The Study On The Application Of The Data Mining In The College Students Score Management

The student score management is one of the important aspects of the colleges and universities teaching and learning. But in despite of the increasing number of the college students, most of the colleges and universities still use the conventional pattern of the student score management. This pattern can not find the 'knowledge' in the substantive student score. Then, the improvement of the currently used pattern is badly needed so that the exact reasons which affect the score of students can be found and the quality and the effect of the teaching and learning can be improved.Through deeply researching on the concrete situation of the present colleges and universities score management, the paper raises the advice to use association rules mining and decision-tree classification technology to improve the currently used score management pattern. In the decision-tree classification, ID3 algorithm is used to analyze and mine score of each examination question and the sum score of English final exams, which will help to produce decision tree, thus find the factors affecting student's final examination and advance the pass rate of English examinations. In the association rules mining, the paper use Apriori algorithm to analyze the affect-degree of one lesson to others so that gaining some valuable information and rules which can provide technical supporting to the courses setting of the educational administration.