sis 24(2):

Research Article

Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges

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  • @ARTICLE{10.4108/eetsis.4493,
        author={Fang Nan and Yanan Li and Jing Zhang and Xuesong Yin and Xintong Cui},
        title={Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={2},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={11},
        keywords={},
        doi={10.4108/eetsis.4493}
    }
    
  • Fang Nan
    Yanan Li
    Jing Zhang
    Xuesong Yin
    Xintong Cui
    Year: 2023
    Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges
    SIS
    EAI
    DOI: 10.4108/eetsis.4493
Fang Nan1, Yanan Li1,*, Jing Zhang2, Xuesong Yin2, Xintong Cui2
  • 1: Qinggong College North China University Of Science And Technology, Tangshan 063000, Hebei, China
  • 2: Qinggong College North China University of Science and Technology, Tangshan 063000, Hebei, China
*Contact email: liyanan312@163.com

Abstract

INTRODUCTION: The quality assessment technology of distance education in colleges and universities, as the critical technology for identifying the quality of distance education in colleges and universities, is conducive to the improvement of the quality of distance teaching and the progress of the existing means and methods of distance education, which makes the means of distance teaching in colleges and universities rich in science. OBJECTIVES: Aiming at the evaluation methods of higher education institutions, there are problems such as insufficient objectivity and comprehensiveness of the evaluation system, single process, and inadequate quantitative analysis. METHODS:Proposes a decision tree and intelligent optimization algorithm for the college distance teaching quality assessment method. Firstly, the kernel principal component analysis method is used to carry out dimensionality reduction analysis on the index system of college distance teaching quality assessment; then, the decision tree parameters are optimized through the marine predator algorithm to construct a college distance teaching quality assessment model; finally, the robustness and efficiency of the proposed method are verified through simulation experimental analysis. RESULTS: The results show that the proposed method improves the accuracy of the assessment model. CONCLUSION: The problem of insufficient objective and scientific evaluation and low precision of distance teaching quality assessment methods in colleges and universities is solved.