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.基于AI自适应学习系统开展初中数学差异化教学策略研究.首先,通过多维度数据采集构建学生个性化知识图谱与能力画像,划分学生层级并制定差异化教学目标与内容,实现"一人一策"的精准教学.其次,系统智能推送适配资源与任务,动态调整学习路径,打破传统课堂固定进度限制,推动初中数学差异化教学向个性化赋能转型.人工智能驱动的自适应学习对学生个性化 学习效果有何影响?——基于 29 项实验和准实验研究的元分析

北京海天环球教育科技有限公司26-05-16【产品中心】8人已围观

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上一篇： .

教育数字化转型背景下,人工智能(Artificial Intelligence, AI)正深刻改变高等教育的教学生态.大学英语作为高校最普及的基础课程,大班授课,内容统一,差异显著的教学现实,使传统模式面临适配性不足,反馈滞后,评价单一等结构性困境.随着数据驱动教学理念的兴起以及自然语言处理,机器学习,自适应学习系统等技术的成熟,基于 AI 的个性化教学已成为提高大学英语教学质量的重要路径.本文以建构主义,多元智能理论和数据驱动教学理论为基础,系统分析大学英语个性化教学的现实需求,构建了包括"课前智能诊断""课中动态适配""课后拓展支持"三个阶段在内的大学英语个性化教学模式,并进一步提出技术,资源与制度等多重保障体系.研究认为,该模式能够有效提升教学适配性,提高学习者自主性和交互质量,为高校推进英语教育现代化提供理论依据与可操作范式.

基于AI自适应学习系统的初中数学差异化教学策略研究

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With the rapid advancement of artificial intelligence (AI) technology, the role of adaptive learning in promoting students' personalized learning outcomes has become a pivotal issue in current educational reform and technology application. Based on this, this paper conducted a meta-analysis of 29 experimental and quasi-experimental research to explore the influence of AI-driven adaptive learning on students' personalized learning outcomes, and to examine potential moderating variables that may cause heterogeneity in the research findings. The results indicated that AI-driven adaptive learning had a significant positive effect on students' personalized learning outcomes, with particularly prominent performance in enhancing sustainable adaptive learning abilities. Furthermore, the effectiveness of AI-driven adaptive learning was regulated by the specific adaptive technologies and adaptive engines employed. Based on the above findings, in order to promote the efficiency of AI-driven adaptive learning in enhancing students' personalized learning and technical adaptability, provide support for promoting personalized cognitive outcomes and personalized non-cognitive development, and optimize the application of adaptive technologies and adaptive engines, so as to enhance the effectiveness of AI-driven adaptive learning in promoting students' personalized learning and improving their technological adaptability.

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