Model Construction and Research on Decision Support System for Education Management Based on Data Mining

Area of Science:

• Computer Science
• Educational Technology

Background:

• Data mining offers powerful tools for analyzing complex datasets.
• Educational management generates vast amounts of data requiring efficient analysis.
• Existing systems may lack sophisticated analytical capabilities for decision support.

Purpose of the Study:

• To develop a data mining-driven decision support system for educational management.
• To apply and improve data mining techniques, specifically the ID3 algorithm, for educational applications.
• To enhance the efficiency and scientific basis of educational assessment and decision-making.

Main Methods:

• Systematic analysis of data mining concepts and processes.
• Design and implementation of a B/S model-based educational management decision support system.
• Application and improvement of the ID3 decision tree algorithm for enhanced efficiency.

Main Results:

• Development of a functional educational management decision support system.
• Implementation of an improved ID3 algorithm reducing client load and increasing operational efficiency.
• Demonstrated capability for assessing and predicting teacher performance.

Conclusions:

• The developed system provides an efficient tool for educational administrators.
• Data mining techniques effectively extract valuable insights from educational data.
• The system supports scientific and efficient decision-making for improving teaching and learning.