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e-Learning, e-Education, and Online Training. 9th EAI International Conference, eLEOT 2023, Yantai, China, August 17-18, 2023, Proceedings, Part I

Research Article

Research on Online Education System for College English Majors Based on Cloud Computing

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-51465-4_21,
        author={Meizhi Wu},
        title={Research on Online Education System for College English Majors Based on Cloud Computing},
        proceedings={e-Learning, e-Education, and Online Training. 9th EAI International Conference, eLEOT 2023, Yantai, China, August 17-18, 2023, Proceedings, Part I},
        proceedings_a={ELEOT},
        year={2024},
        month={1},
        keywords={Teaching English Majors in Universities Online Education System Cloud Computing CP-ABE Encryption Algorithm},
        doi={10.1007/978-3-031-51465-4_21}
    }
    
  • Meizhi Wu
    Year: 2024
    Research on Online Education System for College English Majors Based on Cloud Computing
    ELEOT
    Springer
    DOI: 10.1007/978-3-031-51465-4_21
Meizhi Wu1,*
  • 1: School of Foreign Languages, Sichuan University Jinjiang College
*Contact email: wzm202303@163.com

Abstract

A new cloud computing based online education system for English major teaching in universities is proposed to address the issues of poor system usage and resource storage efficiency in online education systems. The system is based on cloud computing to construct the overall architecture of the system. The functions of each layer of the online education system are designed based on the overall structure. A low redundancy data storage algorithm based on data dependency is introduced to store system resource data. Combined with the CP-ABE encryption algorithm, the system is designed to share and improve the security performance of system resources, achieving research on online education systems for English majors in universities. The experimental results show that the system has a very satisfactory usage effect with a proportion of over 65.0%. The proportion of abnormal data stored in system resources is only 0.3%, and the probability of abnormal modification of resource data is less than 0.4% under all three conditions. This verifies that the system has higher system usage efficiency, resource storage efficiency, and resource data encryption effect. The CPU ratio of the system is studied to reduce the ratio and improve the operation effect of the system in the follow-up research work to further improve the performance of the system.

Keywords
Teaching English Majors in Universities Online Education System Cloud Computing CP-ABE Encryption Algorithm
Published
2024-01-17
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-51465-4_21
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