Prediction of student academic performance by using an adaptive neuro-fuzzy inference system

Abstract

An assessment model based on adaptive neuro-fuzzy inference system (ANFIS) was designed for prediction of the students' academic performance. ANFIS is a composition of fuzzy system and neural networks. For enhancing the systems' speed, adaptability and flexibility, neural networks adapted to fuzzy inference system. The data used in this paper was collected from the students of computer and instructional technology education. Data sets include exam 1, exam 2, project, final and attitude points of the students at graphics and animation course for education in one semester. The performance of the assessment model is presented by graphics and percentages of success.