The Study Of Web Usage Mining Used On E-Learning Platroms

Now, with the popularization of the network and distance education development, there are a growing number of e-learning platforms, such as the Quality Course Web site, game-based learning community. The main problem of these e-learning platforms is that the contents of them are fixed. Learners cannot be provided personalized learning services. After a period of use, server log files of e-learning platforms record a lot of access information and data, back-end database of e-learning platforms has accumulated a large number of students'registration information, academic and other useful data. These data contain useful knowledge; data mining techniques were used to dig out the useful knowledge to optimize the site's structure, to provide users with personalized learning services.Data mining is a very hot topic in the area of database applications in recent years, either the theory or the application of the results has been made a lot.And the technology is relatively mature. The current research gradually shifts from the theory to the application. Data mining has been applied into such industries as credit card companies, retailers, financial services institutions, banks, cellar sales, the aviation industry, manufacturing, telecommunications companies, insurance companies and medical industry. Data mining applications in the field of education is also relatively small. In this paper, we study the data mining application in education, specifically the application of Web usage mining on e-learning platforms.This paper introduces the data mining, Web data mining and network learning platform concepts, and points out that the current lack of e-learning platforms and to make Web-based learning platform for personalized learning. Then the author mines a course of e-learning platform. Web usage mining is divided into two parts, the first part is mining on Web access logs, and the approach is mainly based on statistical data mining. The mining of the access logs mainly use analog and Web log explorer for statistical analysis of data mining, found that learners on the site visits, frequently accessed pages etc. to help the manager of e-learning platforms to improve the site's structure to improve the site cache. The second part is mining on the background database, e-learning platforms are generally dynamic, and its back-end database records a lot of use of information such as the learner's registration information, message recording, online examinations, and online discussions. Mining on this information, the level of utilization in the e-learning platform can be found. Mining method is mainly using the data mining features of SQL Server 2005. In the SQL Server 2005, in accordance with the steps of the establishment of business intelligence is to import the data, modeling, mining, analysis. Ming the back-end database which Record the use of students can help teachers better understand the students for the classroom teaching or remote guidance teaching. The Paper finally concludes the design of an intelligent e-learning platform with a Web usage mining function, which is able to mining e-learning platform Web logs and back-end databases, tracking learners'learning behavior, analysis of learners learning and cognitive levels of learners for classification, providing learning resources for students, pushing resources. The e-learning platform will be more capable of teaching every learner, providing personalized service. According to the results of mining, some suggests about the personalized of e-learning platforms are listed.