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

Abstract

Based on data mining technology, this paper applies a combination of theoretical and practical approaches to systematically describe the background and basic concepts related to the generation of data mining-related technologies. The classical data mining process is analyzed in depth and in detail, and the method of building a decision support system for education management based on the B/S model is studied. Not only are the data mining techniques applied to this system, but also the decision tree model with the improved ID3 algorithm is implemented in this thesis, which is further applied to the educational management decision support system of this topic. The load of the client computer is reduced, and the client computer only needs to run a small part of the program. This paper focuses on the following aspects: the overall planning of the educational management decision support system based on data mining technology. From the actual educational management work, we analyze the requirements and design each functional module of this system in detail, applying the system functional structure diagram and functional use case diagram to represent the functional structure of the system and using flow charts to illustrate the workflow of the system as a whole and in parts. The logical structure design, entity-relationship design, and physical model design of the database have been carried out. To improve the efficiency of the system, the ID3 algorithm was improved on this basis to reduce the time complexity of its operation, improve the efficiency of the system operation, and achieve the goal of assessing and predicting the teaching quality of teachers. The development and design of this system provide an efficient, convenient, scientific, and reliable system tool to reduce the workload of education administrators and, more importantly, to make reasonable and effective use of the large amount of data generated in the management, and data mining techniques are used to extract valuable and potential information from these data, which can be more scientific and efficient for the teaching of teachers and students. It can provide reliable, referenceable, and valuable information for managers to make assessments and decisions.

Implementation of Data Mining to Predict Student Study Period with Decision Tree Algorithm (C4.5)

“…Each node in this structure represents an attribute that has been tested to make a decision [22]. The application of data mining can also be used to understand the relationship between different attribute values [23]. In this research, using Decision Tree with the C4.5 algorithm.…”

Special Issue on Algorithms in Decision Support Systems Vol.2

“…These systems facilitate the extraction and manipulation of information in a flexible way, allowing users to define what information they need and how to combine it. Due to their ability to analyze and process data, they are widely used in different fields, such as population health management [1,2], education [3], medical diagnosis [4], catastrophe avoidance [5], agriculture [6], sustainable development [7], inventory organization [8], etc. The basic components needed to define the architecture of a DSS are (a) the knowledge base or database required for the storage of structured or unstructured information; (b) the user interface, essential for interactions between users and machines; (c) the model, used to infer decisions; and (d) the user, who normally uses the system and makes decisions.…”