The Role of Multi-Agent System Based Educational Data Mining Techniques for Student Performance Prediction
Any educational institution's primary aim is to give students the highest educational opportunity and skills. To accomplish the purpose is necessary to recognize students who require additional assistance and take effective steps to increase their results. Educational programs require creative ways of improving school efficiency in order to produce the best outcomes and lower the risk of failure. Educational Decision Support System (EDSS) has recently boomed in education systems, enabling pupil outcome monitoring and assessment to be carried out in progress. Inadequate information systems face difficulty and obstacles to profit adequately from EDSS due to the lack of precision, improper study of the characteristic characteristics and inadequate database. A detailed literature review and collection of the highest predictive methodology are very critical for improving the prediction process. Machine learning methods were used for this study in order to construct a classifier that can forecast students' success in the economic field. This paper discuss about Intelligent Knowledge base DSS model to evaluate the student performance via mid-term exam and final-term exam using Multi-agent system based educational mining techniques.