An efficient Model for Satisfaction Evaluation of College Students' Online Ideological and Political Education with Single-Valued Neutrosophic Numbers

Abstract

 Under the background of big data, the evaluation of college students' satisfaction 
with online ideological and political education (IAPE) is primarily achieved through data 
mining and analysis techniques, allowing for a more comprehensive and accurate reflection of 
students' attitudes and feedback. By collecting data through online surveys, social media 
interactions, and other channels, educators can adjust the content and methods of teaching in 
real-time to better meet students' needs and improve the effectiveness and satisfaction of IAPE. 
The satisfaction evaluation of college students' online IAPE in the context of big data is a multi
attribute group decision-making (MAGDM) problem. Recently, VIKOR method have been 
applied to address MAGDM challenges. Single-valued neutrosophic sets (SVNSs) are 
employed as a tool to represent uncertain data in the satisfaction evaluation of college students' 
online IAPE within the big data context. In this paper, we propose the single-valued 
neutrosophic number VIKOR (SVNN-VIKOR) method to solve MAGDM problems under 
SVNSs. Finally, a numerical case study is presented to validate the effectiveness of the proposed 
method in evaluating the satisfaction of college students' online IAPE in the context of big data. 

DOI: 10.5281/zenodo.14010259