The paper focuses on Web usage mining (WUM) among students categories of accessing web contents for their education purposes. The study focuses on finding the potential knowledge from browsing patterns of the students. It leads us to find the correlation between web pages in the students visit. The primary data source used in web usage mining is the university server log-files (web-logs). Browsing web pages by the students leaves a lot of information in the log-file. Analysing log-files information drives us to understand the behaviour of the student in academic basis. Web-logs include web server access logs, proxy server logs, client logs and application server logs. Our paper focuses on the use of web mining techniques to cluster web pages according to students visit. This cluster process helps us to understand the student’s behaviour in accessing the network.