Predicting Students’ Academic Performance Using Data Mining
Abstract
In daily education and teaching, schools have accumulated lots of complex data on education and teaching, and it has become more and more difficult to manage and retrieve this data. How to find the intrinsic and valuable information from this data to provide reference information for school decision-makers, and to scientifically guide the teaching and to improve teaching management level is currently an issue for further study. At the same time, the rapid development of data mining technology and the continuous expansion of its applications makes the data mining technology in teaching and management become an inevitable trend. It is undoubtedly very useful that the data mining is applied to the teaching which can comprehensively analyse the hidden internal links between the test results and a variety of factors to take effective measures in a targeted manner and to improve the quality of education and teaching
Mainly based on the given students’ achievement data, this paper uses the data mining technology (classification and prediction, association analysis, cluster analysis), and uses Oracle 10G and BI tools. In accordance with the corresponding analytical model, students’ achievement data is retrieved to get the internal links among failed courses from warning students, and to get the possible reasons for failure. Key factors, as well as the common characteristics of these students, are retrieved to identify hidden rules and patterns. Based on this useful information, a prediction is made on the students who are going to, or have already, deviated from the credit requirements. A prediction for subsequent teaching requirement is also made, to improve the overall quality of teaching.
Contents
Abstract 2
Acknowledgments 3
1. Introduction 5
1.1 The background and significance of the subject/topic 5
1.2 The Main Work of This Project 7
1.3 The structural arrangement of this project 7
2. Students Performance Prediction 9
3. Student performance database Design 11
3.1 Based on management decision-making system, characteristic analysis on Database 11
3.2 The database design of analysis on students’ a performance 11
3.2.1 Aims and requirements 11
3.2.2 Requirements analysis 12
3.2.3 System Function Demand Design 12
3.2.4 System Function Design 12
3.2.5 Data Dictionary 13
3.2.6 Concept Model Design 14
3.2.7 The logical structure and physical structure design 15
(2) Course ( Course_Code, Course_Name), Course_Code as the Primary key; 15
The storage structures of the database 16
4. Data Mining 18
4.1 Data Mining? 18
4.1.1 What is the Data Mining? 18
4.1.2 What Data Mining can do? 19
4.1.3 How is the application of data mining in various fields 22
4.2 Introduce Oracle Data Mining 23
4.2.1 Why we choose the Oracle Data Mining? 23
4.2.2 The function of the Data Mining: 23
4.2.3 The Algorithms of the Data Mining 25
ETL Implementation 25
5. Student Data Analysis Using Oracle BI Tools 26
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