the application of artificial intelligence in the educational personalized recommendation. Firstly, it summarizes the concept, characteristics of the educational personalized recommendation and the basic principles of artificial intelligence of educational personalized recommendation, and analyzes the convergence point between the two. Through the analysis of the research status at home and abroad, the typical application cases of artificial intelligence in the personalized education recommendation are summarized, and the advantages and limitations of the existing applications are pointed out. On this basis, this study focuses on the key technologies such as learner portrait construction technology, intelligent matching algorithm of learning resources and recommendation effect evaluation method. At the same time, it also puts forward the implementation strategy of AI in the personalized education recommendation, including data collection and processing, system architecture design, and teacher role change and support.
Keywords:Artificial intelligence personalized learning educational recommendation system deep learning
目 录
1 引言 1
2 理论基础 1
2.1 教育个性化推荐的概念与特征 1
2.2 人工智能技术的基本原理 1
2.3 人工智能与教育个性化推荐的契合点 2
3 人工智能在教育个性化推荐中的应用现状 2
3.1 国内外研究现状分析 2
3.2 典型应用案例研究 3
3.3 现有应用的优势与局限 3
4 语人工智能在教育个性化推荐中的关键技术 4
4.1 学习者画像构建技术 4
4.2 学习资源智能匹配算法 4
4.3 推荐效果评估方法 5
5 人工智能在教育个性化推荐中的实施策略 5
5.1 数据采集与处理策略 5
5.2 系统架构设计原则 5
5.3 教师角色转变与支持策略 6
6 结论 6
致 谢 8
参考文献 9
摘 要
随着信息技术的迅猛发展，教育领域正经历着深刻的变革。其中，教育个性化推荐作为提升教学质量和学习效率的重要手段，日益受到广泛关注。本研究深入探讨了人工智能在教育个性化推荐中的应用，首先概述了教育个性化推荐的概念、特征以及人工智能的基本原理，分析了两者之间的契合点。通过对国内外研究现状的梳理，总结了人工智能在教育个性化推荐中的典型应用案例，并指出了现有应用的优势与局限。在此基础上，本研究重点探讨了学习者画像构建技术、学习资源智能匹配算法以及推荐效果评估方法等关键技术。同时，还提出了人工智能在教育个性化推荐中的实施策略，包括数据采集与处理、系统架构设计以及教师角色转变与支持等方面。
关键词：人工智能 个性化学习 教育推荐系统 深度学习
Abstract
With the rapid development of information technology, the field of education is undergoing profound changes. Among them, the personalized educational recommendation, as an important means to improve the teaching quality and learning efficiency, has been increasingly attracted wide attention. This study deeply discusses the application of artificial intelligence in the educational personalized recommendation. Firstly, it summarizes the concept, characteristics of the educational personalized recommendation and the basic principles of artificial intelligence of educational personalized recommendation, and analyzes the convergence point between the two. Through the analysis of the research status at home and abroad, the typical application cases of artificial intelligence in the personalized education recommendation are summarized, and the advantages and limitations of the existing applications are pointed out. On this basis, this study focuses on the key technologies such as learner portrait construction technology, intelligent matching algorithm of learning resources and recommendation effect evaluation method. At the same time, it also puts forward the implementation strategy of AI in the personalized education recommendation, including data collection and processing, system architecture design, and teacher role change and support.
Keywords:Artificial intelligence personalized learning educational recommendation system deep learning
目 录
1 引言 1
2 理论基础 1
2.1 教育个性化推荐的概念与特征 1
2.2 人工智能技术的基本原理 1
2.3 人工智能与教育个性化推荐的契合点 2
3 人工智能在教育个性化推荐中的应用现状 2
3.1 国内外研究现状分析 2
3.2 典型应用案例研究 3
3.3 现有应用的优势与局限 3
4 语人工智能在教育个性化推荐中的关键技术 4
4.1 学习者画像构建技术 4
4.2 学习资源智能匹配算法 4
4.3 推荐效果评估方法 5
5 人工智能在教育个性化推荐中的实施策略 5
5.1 数据采集与处理策略 5
5.2 系统架构设计原则 5
5.3 教师角色转变与支持策略 6
6 结论 6
致 谢 8
参考文献 9
