Instructor’s Performance Evaluation System using Data Mining Techniques

Abstract: The development of an improved and intelligent model for the evaluation of instructors� performance in higher institutions uses the efficient data mining techniques considering the drawbacks of the prior traditional techniques. This proposed system analyses the factors related with the evaluation of instructors teaching performance using predictive data mining techniques known as regression statistical model. Regression is a data mining predictive technique that is used to make statistical prediction of the variables, given a set of data. Consequently, the evaluation of instructors� performance is useful for the academic institutions as it helps to make effective managerial decisions, improve the quality, reliability and efficiency of the instructors, provides a basis for the performance improvement that will optimize students� academic outcomes and improve standard of education and contribute to successful accomplishment of the organizational goals.

Keywords: Prediction algorithms, Statistical Regression Model, Linear Regression algorithm, Performance Evaluation, Educational Data Mining (EDM).