Method of adaptive learning feature model fusion and verification based on metamodels

Chenyu Wang; Yi Zhu; Zixin Wu; Guosheng Hao

doi:10.1117/12.3034756

11 July 2024 Method of adaptive learning feature model fusion and verification based on metamodels

Chenyu Wang, Yi Zhu, Zixin Wu, Guosheng Hao

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132102F (2024) https://doi.org/10.1117/12.3034756
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

As the advancement of computer technique and artificial intelligence technology, education based on computer technology has become a hot topic, and the wave of educational informatization is rising. Among them, adaptive learning has received widespread attention as a type of educational informatization technology. However, the current adaptive learning feature models use different semantics to describe each other, and the models lack meta model level explanations, resulting in a lack of further operability of the models and difficulty in integrating with each other. In order to solve these problems, our paper proposes a fusion and verification method for learning feature adaptive models based on meta models. Above all, an adaptive learning feature meta model is proposed, which defines the construction rules of the adaptive learning feature model at meta model level, so that different models can be fused using the same set of semantic rules. Then, at the meta model level, transform the learning model into a requirement model. Finally, using formal methods, validate the fused feature model, which can make sure of the semantic consistency between the previous and subsequent models. This article demonstrates the entire process through a model fusion experiment. The experimental results indicate that this method is correct and feasible in promoting feature model fusion without adaptive learning.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chenyu Wang, Yi Zhu, Zixin Wu, and Guosheng Hao "Method of adaptive learning feature model fusion and verification based on metamodels", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132102F (11 July 2024); https://doi.org/10.1117/12.3034756

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KEYWORDS

Semantics

Feature fusion

Machine learning

Logic

Systems modeling

Data modeling

Modeling

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