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

Q2 Social Sciences International Journal of Web-Based Learning and Teaching Technologies Pub Date : 2023-03-03 DOI:10.4018/ijwltt.319368

Weiqiang Wang, Haiyan Tian

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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.

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基于计算神经模型仿真的多元视频分析在英语教学效果评价中的应用

通过视频观察和内容分析，对英语课堂教学视频中所反映的英语教师的教学行为进行“定量-定性”分析，从各个方面对英语教师的教学行为特征进行准确的描述、分析和总结。基于此，本研究运用视频分析方法和NVivo 11定性分析工具，将教学视频内容获得的定量数据导入Excel表格进行统计分析，客观描述初中英语教师教学效果的规律和特点，进而提出优化教学效果的建议和促进英语课堂发展的策略建议。本文建立了一个视频分析与评价模型。首先计算模型所需的权重，然后计算关系矩阵，再计算二级视频分析评价。利用二级权重和关系矩阵，得到教师的评价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Web-Based Learning and Teaching Technologies Social Sciences-Education

CiteScore

2.40

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0.00%

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