人工智能驱动的大学生个性化学习模式构建  

Construction of Artificial Intelligence-Driven Personalized Learning Models for the Students of Colleges and Universities

作　　者：杨冬 YANG Dong(Institute of Higher Education,Lanzhou University,Lanzhou,730000,China)

机构地区：[1]兰州大学高等教育研究院,甘肃兰州730000

出　　处：《高等理科教育》2025年第2期13-16,共4页Higher Education of Sciences

基　　金：甘肃省基础研究计划—软科学专项“工程教育智能化的应用场景、形成机制与实践路径研究”(项目编号:25JRZA016)。

摘　　要：人工智能正在重构大学教育教学,个性化学习是未来大学教育的基本方向。作为信息和数字技术高度发达的产物,凭借强大的数据、算法、算力和模型等,人工智能可将大学教育领域的一切加以智能化,为大学生个性化学习提供便捷条件和强力支撑。按照人机互动的内容和方式,人工智能驱动的大学生个性化学习模式可解构为基于知识的对话式学习、基于问题的探究式学习、基于实践的仿真式学习、基于情境的沉浸式学习、基于创新的合作式学习、基于平台的跨学科学习6种。大学只有处理好人与技术的共生交互关系,推动“机智”与“人智”协同互补,才能实现学生个性化学习效果的最大化。Artificial Intelligence(AI)is reshaping university education and teaching,and personalized learning is becoming a fundamental direction for future higher education.As a product of highly developed information and digital technologies,AI leverages its robust capabilities in data,algorithms,computing power,and models to intelligently transform all aspects of university education,providing convenient conditions and strong support for personalized learning among college students.Based on the content and methods of human-machine interaction,AI-driven personalized learning models for college students can be deconstructed into six types:knowledge-based conversational learning,problem-based inquiry learning,practice-oriented simulation learning,context-driven immersive learning,innovation-focused collaborative learning,and platform-enabled interdisciplinary learning.To maximize the effectiveness of personalized learning,universities must harmonize the symbiotic interaction between humans and technology,ensuring collaborative complementarity between"machine intelligence"and"human intelligence".

关 键 词：人工智能 个性化学习 人技关系 大学教育 学习模式 

分 类 号：G642.0[文化科学—高等教育学]