Educational Data Mining on students’ academic performance using Clustering technique

Abstract

The student database needs to be analysed and the useful information is to be extracted by the educational institutions to focus on improvement in the student records. The performance indicators of students are to be observed as they may count on varied factors including their learning methodology, environment they are associated with, their place of stay and so on. Data Mining comes up with its techniques and applications to satisfy the needs. Educational Data Mining, an emerging application of data mining used principally on student data is applied here to discover knowledge from the largely available data. Clustering of students is done using K-means based on their scores where students of the same cluster show homogenous characteristics with one another and the interesting hidden patterns among the students are mined. Here, R tool provides an extensive platform to accomplish the mining process. The reports are generated in the form of visualization through graphs