An application of undergraduate academic growth path on the credit system based on data mining

With the development of teaching reformation in colleges and universities, the application of the credit system is an inevitable trend. On the basis of the credit system, students can select the courses freely and independently according to their academic plan. However, there are some problems about the credit system as following. How do the students select the courses in accordance of specialty knowledge? How do the students cultivate their own professional quality in accordance of social requirements? How do the students plan their academic path in accordance of talents training? Thence, the kernel key of the credit system is to cultivate the applicable and high-quality talents from colleges and universities. At the same time, the data mining is a kind of effective data analysis technologies. Because a group of big data would come exactly from the digital information of administration processing of colleges and universities, the application of data mining on it could solve these problems above and promote the implementation of the credit system in colleges and universities.