Development and Design of Outward Training Management Platform for College Students Based on Cloud Computing
- 10.2991/assehr.k.220401.155How to use a DOI?
- Cloud computing; Management platform; Design and Implementation; Mental health
It has positive practical significance to complete the design of the Outward Training management platform for college students based on cloud computing technology, so as to deal with the trend of college students’ depression and suicide. Based on the system goal, this paper completes the exposition of the platform from the aspects of data analysis and function design. The design platform organization can be divided into data analysis phase, activity design phase and activity implementation phase. In the data analysis stage, the platform based on B/S architecture can collect students’ psychological data information. Then, the analysis and identification of the mental health status of college students is completed by designing a data analysis model. In the activity design stage, the platform will further complete the targeted Outward Training plan for college students by reading the analysis results of cloud logic and data. In the activity design stage, the platform will further complete the targeted Outward Training plan for college students by reading the analysis results of cloud logic and data. In the implementation stage of the activity, the management platform will complete the functions of instant communication, evaluation of teaching and establishment of students’ mental health data files based on the B/S structure.
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
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Cite this article
TY - CONF AU - Luqiang Cheng AU - Xingguang Chen AU - Zhaoguang Chen PY - 2022 DA - 2022/04/08 TI - Development and Design of Outward Training Management Platform for College Students Based on Cloud Computing BT - Proceedings of the 2022 International Conference on Social Sciences and Humanities and Arts (SSHA 2022) PB - Atlantis Press SP - 808 EP - 811 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220401.155 DO - 10.2991/assehr.k.220401.155 ID - Cheng2022 ER -