Predictive Decision Support System for Licensure Examination Performance through Integration of Multiple Regression and PART Classification Models of Data Mining

Abstract

Data mining is the process of discovering knowledge which in turn can be used to predict future trends. On the other hand, decision support system is an information system that enables one to analyze data and compile information that will aid in decision making process. This paper presents the integration of data mining and decision support system in an educational context. thus, a predictive decision support system for licensure examination performance (PDSS-LEP) is designed that highlights the repeated generation of multiple regression model and the integration of another classification model which was derived using PART classification technique. The PDSS-LEP was found beneficial as it provides a good platform for generation of MR model that can be adapted by other institutions because of its model selection procedures and user-oriented interface. It is however suggested that data integration should be enhanced by considering multiple sources of data.