ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2019, Vol. 56 ›› Issue (1): 209-224.doi: 10.7544/issn1000-1239.2019.20180758

• 综述 • 上一篇    

智慧教育研究现状与发展趋势

郑庆华1,3,董博2,3,钱步月1,3,田锋1,3,魏笔凡2,3,张未展1,3,刘均1,3   

  1. 1(西安交通大学电子与信息工程学院 西安 710049); 2(西安交通大学继续教育学院 西安 710049); 3(大数据算法与分析技术国家工程实验室(西安交通大学) 西安 710049) (qhzheng@mail.xjtu.edu.cn)
  • 出版日期: 2019-01-01
  • 基金资助: 
    国家重点研发计划项目(2018YFB1004500);国家自然科学基金项目(61532004,61532015,61502379,61672418,61672419);国家自然科学基金创新研究群体项目(61721002);教育部创新团队项目(IRT 17R86);中国工程院项目

The State of the Art and Future Tendency of Smart Education

Zheng Qinghua1,3,Dong Bo2,3,Qian Buyue1,3,Tianfeng1,3,Wei Bifan2,3,Zhang Weizhan1,3,Liujun1,3   

  1. 1(School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049); 2(School of Continuing Education, Xi’an Jiaotong University, Xi’an 710049); 3(National Engineering Laboratory for Big Data Analytics (Xi’an Jiaotong University), Xi’an 710049)
  • Online: 2019-01-01

摘要: 当前,以大数据分析、人工智能等信息技术为支撑的智慧教育模式已成教育信息化发展的趋势,也成为学术界热点的研究方向.首先,对教学行为、海量知识资源2类教育大数据的挖掘技术进行调研分析;其次,重点论述了导学、推荐、答疑、评价等教学环节中的4项关键技术,包括学习路径生成与导航、学习者画像与个性化推荐、智能在线答疑以及精细化评测,进而对比分析了国内外主流的智慧教育平台;最后,探讨了当前智慧教育研究的局限性,总结出在线智能学习助手、学习者智能评估、网络化群体认知、因果关系发现等智慧教育的研究发展方向.

关键词: 智慧教育, 教育大数据, 大数据分析, 人工智能, 知识图谱

Abstract: At present the smart education pattern supported by information technology such as big data analytics and artificial intelligence has become the trend of the development of education informatization, and also has become a popular research direction in academic hotspots. Firstly, we investigate and analyze the data mining technologies of two kinds of educational big data including teaching behavior and massive knowledge resources. Secondly, we focus on four vital technologies in teaching process such as learning guidance, recommendation, Q&A and evaluation, including learning path generation and navigation, learner profiling and personalized recommendations, online smart Q&A and precise evaluation. Then we compare and analyze the mainstream smart education platforms at home and abroad. Finally, we discuss the limitations of current smart education research and summarize the research and development directions of online smart learning assistants, learner smart assessment, networked group cognition, causality discovery and other smart education aspects.

Key words: smart education, educational big data, big data analytics, artificial intelligence, knowledge graph

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