Knowledge mining for effective teaching and enhancing engineering education

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.