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Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I

Research Article

Research on Autonomous Learning Management Software Based on Mobile Terminal

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-28787-9_53,
        author={Han Yin and Qinglong Liao},
        title={Research on Autonomous Learning Management Software Based on Mobile Terminal},
        proceedings={Advanced Hybrid Information Processing. 6th EAI International Conference, ADHIP 2022, Changsha, China, September 29-30, 2022, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2023},
        month={3},
        keywords={Mobile terminal equipment Psychological assistance Autonomous learning Management software Software development Learning management},
        doi={10.1007/978-3-031-28787-9_53}
    }
    
  • Han Yin
    Qinglong Liao
    Year: 2023
    Research on Autonomous Learning Management Software Based on Mobile Terminal
    ADHIP
    Springer
    DOI: 10.1007/978-3-031-28787-9_53
Han Yin1,*, Qinglong Liao2
  • 1: School of Traffic and Transportation, Xi’an Traffic Engineering Institute
  • 2: State Grid Chongqing Electric Power Research Institute
*Contact email: xinqiba001@sina.com

Abstract

There is a large amount of data calculation in the data transmission from the mobile terminal to the server edge. Psychologically assisted autonomous learning management software provides users with learning resources and learning activities to stimulate and maintain learning motivation. According to the software requirement, the whole development architecture is established based on the mobile terminal device, and the client mobile terminal device responds to the user operation and sends the data request to the Web server. The server adopts module entity to reflect the system database concept, divides the task into different modules according to the decision result, and reduces the delay of data transmission. The client is mainly composed of three interfaces: system login module, online learning module and support service module, which correspond to different activities respectively. The test results show that the psychologically aided autonomous learning management software based on mobile terminal device can reduce CPU usage and memory usage and improve performance.

Keywords
Mobile terminal equipment Psychological assistance Autonomous learning Management software Software development Learning management
Published
2023-03-22
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-28787-9_53
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