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e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9–10, 2022, Proceedings, Part I

Research Article

College Library Assisted Online Teaching Model Based on Cloud Service

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-21161-4_43,
        author={Caifeng Gao},
        title={College Library Assisted Online Teaching Model Based on Cloud Service},
        proceedings={e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9--10, 2022, Proceedings, Part I},
        proceedings_a={ELEOT},
        year={2023},
        month={3},
        keywords={Cloud service University library Auxiliary online teaching model Learner characteristics analysis Resource characteristics Association rules},
        doi={10.1007/978-3-031-21161-4_43}
    }
    
  • Caifeng Gao
    Year: 2023
    College Library Assisted Online Teaching Model Based on Cloud Service
    ELEOT
    Springer
    DOI: 10.1007/978-3-031-21161-4_43
Caifeng Gao1,*
  • 1: Henan Medical College
*Contact email: dee8515555@sina.com

Abstract

Due to the low suitability between online teaching and learners, the teaching effect of online teaching is not ideal. Therefore, this paper puts forward a college library assisted online teaching model based on cloud service. On the analysis of the cloud services on the basis of the auxiliary in the teaching characteristics, constructs the contains learner characteristics analysis module, design module, the task group composition design module and learning resource design module of the online teaching model, using cloud services for university library resources characteristics were extracted, combining the resources of the university library association rules matching features and characteristics of learners, Realize the design of teaching resources. The results show that the degree of fitness, teaching resource satisfaction, teaching activity satisfaction and communication mode satisfaction of design students are 86%, 80%, 87% and 83% respectively, and it is very helpful for the improvement of comprehensive quality.

Keywords
Cloud service University library Auxiliary online teaching model Learner characteristics analysis Resource characteristics Association rules
Published
2023-03-09
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-21161-4_43
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