Fuzzy logic-based multilevel assessment model for education quality with dynamic learning planning approach

In order to solve the problem of vagueness and uncertainty, which is difficult to deal with in traditional education assessment, this paper introduces the theory of fuzzy matrix logic, and constructs a multilevel assessment model of education quality by means of the affiliation function and multilevel weight allocation.Through fuzzy reasoning and cognitive estimation techniques, combined with knowledge graph visualization, the cognitive level of learners is accurately estimated to achieve personalized learning resource recommendation.The quality assessment of physical education teaching in colleges and universities is taken as an example to verify the application value of the model.The constructed PE teaching quality evaluation index system contains 3 level 1 indicators, 11 level 2 indicators, and 38 level 3 indicators.The initial index scoring result of the PE classroom by 5 raters is an average score of 100.8, which is 89.2 points different from the full average score.The weights of the indicators within the 3 levels do not differ much.Students' levels of knowledge of the 6 initial physical education concepts ranged from 0.53 to 0.86 points.The maximum inter-conceptual influence strength was 0.86 and the minimum was 0.18.After the interference of the resource recommendation, the cognitive level increased to between 0.67-0.98points.The maximum inter-conceptual influence intensity reaches 1.The Sig value is greater than 0.05, and the results of the model calculations have reliability and can be used for education quality assessment and dynamic learning planning method improvement.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127a-394
Citations
1
Primary Topic
Educational Technology and Assessment
Type
article
Field-Weighted Citation Impact
3.25
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article

Fuzzy logic-based multilevel assessment model for education quality with dynamic learning planning approach

1 citations
Journal of Combinatorial Mathematics and Combinatorial Computing
Educational Technology and Assessment
3.25
article

Fuzzy logic-based multilevel assessment model for education quality with dynamic learning planning approach

article en
1 citations

Abstract

In order to solve the problem of vagueness and uncertainty, which is difficult to deal with in traditional education assessment, this paper introduces the theory of fuzzy matrix logic, and constructs a multilevel assessment model of education quality by means of the affiliation function and multilevel weight allocation.Through fuzzy reasoning and cognitive estimation techniques, combined with knowledge graph visualization, the cognitive level of learners is accurately estimated to achieve personalized learning resource recommendation.The quality assessment of physical education teaching in colleges and universities is taken as an example to verify the application value of the model.The constructed PE teaching quality evaluation index system contains 3 level 1 indicators, 11 level 2 indicators, and 38 level 3 indicators.The initial index scoring result of the PE classroom by 5 raters is an average score of 100.8, which is 89.2 points different from the full average score.The weights of the indicators within the 3 levels do not differ much.Students' levels of knowledge of the 6 initial physical education concepts ranged from 0.53 to 0.86 points.The maximum inter-conceptual influence strength was 0.86 and the minimum was 0.18.After the interference of the resource recommendation, the cognitive level increased to between 0.67-0.98points.The maximum inter-conceptual influence intensity reaches 1.The Sig value is greater than 0.05, and the results of the model calculations have reliability and can be used for education quality assessment and dynamic learning planning method improvement.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Openalex Percentile: Top 10%
Educational Technology and Assessment
3.25
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