sis 23(1):

Research Article

Application Entropy Weight and TOPSIS Method in English Teaching Quality Evaluation of "Smart Classroom"

Download306 downloads
  • @ARTICLE{10.4108/eetsis.4218,
        author={Qingqing Chen},
        title={Application Entropy Weight and TOPSIS Method in English Teaching Quality Evaluation of "Smart Classroom"},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={1},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={10},
        keywords={smart classroom, entropy weight, TOPSIS method, English teaching quality, optimization and improvement},
        doi={10.4108/eetsis.4218}
    }
    
  • Qingqing Chen
    Year: 2023
    Application Entropy Weight and TOPSIS Method in English Teaching Quality Evaluation of "Smart Classroom"
    SIS
    EAI
    DOI: 10.4108/eetsis.4218
Qingqing Chen1,*
  • 1: Zhengzhou University of Industrial Technology
*Contact email: happyjoan1008@126.com

Abstract

INTRODUCTION: Based on TOPSIS (Technological Ordering of Superiority and Inferiority) and entropy weight method, it aims to evaluate the quality of intelligent classroom English teaching. The brilliant classroom teaching model has attracted much attention for its highly interactive, personalized, and real-time feedback features; however, how to accurately evaluate the quality of intelligent classroom teaching remains a challenge. OBJECTIVES: To combine the TOPSIS and entropy weight methods in practical application and consider the index ordering and weight calculation comprehensively to arrive at the quality evaluation results of each brilliant classroom teaching. METHODS: The TOPSIS method is first used to rank multiple indicators of teaching quality to determine the optimal teaching quality. The TOPSIS method can consider the interrelationships between the hands and find the solution closest to the positive ideal solution and farthest away from the negative perfect solution by calculating each indicator's positive and negative perfect solutions. Then, the weight of each hand is calculated by combining the entropy weight method. The entropy weight method can consider the indicators' information and differences and measure the degree of their contribution to the evaluation results by calculating the entropy value of the hands. RESULTS: The results show that the method can comprehensively consider the correlation and weight of multiple indicators, provide teachers and educational administrators with accurate teaching quality evaluation and improvement suggestions, and thus promote the optimization and enhancement of innovative classroom teaching. CONCLUSION: By analyzing the actual smart classroom teaching data, the Author found that the method can effectively evaluate the quality of intelligent classroom teaching and provide valuable guidance for English teaching improvement.