Clustering Moodle Data As a Tool For Profiling Students Existing System

Abstract We wish to create system that will gather information related to e-learning courses and performing analysis on the data. In this system analysis, clustering and prediction on data is performed to generate results, which makes monitoring data easier. The aim of our project is to use the methods of data mining, machine learning to given students better tools to help their e-learning courses.In this system processing of Moodle data is to be carried out.This project includes online tests, quizzes, displaying notifications, assignments submission ,calculating grades,attendance sheet generation etc. Keywords:Datamining,Clustering,Prediction,Machine learning Problem Definition To make monitoring easier, we will provide reliable statistics, behavior groups and predicted results.In this step of the project, we are clustering students by mining Moodle log data. A first objective is to define relevant clustering features. A second objective is to determine if our students show different learning behaviours. We will experiment whether there is an overall,ideal number of clusters and whether the clusters show mostly qualitative or quantitative differences. Experiments in clustering were carried out using real data obtained from various institute using Moodle platform