July 10, 2025Transactions on Computer Science and Intelligent Systems Research

Application of Data Mining in Education

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QCQihao ChenWuhan University of Technology

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Implication

This review highlights how data mining methods improve student behavior analysis and educational interventions, suggesting new paths for interdisciplinary collaboration.

Key Points

Data mining techniques uncover valuable insights from educational data, enhancing decision-making in educational practices.
Clustering algorithms effectively group students, yet initial data handling needs optimization for better analysis outcomes.
Deep learning models excel in predictions but struggle with interpretability, limiting their direct application in education.
Innovative data visualization techniques bridge algorithm outputs and educational applications, promoting ethical data use.

Cite This Study

Qihao Chen (2025) studied this question.

synapsesocial.com/papers/68af736e7567bf4f94fed8af https://doi.org/10.62051/f68v1y26

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Implication

This review highlights how data mining methods improve student behavior analysis and educational interventions, suggesting new paths for interdisciplinary collaboration.

Application of Data Mining in Education

Discussion

Member takes

Implication

Key Points

Cite This Study

Application of Data Mining in Education

Discussion

Member takes

Implication

Key Points

Cite This Study

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Also Consider