Application Entropy Weight and TOPSIS Method in English Teaching Quality Evaluation of "Smart Classroom"
DOI:
https://doi.org/10.4108/eetsis.4218Keywords:
smart classroom, entropy weight, TOPSIS method, English teaching quality, optimization and improvementAbstract
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.
References
Bruya B, Ardelt M. Wisdom can be taught: a proof-of-concept study for fostering wisdom in the classroom[J]. Learning and Instruction, 2018, 58: 106-114.
Bruya B, Ardelt M. Fostering wisdom in the classroom, part 1: A general theory of wisdom pedagogy[J]. I was teaching Philosophy, 2018, 41(3): 239-253.
ZHOU Lei, LUO Hao, KWONG Xiangjun. Exploration of intelligent teaching mode for international students under the new crown epidemic - taking university physics experiment as an example[J]. University Physics, 2023, 42(05): 41.
WU Xiaoru, LIU Bangqi, YUAN Tingting. Next-generation smart classroom: concept, platform, and architecture[J]. China Electrified Education, 2019 (3): 81-88.
Zhou B. Smart classroom and multimedia network teaching platform application in college physical education teaching[J]. International Journal of Smart Home, 2016, 10(10): 145-156.
Nai R. The design of intelligent classroom for modern college English teaching under Internet of Things[J]. Plos one, 2022, 17(2): e0264176.
Zhang M, Li X. Design of Innovative Classroom System Based on Internet of Things Technology and Intelligent Classroom [J]. Mobile Information Systems, 2021, 2021: 1-9.
Zhang, Xiaohua, and Lin Chen. "College English smart classroom teaching model based on artificial intelligence technology in mobile information systems." Mobile Information Systems 2021 (2021): 1-12.
Saini, Mukesh Kumar, and Neeraj Goel. "How smart are smart classrooms? A review of intelligent classroom technologies. "ACM Computing Surveys (CSUR) 52.6 ( 2019): 1-28.
Lu, K., Yang, H. H., Shi, Y., & Wang, X. (2021). Examining the key influencing factors on college students' higher-order thinking skills in the intelligent classroom environment. International Journal of Educational Technology in Higher Education, 18, 1-13.
Liu, Li, Yongchao Wang, and Chizhu Ma. "The Cultivating Strategies of Pre-Service Teachers' Informatization Teaching Ability Oriented to Wisdom Generation." International Journal of Emerging Technologies in Learning (iJET) 16.6 (2021): 57-71.
Tong, Yinping. "A Study on the Construction and Evaluation of College English Wisdom Classroom in the "Internet Plus" Era." 8th International Conference on Education, Language, Art and Inter-cultural Communication (ICELAIC 2021). Atlantis Press, 2022.
Ren Yuanfang. Research on the Evaluation System of Teaching Effect of Smart Classroom under the Background of Big Data[J]. Journal of Higher Education, 2023, 9(25):91-94.DOI:10.19980/j.CN23-1593/G4.2023.25.023.
Zhan, Z., Wu, Q., Lin, Z., & Cai, J. (2021). Innovative classroom environments affect teacher-student interaction: Evidence from a behavioral sequence analysis. Australasian Journal of Educational Technology, 37(2), 96-109.
Kaur, Avneet, Munish Bhatia, and Giovanni Stea. "A survey of smart classroom literature." Education Sciences 12.2 (2022): 86.
Zhu, Yuxin, Dazuo Tian, and Feng Yan. "Effectiveness of entropy weight method in decision-making." Mathematical Problems in Engineering 2020 (2020): 1 -5.
Cong, Peijiang, Wang, Liang, Yin, Zhigang, Zhang, Bo & Li, Yanchun. (2023). Determination of Disease Risk Levels of Earth and Rock Dams Based on Combinatorial Empowerment and Topologizable Theory. Journal of Water Resources and Construction Engineering (02), 36-42.
Wang, T.-D., He, Z.-R., Shan, X.-F., Liu, G., Deng, Q.-L. & Ren, Z.-G. (2023). Evaluation and analysis of photovoltaic solar thermal cooling system based on entropy weight-TOPSIS. Journal of Solar Energy (09), 229-235. doi:10.19912/j.0254-0096.tynxb.2022-0676.
Chakraborty, Subrata. "TOPSIS and Modified TOPSIS: A comparative analysis." Decision Analytics Journal 2 (2022): 100021.
Chen, Pengyu. "Effects of the entropy weight on TOPSIS." Expert Systems with Applications 168 (2021): 114186.
Salih, M. M., Zaidan, B. B., Zaidan, A. A., & Ahmed, M. A. (2019). Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017. Computers & Operations Research, 104, 207-227.
Li, Z., Luo, Z., Wang, Y., Fan, G., & Zhang, J. (2022). The suitability evaluation system for the shallow geothermal energy implementation in the region by Entropy Weight Method and TOPSIS method. Renewable Energy Renewable Energy, 184, 564-576.
Wu, H. W., Li, E. Q., Sun, Y. Y., & Dong, B. T. (2021). Research on the operation safety evaluation of urban rail stations based on the improved TOPSIS and entropy weight methods. Journal of Rail Transport Planning & Management, 20, 100262.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Qingqing Chen
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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.