A KNOWLEDGE DISCOVERY BASED DECISION TECHNIQUE IN ENGINEERING EDUCATION PLANNING

Abstract

One of the main challenges of process perspective in higher engineering education planning is to take the right decision from innumerable choices of engineering discipline/branches for seeking admission in Engineering Colleges/ Universities / Institutions. To overcome this problem, we are trying to implement a Knowledge Discovery based Technique (as a part of KDDS) to predict a right decision in particular engineering discipline/branch for a particular student. In this work, we analyzed the real data (35,534 records) of All India Engineering Entrance Examination (AIEEE) 2007. As a part of this technique our focus is to build a Decision Tree and a Rule set to predict particular discipline/branch (e.g. Computer Engineering, Civil Engineering etc.) using Decision Tree Algorithm such as C5.0/See5, C&R Tree and ANN Algorithm in SPSS Clementine 11.1 Environment. Based on these algorithms, accuracy Rate for different partition sizes of the data is calculated and compared. Finally we have introduced a hybrid knowledge based decision technique in .NET platform to take a right decision of engineering discipline/branches.