QSVN Soft Sets and Their Applications in Student Classification

Abstract

For a learner, grades are very important. However, our modern educational system cannot provide correct grades to a student. In the current grading system, overall educational activities are not measured perfectly. Different letter grades are given to students in different subjects. The class rank is determined by considering average grade of these subjects. All these well-known methods of grading are not errorless. Thus, modern grading systems cannot be a proper reflection of student knowledge. In recent years, several authors have studied problems regarding educational measurement, particularly student assessments and grading. But most of the new methods are based on statistical techniques. Here, the authors have introduced Quadripartitioned single valued neutrosophic soft set (QSVNSS) for the first time. The authors have studied some set theoretic properties of QSVNSS. Also, several distance measures on QSVNSS are introduced. Based on the distance measures on QSVNSS, this chapter proposes some similarity measures on QSVNSS. Finally, these similarity measures are applied to a MADM real life problem.