Paper Info
Title
A Heterogeneous Information-Based Multi-Attribute Decision Making Framework for Teaching Model Evaluation in Economic Statistics
Abstract
A teaching model is a stable teaching procedure established under the guidance of certain teaching ideas or theories. As a methodological major in higher education, economic statistics cross various fields of natural science and social science, showing the characteristics of intersection, integration, and marginality. Therefore, this paper proposes a multi-attribute decision-making (MADM) framework for teaching model evaluation based on heterogeneous information. First, the attribute system of competition-academic research-master of knowledge-practical operation (CAMP) is constructed. Second, heterogeneous information is introduced in the process of teaching model evaluation; Third, a weight determination method based on a trust relationship of the fuzzy-social network is proposed, which provides a better solution to the problem of decision makers' (DMs') weight allocation in teaching model evaluation. Furthermore, a combined attribute weights determination method under an intuitionistic fuzzy number is constructed, which improves the shortcomings of the weight method in teaching model evaluation. Finally, through empirical research and stability analysis, the proposed evaluation framework has good effectiveness and feasibility, and policy suggestions for improvements to the economic statistical teaching model are then proposed.
Year
DOI
Venue
2022
10.3390/systems10040086
SYSTEMS
Keywords
DocType
Volume
teaching model evaluation, heterogeneous information, economic statistics, social network analysis, multi-attribute decision making
Journal
10
Issue
ISSN
Citations 
4
2079-8954
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Weihua Su1233.06
Le Zhang226832.16
Chonghui Zhang300.34
Shouzhen Zeng401.35
Wangxiu Liu500.34