Analysis of the Factors Affecting Student Performance Using a Neuro-Fuzzy Approach

Predicting students’ academic performance and the factors that significantly influence it can improve completion graduation rates, as well reduce attrition rates. In this study, we examine influencing student achievement. A fuzzy-neural approach is adopted to build a model predicts explains variations in course grades among students, based on category, attendance rate, gender, high-school grade, school type, grade point average (GPA), delivery mode input predictors. The neuro-fuzzy system was used because of its ability implicitly capture functional form between dependent variable Our results indicate most significant predictors are GPA, followed by category. Using sensitivity analysis, determined be factor explaining grades, with ranked third. findings also hybrid has positively impacted opposed online or face-to-face alone.