Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization

Quantitative analysis of classroom teaching language traditionally relies on manual coding, presenting significant challenges such as complexity and labor-intensive workloads, which hinder its applicability to large-scale classroom evaluations. Rapid advancements in artificial intelligence technolog...

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Main Authors: FENG Xiumei, JIANG Yuchen, WANG Yiting
Format: Article
Language:zho
Published: Journal Press of Southwest University 2025-07-01
Series:Jiaoshi jiaoyu xuebao
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Online Access:https://xbgjxt.swu.edu.cn/article/doi/10.13718/j.cnki.jsjy.2025.04.006
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author FENG Xiumei
JIANG Yuchen
WANG Yiting
author_facet FENG Xiumei
JIANG Yuchen
WANG Yiting
author_sort FENG Xiumei
collection DOAJ
description Quantitative analysis of classroom teaching language traditionally relies on manual coding, presenting significant challenges such as complexity and labor-intensive workloads, which hinder its applicability to large-scale classroom evaluations. Rapid advancements in artificial intelligence technology have recently offered promising solutions to these issues. Therefore, this study aims to foster the development of high-quality pre-service teachers by providing a technical pathway and empirical evidence for intelligent classroom language evaluation from three key dimensions: effectiveness evaluation, practical application, and intelligent optimization. Initially, an encoding system specifically tailored to the instructional language characteristics of pre-service teachers was developed. Then, an automated encoding model was constructed and tested for feasibility and effectiveness in language coding tasks. Subsequently, this automated encoding model was applied to analyze instructional language differences between pre-service teachers' training videos and exemplary teaching videos, systematically identifying problems and proposing generalized optimization recommendations. Finally, an instructional language optimization assistant was preliminarily established using large language models, offering personalized language guidance to pre-service teachers based on identified optimization strategies. The findings demonstrate that artificial intelligence technologies effectively address the challenges of quantitative instructional language analysis and show significant potential in automation and personalized educational evaluation.
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spelling doaj-art-028374dbac0149c0b979cb3f5675fdd22025-08-20T03:49:50ZzhoJournal Press of Southwest UniversityJiaoshi jiaoyu xuebao2095-81292025-07-01124516110.13718/j.cnki.jsjy.2025.04.006jsjyxb-12-4-51Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and OptimizationFENG Xiumei0JIANG Yuchen1WANG Yiting2College of Physics Science and Technology, Central China Normal University, Wuhan 430079, ChinaCollege of Physics Science and Technology, Central China Normal University, Wuhan 430079, ChinaCollege of Physics Science and Technology, Central China Normal University, Wuhan 430079, ChinaQuantitative analysis of classroom teaching language traditionally relies on manual coding, presenting significant challenges such as complexity and labor-intensive workloads, which hinder its applicability to large-scale classroom evaluations. Rapid advancements in artificial intelligence technology have recently offered promising solutions to these issues. Therefore, this study aims to foster the development of high-quality pre-service teachers by providing a technical pathway and empirical evidence for intelligent classroom language evaluation from three key dimensions: effectiveness evaluation, practical application, and intelligent optimization. Initially, an encoding system specifically tailored to the instructional language characteristics of pre-service teachers was developed. Then, an automated encoding model was constructed and tested for feasibility and effectiveness in language coding tasks. Subsequently, this automated encoding model was applied to analyze instructional language differences between pre-service teachers' training videos and exemplary teaching videos, systematically identifying problems and proposing generalized optimization recommendations. Finally, an instructional language optimization assistant was preliminarily established using large language models, offering personalized language guidance to pre-service teachers based on identified optimization strategies. The findings demonstrate that artificial intelligence technologies effectively address the challenges of quantitative instructional language analysis and show significant potential in automation and personalized educational evaluation.https://xbgjxt.swu.edu.cn/article/doi/10.13718/j.cnki.jsjy.2025.04.006educational evaluationevaluation of classroom teaching languageartificial intelligenceautomation
spellingShingle FENG Xiumei
JIANG Yuchen
WANG Yiting
Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
Jiaoshi jiaoyu xuebao
educational evaluation
evaluation of classroom teaching language
artificial intelligence
automation
title Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
title_full Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
title_fullStr Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
title_full_unstemmed Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
title_short Intelligent Evaluation of Classroom Teaching Language: Effectiveness, Application, and Optimization
title_sort intelligent evaluation of classroom teaching language effectiveness application and optimization
topic educational evaluation
evaluation of classroom teaching language
artificial intelligence
automation
url https://xbgjxt.swu.edu.cn/article/doi/10.13718/j.cnki.jsjy.2025.04.006
work_keys_str_mv AT fengxiumei intelligentevaluationofclassroomteachinglanguageeffectivenessapplicationandoptimization
AT jiangyuchen intelligentevaluationofclassroomteachinglanguageeffectivenessapplicationandoptimization
AT wangyiting intelligentevaluationofclassroomteachinglanguageeffectivenessapplicationandoptimization