Research on integration method of AI teaching resources based on learning behaviour data analysis

被引:0
|
作者
Yang, Xiaohua [1 ]
机构
[1] Luohe Vocat Technol Coll, Clothing Dept, Luohe, Peoples R China
关键词
learning behaviour data analysis; artificial intelligence; teaching resources; integration method; random forest algorithms; mountain climbing method;
D O I
10.1504/ijceell.2020.110930
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Aiming at the problem of long running time and low precision of traditional artificial intelligence resource integration method, a new artificial intelligence teaching resource integration method based on learning behaviour data analysis is proposed. Analyse online learning behaviour data, extract relevant data of artificial intelligence teaching resources, and realise sample collection of artificial intelligence teaching resources. Random forest algorithm was used to classify them, reward and punishment factors were added, and mountain-climbing method was used to search the solution space, so as to realise the integration of artificial intelligence teaching resources. The experimental results show that this method can improve the efficiency and precision of the whole method, and obtain better integral results.
引用
收藏
页码:492 / 508
页数:17
相关论文
共 50 条
  • [31] The Research of Heterogeneous Data Source Integration Method Based on Ontology
    Department of Computer Anshan Normal University Anshan Liaoning China LouYabinTaoFengmei School of Computer Science and Engineering Anshan University of Science and Technology Ansha China MaYuan
    微计算机信息, 2005, (20) : 119 - 121
  • [32] Digital Resources for Teaching and Learning History: A Research Review
    Rodrigues Junior, Osvaldo
    Suelves, Diana Marin
    Gomez, Silvia Lopez
    Rodriguez, Jesus Rodriguez
    PANTA REI-DIGITAL JOURNAL OF HISTORY AND DIDACTICS OF HISTORY, 2024, 18
  • [33] Research on the Evaluation of Deeply Intelligent Classroom Teaching and Learning in Colleges and Universities Based on Data Analysis
    Liang F.
    Shen W.
    Chen L.
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [34] Research and Implement of Course Early Warning System Based on Teaching Behaviour Data
    Yang, Huansong
    Diao, Jingwei
    Zhou, Tao
    Yao, Zhengwei
    Shi, Xingmin
    Wang, Zhuping
    2018 INTERNATIONAL SEMINAR ON COMPUTER SCIENCE AND ENGINEERING TECHNOLOGY (SCSET 2018), 2019, 1176
  • [35] Research on Sharing System of Big Data Teaching Resources
    Dai, Zhiqiang
    PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON EDUCATION TECHNOLOGY, MANAGEMENT AND HUMANITIES SCIENCE, 2016, 50 : 432 - 434
  • [36] Emotion Analysis Method of Teaching Evaluation Texts Based on Deep Learning in Big Data Environment
    Li, Liqin
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [37] PhET Interactive Simulations: Free, research-based resources for teaching and learning chemistry
    Perkins, Katherine
    Lancaster, Kelly
    Parson, Robert
    Adams, Wendy
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2010, 239
  • [38] Technological Resources for Second Language Pronunciation Learning and Teaching: Research-based Approaches
    Walesiak, Beata
    JOURNAL OF SECOND LANGUAGE PRONUNCIATION, 2024, 10 (03) : 427 - 430
  • [39] A personalised recommendation method of online and offline mixed teaching resources based on user preference behaviour
    He, Qingqing
    International Journal of Reasoning-based Intelligent Systems, 2024, 16 (05) : 345 - 351
  • [40] Study of Network Teaching Resources Integration Mode under informal learning
    Xia, Yan
    PROCEEDINGS OF THE 2016 4TH INTERNATIONAL EDUCATION, ECONOMICS, SOCIAL SCIENCE, ARTS, SPORTS AND MANAGEMENT ENGINEERING CONFERENCE (IEESASM 2016), 2016, 22 : 910 - 912