基于语料库数据的英语教学模糊决策支持系统

IF 5 3区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Egyptian Informatics Journal Pub Date : 2025-01-26 DOI:10.1016/j.eij.2025.100612

Meilin Huang

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引用次数: 0

摘要

过去的语料库数据和新手的观察对提高高中英语教学的熟练程度是有用的。优化方法通过从语料库数据中获得的微调过程来支持这种能力。为此，本文介绍了一种基于模糊决策优化的以进步为中心的教学系统。该系统的重点是识别和提供解决方案的词汇放置错误。注重英语教学的进步，追求高质量的输出，词汇安排，减少错误。模糊决策系统从词汇教学中可能的词汇位置中识别出最大精度的输出。在这个决策过程中，通过个性化的培训建议来调整针对特定输出的教学效率。模糊输出作为最大精度输出的基准，为进一步的教学提供参考。因此，通过纠正之前语料库输入中的错误，可以实现英语词汇教学的持续发展。

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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Fuzzy decision support system for english language teaching with corpus data

Corpus data from the past and novice observations are useful in improving the adeptness of English language teaching in high schools. Optimization methods support this adeptness through fine-tuning processes acquired from the corpus data. Hence, this article introduces a Progression-focused Teaching System (PTS) optimized by Fuzzy Decision (FD). This system focuses on identifying and providing solutions for lexical placement errors. Focusing on the progression of English teaching with high-quality outputs, lexical arrangement, and error reduction is pursued. The fuzzy decision system identifies a maximum precision output from the possible lexical placement in teaching vocabulary. In this decision process, the teaching efficiency towards the specific output is tuned through personalized training recommendations. The fuzzy output is used to benchmark the maximum precision output for further teaching references. Therefore, a consistent progression in teaching English vocabulary is attained by rectifying the errors in the previous corpus inputs.

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来源期刊

Egyptian Informatics Journal Decision Sciences-Management Science and Operations Research

CiteScore

11.10

自引率

1.90%

发文量

审稿时长

110 days

期刊介绍： The Egyptian Informatics Journal is published by the Faculty of Computers and Artificial Intelligence, Cairo University. This Journal provides a forum for the state-of-the-art research and development in the fields of computing, including computer sciences, information technologies, information systems, operations research and decision support. Innovative and not-previously-published work in subjects covered by the Journal is encouraged to be submitted, whether from academic, research or commercial sources.