Analysis of Academic Performance of Mathematics Students Using Fuzzy Logic

Abstract

Traditional performance evaluation, which is primarily focused on exam results and frequently yields binary outcomes of pass or fail, is the mainstay of conventional assessment methods in the field of education. This study challenges conventional by presenting novel approaches to performance evaluation, particularly by employing fuzzy logic, a cutting-edge mathematical tool based on set theory that improves decision-making. Our research focuses on the NEP batch's academic performance in an autonomous college, evaluating their theory and practical mathematics scores from semesters I and II. In order to provide a more accurate and dynamic method of evaluating student achievement, this study promotes the use of fuzzy logic.The simulation's results provide strong evidence for the effectiveness of the suggested fuzzy logic-based evaluation technique. Beyond the limitations of conventional pass/fail classifications, the transition towards an elaborate and adaptable assessment framework has the potential to offer a deeper insight of student performance. The study promotes the use of fuzzy logic in educational evaluations in order to provide a more thorough and accurate depiction of students' academic performance.