大数据分析下的英语教学能力评价模型设计

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC Journal of Electrical Systems Pub Date : 2024-05-08 DOI:10.52783/jes.3527
Liqin He, Chaojie Hu, Ling Nie, Chunxia Li, Honglian Liu
{"title":"大数据分析下的英语教学能力评价模型设计","authors":"Liqin He, Chaojie Hu, Ling Nie, Chunxia Li, Honglian Liu","doi":"10.52783/jes.3527","DOIUrl":null,"url":null,"abstract":"Traditional methods of evaluating English teaching capability involve a considerable degree of subjective human judgment, leading to classification errors in big data information. To improve the comprehensiveness and accuracy of English teaching capability evaluation, it is necessary to construct a corresponding evaluation model based on big data. This paper employs the k-means clustering analysis algorithm to devise a system structure design for English teaching capability, applies constrained parameter big data structure analysis, and proposes utilizing a quantitative recursive approach to evaluate the teaching capabilities of big data information models based on cluster analysis. The simulation results demonstrate that the method designed in this paper can enhance the comprehensiveness and precision of English teaching capability evaluation, thereby contributing to the advancement of information fusion analysis capabilities.","PeriodicalId":44451,"journal":{"name":"Journal of Electrical Systems","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of English Teaching Capability Evaluation Model Under Big Data Analysis\",\"authors\":\"Liqin He, Chaojie Hu, Ling Nie, Chunxia Li, Honglian Liu\",\"doi\":\"10.52783/jes.3527\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional methods of evaluating English teaching capability involve a considerable degree of subjective human judgment, leading to classification errors in big data information. To improve the comprehensiveness and accuracy of English teaching capability evaluation, it is necessary to construct a corresponding evaluation model based on big data. This paper employs the k-means clustering analysis algorithm to devise a system structure design for English teaching capability, applies constrained parameter big data structure analysis, and proposes utilizing a quantitative recursive approach to evaluate the teaching capabilities of big data information models based on cluster analysis. The simulation results demonstrate that the method designed in this paper can enhance the comprehensiveness and precision of English teaching capability evaluation, thereby contributing to the advancement of information fusion analysis capabilities.\",\"PeriodicalId\":44451,\"journal\":{\"name\":\"Journal of Electrical Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2024-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Electrical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52783/jes.3527\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Electrical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52783/jes.3527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

传统的英语教学能力评价方法涉及相当程度的人为主观判断,导致大数据信息的分类误差。为了提高英语教学能力评价的全面性和准确性,有必要构建相应的基于大数据的评价模型。本文采用k-means聚类分析算法设计英语教学能力的系统结构设计,应用约束参数大数据结构分析,提出利用定量递归的方法评价基于聚类分析的大数据信息模型的教学能力。仿真结果表明,本文设计的方法可以提高英语教学能力评价的全面性和精确性,从而有助于提升信息融合分析能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Design of English Teaching Capability Evaluation Model Under Big Data Analysis
Traditional methods of evaluating English teaching capability involve a considerable degree of subjective human judgment, leading to classification errors in big data information. To improve the comprehensiveness and accuracy of English teaching capability evaluation, it is necessary to construct a corresponding evaluation model based on big data. This paper employs the k-means clustering analysis algorithm to devise a system structure design for English teaching capability, applies constrained parameter big data structure analysis, and proposes utilizing a quantitative recursive approach to evaluate the teaching capabilities of big data information models based on cluster analysis. The simulation results demonstrate that the method designed in this paper can enhance the comprehensiveness and precision of English teaching capability evaluation, thereby contributing to the advancement of information fusion analysis capabilities.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Electrical Systems
Journal of Electrical Systems ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
1.10
自引率
25.00%
发文量
0
审稿时长
10 weeks
期刊最新文献
Frequency Domain Backdoor Attacks for Visual Object Tracking Exploring Emotional Intelligence in Jordan’s Artificial Intelligence (AI) Healthcare Adoption: A UTAUT Framework Twitter Based Sentiment Analysis of Russia-Ukraine War Using Machine Learning Predictive Analytics and Machine Learning Applications in the USA for Sustainable Supply Chain Operations and Carbon Footprint Reduction Comparison of Control Strategies of Quasi Z-Source Inverter for Wind Power Generation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1