Multi-scenario application of Chatgpt-based language modeling for empowering English language teaching and learning

IF 4.7 3区材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-01-01 DOI:10.2478/amns-2024-0790

Hui Sun

引用次数: 0

Abstract

This paper discusses the multi-scenario application of ChatGPT-based language modeling in English language teaching, and empirical experiments are conducted to support the research findings. The study includes constructing and analyzing English composition scoring and similarity detection models. The BERT-BiLSTM algorithm was utilized and compared to the Word2Vec-BiLSTM model. The BERT-BiLSTM-based English composition scoring model has a high correlation and consistency with the original scores, with an average correlation of 0.72 and a consistency of 82%. Conversely, the Word2Vec-BiLSTM model has a lesser correlation and consistency. We created a model and used different K values for the experiment to detect English composition similarity. The correctness, recall, and F1 measures were higher at a K value 200, with F1 values fluctuating between 89.35% and 95.14%. These support the high accuracy and efficiency of ChatGPT-based language modeling in English language teaching.

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基于 Chatgpt 的语言建模在英语教学中的多场景应用

本文讨论了基于 ChatGPT 的语言建模在英语教学中的多场景应用，并进行了实证实验以支持研究成果。研究内容包括构建和分析英语作文评分和相似性检测模型。研究采用了 BERT-BiLSTM 算法，并与 Word2Vec-BiLSTM 模型进行了比较。基于 BERT-BiLSTM 的英语作文评分模型与原始评分具有较高的相关性和一致性，平均相关性为 0.72，一致性为 82%。相反，Word2Vec-BiLSTM 模型的相关性和一致性较低。我们创建了一个模型，并在实验中使用不同的 K 值来检测英语作文的相似性。在 K 值为 200 时，正确率、召回率和 F1 指标都较高，F1 值在 89.35% 和 95.14% 之间波动。这些都证明了基于 ChatGPT 的语言建模在英语教学中的高准确性和高效性。

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

ACS Applied Electronic Materials Multiple-

CiteScore

7.20

自引率

4.30%

发文量

567

期刊介绍： ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric. Indexed/Abstracted： Web of Science SCIE Scopus CAS INSPEC Portico

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