A Self-learning Ability Assessment Method Based on Weight-Optimised Dfferential Evolutionary Algorithm

Zhiwei Zhu

doi:10.4108/eetsis.5175

Authors

Zhiwei Zhu Anhui Jianzhu University

DOI:

https://doi.org/10.4108/eetsis.5175

Keywords:

college students' independent learning ability cultivation, experiential teaching, differential evolutionary algorithm, weight optimisation

Abstract

INTRODUCTION: The research on the method of cultivating college students' autonomous ability based on experiential teaching is conducive to college students' change of learning mode and learning thinking, improving the utilisation rate of educational resources, as well as the reform of education.

OBJECTIVES: Addressing the current problems of unquantified analyses, lack of breadth, and insufficient development strategies in the methods used to develop independent learning skills in university students.

METHODS: This paper proposes an intelligent optimisation algorithm for the cultivation of college students' independent learning ability in experiential teaching. Firstly, the characteristics and elements of college students' independent learning are analysed, while the strategy of cultivating college students' independent learning ability in experiential teaching is proposed; then, the weight optimization method of cultivating college students' independent learning ability based on experiential teaching is proposed by using the improved intelligent optimization algorithm; finally, the validity and feasibility of the proposed method are verified through experimental analysis.

RESULTS: The results show that the proposed method has a wider range of culture effects.

CONCLUSION: Addressing the problem of poor generalisation in the development of independent learning skills among university students.

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