Research on the Evaluation Model of Practical Education Effect in Colleges and Universities Based on Big Data Analysis

Guanbo Zheng et al.

Journal of Cases on Information Technology2026https://doi.org/10.4018/jcit.398954article
ABDC C
Weight
0.50

What the paper says

In higher education, traditional evaluation methods have problems such as strong subjectivity and fragmented data. This study constructed an evaluation model for the effectiveness of practical education in universities based on big data analysis. It comprehensively used literature analysis, the Delphi method, an analytic hierarchy process, and other methods to construct an indicator system. With the help of big data analysis technology, multiple sources of data were collected and integrated, and linear regression models were used for evaluation. Through empirical analysis, the effectiveness of the model was verified. Research found significant differences in the effectiveness of practical education in different disciplines. Big data evaluation models promote teaching reform, and different types of practice contribute differently to ability development. This study provided data support for optimizing the practical education system in universities, which is of great significance for improving the quality of practical education.

Open paper page →

Cite this paper

https://doi.org/https://doi.org/10.4018/jcit.398954

Or copy a formatted citation

@article{guanbo2026,
  title        = {{Research on the Evaluation Model of Practical Education Effect in Colleges and Universities Based on Big Data Analysis}},
  author       = {Guanbo Zheng et al.},
  journal      = {Journal of Cases on Information Technology},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/jcit.398954},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Research on the Evaluation Model of Practical Education Effect in Colleges and Universities Based on Big Data Analysis

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.