Application of a Combined Approach of Text Mining and QFD Methodology Based on Single Valued Neutrosophic Numbers for Efficient Curriculum Design

Abstract

In this study, an alternate curriculum design for an undergraduate program of Statistics is suggested carrying out a combined approach of the QFD methodology, text mining techniques under single valued neutrosophic set environment. To capture the employers’ expectations from their potential employees, 640 job advertisements, obtained from two of the most important career and job posting sites in Turkey, were analyzed using TF-IDF technique, which is one of the text mining methods. By using single-valued neutrophic set (SVNS) theory in QFD, the technical requirements representing the courses included in the curriculum were found their priorities. Hence, the technical characteristics that play a critical role in evaluating the curriculum quality of the undergraduate program were revealed. In addition, single valued neutrosophic sets have provided a flexible decision-making procedure to improve the quality of individuals’ subjective assessments. Consequently, this is expected to be a good reference for researchers working on these issues, both in terms of the proposed approach and the problem addressed.