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Application of Multivariate Video Analysis in English Teaching Effect Evaluation Based on Computational Neural Model Simulation

Application of Multivariate Video Analysis in English Teaching Effect Evaluation Based on Computational Neural Model Simulation

Weiqiang Wang, Haiyan Tian
Copyright: © 2023 |Volume: 18 |Issue: 2 |Pages: 16
ISSN: 1548-1093|EISSN: 1548-1107|EISBN13: 9781668494974|DOI: 10.4018/IJWLTT.319368
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MLA

Wang, Weiqiang, and Haiyan Tian. "Application of Multivariate Video Analysis in English Teaching Effect Evaluation Based on Computational Neural Model Simulation." IJWLTT vol.18, no.2 2023: pp.1-16. https://doi.org/10.4018/IJWLTT.319368

APA

Wang, W. & Tian, H. (2023). Application of Multivariate Video Analysis in English Teaching Effect Evaluation Based on Computational Neural Model Simulation. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 18(2), 1-16. https://doi.org/10.4018/IJWLTT.319368

Chicago

Wang, Weiqiang, and Haiyan Tian. "Application of Multivariate Video Analysis in English Teaching Effect Evaluation Based on Computational Neural Model Simulation," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) 18, no.2: 1-16. https://doi.org/10.4018/IJWLTT.319368

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Abstract

Video observation and content analysis are used to make a "quantitative-qualitative" analysis of English teachers' teaching behavior reflected in English classroom teaching videos, and to accurately describe, analyze, and summarize the characteristics of English teachers' teaching behavior from various aspects. Based on this, this study uses video analysis methods and NVivo 11 qualitative analysis tools to import quantitative data obtained from teaching video content into Excel tables for statistical analysis, objectively describe the rules and characteristics of junior high school English teachers' teaching effects, and then put forward suggestions to optimize teaching effects and strategies and suggestions to promote English classroom development. This paper establishes a video analysis and evaluation model. First, calculate the weights required by the model, then calculate the relationship matrix, and then calculate the second-level video analysis and evaluation. Using the second-level weight and relationship matrix, the teacher's evaluation value will be obtained.