| Literature DB >> 35655946 |
Ping Zou1, Yanjun Wu2, Jingdan Zhang3.
Abstract
This paper constructs a platform framework for extensive data analysis of college students' psychological quality with the help of the thinking mode of big data and related technologies and proposes the construction principles, data sources, data processing methods, data platform construction, and platform application of big data analysis platform for college students' psychological quality assessment. This paper combines the application methods of big data technology, collects the management data related to the psychological quality assessment of college students, saves them into the system database with certain storage logic, and realizes the function of psychological quality assessment through the design of selected psychological quality assessment data, data management and data resource management and other parts based on the data results of extensive data analysis. This study provides some insights into the psychological quality assessment of college students. The strength of association between the variables of psychological quality assessment of college students changes over time, but the overall psychological structure is more stable. This stable psychological structure characteristic is conducive to constructing the policy of constant psychological education in large universities.Entities:
Mesh:
Year: 2022 PMID: 35655946 PMCID: PMC9146441 DOI: 10.1155/2022/7982808
Source DB: PubMed Journal: Occup Ther Int ISSN: 0966-7903 Impact factor: 1.565
Figure 1Differences in the psychological quality of college students.
Read and write parameters.
| Name | Symbol | Minimum value | Typical value | Maximum value |
|---|---|---|---|---|
| Count data build time | TDDR | 1 | 12 | 30 |
| Write data build time | TDSW | 1500 | 3000 | 5200 |
| Data hold time | TH | 160 | 410 | 920 |
| Address hold time | TAH | 30 | 45 | 120 |
| Address build time | TAb | 35 | 74 | 150 |
| Pulse width | TPw | 34 | 65 | 160 |
| Cycle time | TC | 54 | 110 | 210 |
| Rise/fall time | TF TR | 30 | 65 | 130 |
Figure 2Big data analysis process processing framework.
Figure 3The process of psychological quality assessment of college students.
Figure 4Comparison results of measuring management efficiency.