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

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 multiattribute 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. [ABSTRACT FROM AUTHOR]