Research on Teaching Evaluation Based on Multi-Granularity Rough Set with Confidential Dominance Relations
Year: 2024
Type: conference-paper
Abstract: The traditional teaching evaluation methods often rely on single indicators, and the factors reflecting the quality of teaching are not comprehensive enough. To address the subjectivity and uncertainty of evaluation values when independent experts from different fields participate in teaching evaluations, a teaching evaluation method based on confident dominance multi-granularity rough set theory is proposed. In the paper the optimistic and pessimistic upper and lower approximations of the confident dominance multi-granularity rough set model are studied from a multi-granularity perspective. By introducing the confidence degree of the order decision rule, "or" and "and" type order decision rules and their judgment theorems are given. Finally, the feasibility of the model is verified by a multi-expert participation teaching decision evaluation analysis, and several order decision rules are extended. Examples show that the multi-granularity rough set model can be applied to accurately evaluate the quality of course teaching, and has gained theoretical significance and practical value for the research on the evaluation method of university teaching quality.
Authors: Yumei Lin, Lianhua Fang
Institution: Quanzhou University of Information Engineering
Language: English
Topic: Rough Sets and Fuzzy Logic
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4410210708