Construction of English teaching quality diagnosis and evaluation model combined with improved EM algorithm

Yi Zuo

doi:10.1117/12.2673535

22 May 2023 Construction of English teaching quality diagnosis and evaluation model combined with improved EM algorithm

Yi Zuo

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 126401L (2023) https://doi.org/10.1117/12.2673535
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

With the continuous improvement of teaching methods, people put forward higher requirements for the quality of English teaching. Traditional approaches for assessing instructional quality are less sensitive to the initial data in the evaluation process, and cannot achieve the optimal convergence effect. To better evaluate the level of instruction in English, the research uses the improved EM algorithm to create a diagnostic evaluation model for English teaching quality. The performance of the model is tested by using the English scores of college students. The outcomes demonstrate that the accuracy of enhanced model is 99%. The trained model is used for data testing, and the test error obtained is 0.8%. The error is 0.4% and 0.1% lower than EM model and FCM-EM model respectively. Therefore, the IFCM-EM evaluation method for teaching English proposed in the study has good accuracy and efficiency. It can effectively diagnose and evaluate the effectiveness of English instruction in schools, as well as offer assistance with improve English teaching evaluation methods and teaching levels.

Citation Download Citation

Yi Zuo "Construction of English teaching quality diagnosis and evaluation model combined with improved EM algorithm", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 126401L (22 May 2023); https://doi.org/10.1117/12.2673535

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