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A Case Study

Jian Sun et al.

Journal of Cases on Information Technology2026https://doi.org/10.4018/jcit.406948article
ABDC C
Weight
0.50

What the paper says

This paper constructs a decision-support framework comprising data, rules, interventions, and feedback for ecological education, addressing the demand to integrate healthy consumption upgrading and ecological education. Based on students' physical measurement data over the past three years, this paper introduces transaction compression, hash pruning, and information entropy approximation to improve the Apriori algorithm, mines correlations among physical fitness indicators, and analyzes the current state of teaching practice using teachers' questionnaires. The results show that the improved algorithm can significantly enhance operational efficiency while maintaining rule consistency and effectively identify stable correlations between speed and strength and other key physical fitness indicators. The research shows that the data-driven method can provide a basis for operable teaching interventions and resource allocation for the ecological reform of physical education classrooms, and offer a reproducible case path for implementing ecological education in college and university physical education courses.

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https://doi.org/https://doi.org/10.4018/jcit.406948

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@article{jian2026,
  title        = {{A Case Study}},
  author       = {Jian Sun et al.},
  journal      = {Journal of Cases on Information Technology},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/jcit.406948},
}

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A Case Study

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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.