About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
sis 24(6):

Research Article

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

Download86 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetsis.5175,
        author={Zhiwei Zhu},
        title={A Self-learning Ability Assessment Method Based on Weight-Optimised Dfferential Evolutionary Algorithm},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={6},
        publisher={EAI},
        journal_a={SIS},
        year={2024},
        month={4},
        keywords={college students' independent learning ability cultivation, experiential teaching, differential evolutionary algorithm, weight optimisation},
        doi={10.4108/eetsis.5175}
    }
    
  • Zhiwei Zhu
    Year: 2024
    A Self-learning Ability Assessment Method Based on Weight-Optimised Dfferential Evolutionary Algorithm
    SIS
    EAI
    DOI: 10.4108/eetsis.5175
Zhiwei Zhu1,*
  • 1: Anhui Jianzhu University
*Contact email: zzw@ahjzu.edu.cn

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.

Keywords
college students' independent learning ability cultivation, experiential teaching, differential evolutionary algorithm, weight optimisation
Received
2024-02-22
Accepted
2024-03-29
Published
2024-04-08
Publisher
EAI
http://dx.doi.org/10.4108/eetsis.5175

Copyright © 2024 Z. Zhu et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL