Research On Application Of Decision-tree And Association Analysis In The Education Management Of Higher Vocational Colleges

With the rapid development of education, higher vocational colleges have been expanding their sizes and recruiting more students in recent years. Because of the increase of the faculty and students, most of the traditional teaching management models can not adapt to the development of colleges. All the colleges have been increasing the investment on information technology to improve the education management efficiency and standard effectively, and various kinds of information management systems are put into use, such as education administration system, score Administration system, the school register management system, college CRP system, library information management systems and so on. Such systems can improve the working efficiency and working level, they can save the money, manpower and material resources as well. Such systems brought a lot of convenience to daily management. However, if the database systems have accumulated a great deal of data, with the time elapse, these historical statistics have not been put into good use; on the contrary, they became garbage files and were deleted and rejected. Although these management systems can only use functions on recording, consulting, modifying and so on, they can not get the internal connections and corresponding rules between the data. If we can make good use of the data which come from first level, find out the valuable information hidden in the data, and improve their utility value, we can offer better factual basis to decision-makers, help them change the management methods and improve the educational quality and level.In the face of massive statistics in vocational schools, data mining technology is an intelligent information processing technology that can find knowledge from a huge amount of data effectively. If using data mining techniques to explore the potential and valuable information, it will provide strong support for teaching reform of vocational education. Therefore, it will be a great breakthrough for data mining applied in higher education.Based on data mining technology, this article solves two practical problems for higher vocational colleges’ education:First, establish a tree model about the curriculum and student employment.The market-oriented teaching goal is the ultimate goal in higher vocational colleges. As the products of schools, students can not meet the requirements of the market unless they are good enough. So, if we want to make the students meet the demand of the market and reach the requirement of employers, we have to conduct the data mining to the academic record and employment status of students. Getting the rate that all the courses affect the employment of students, we can adjust the arrangement of professional curriculum without delay and improve the talent training scheme. Nowadays, the curriculum-provision system in higher vocational colleges mainly concentrates on the requirement of mainstream companies, but it is not universal. Based on the facts of the data, the result from data mining is reliable. If we adjust courses according to these data, we will make the curriculum more rational, and more conducive to the students’ employment.The author analyzed the school course grades and employment situation of alumni by using C4.5algorithm and ID3algorithm to establish a tree model of curriculum and employment situation. Find out that the course will affect students’ employment and the rules between them, provide a basis for future reform of the curriculum. Students can follow the model to guide their interest and orientation in learning.Second, how to use data mining to find reference books in library and build associated model for courses and reference books.The university library is an important place for students to study by themselves. There are a large number of literature information resources in the library. Students can collect professional knowledge there after class. The library plays a very important role in their study. But the resources in the library are of great quantity, various reference books can’t be counted. So it is very important to find out which reference books among them are helpful to the students when they are learning this course. Sometimes most of the students are aimless when they are selecting. The method in which the students choose the appropriate reference books is introduced in this article.Using meta-rules method of data mining technology, through mathematical algorithms and Apriori arithmetic respectively, the author is easy to calculate and verify the relevance between courses and reference books. The author used the Apriori algorithm to find out the connection rules between curriculum and reference books, through those rules we find that curriculum and reference books have a strong positive correlation relationship. Students can choose their reference books that are suitable for them according to the rules, thus they can make good use of resources in the library.