Knowledge mining for effective teaching and enhancing engineering education

Abstract

In this paper, we introduce a web based learning approach for developing teaching practice and students' knowledge in engineering education, which performs knowledge mining from students' web usage data. We develop an intelligent web application using J2EE that consists both classification and clustering models for mining students' learning activities. The classification model uses decision tree for classifying the learning issues. And clustering model clusters the students into a number of groups so that we can identify each individual student and teach him on his depth of knowledge for a particular engineering course. The weak students need to know the basic fundamental issues of a course and the strong students need to exercise complex problems for developing their conceptual and procedural knowledge of a course in engineering education. The study shows that the proposed learning approach helps the students' learning process to improve their knowledge in engineering education.