Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions

Q1 Arts and Humanities Vysshee Obrazovanie v Rossii Pub Date : 2023-09-13 DOI:10.31992/0869-3617-2023-32-8-9-147-166
E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk
{"title":"Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions","authors":"E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk","doi":"10.31992/0869-3617-2023-32-8-9-147-166","DOIUrl":null,"url":null,"abstract":"The article presents the results of approbation of the intellectual system for testing general language competences (ISTOK) developed by testologists, linguists, specialists in methodology of teaching foreign languages and in artificial intelligence. This system includes a range of tests assessing language ability at levels from A2 to C1 of the Common European Framework of Reference (CEFR), as well as an adaptive placement test. All test materials are calibrated according to the CEFR. ISTOK is an adaptive testing system deployed through neural network solutions and providing assessment of receptive and productive language skills (reading, listening, speaking and writing) by using artificial intelligence and/or neurolinguistic models. The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. The results of various testing cohorts with the total number of test takers exceeding 5,000 demonstrated high reliability and objectified test validity. The new approach to language skills testing can be used for various purposes in higher education institutions, as well and to identify and/or confirm language proficiency of personnel in different organisations and businesses, while the principles of training and practical use of neurolinguistic models will find wide application in various fields of applied research.","PeriodicalId":37083,"journal":{"name":"Vysshee Obrazovanie v Rossii","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vysshee Obrazovanie v Rossii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31992/0869-3617-2023-32-8-9-147-166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
引用次数: 0

Abstract

The article presents the results of approbation of the intellectual system for testing general language competences (ISTOK) developed by testologists, linguists, specialists in methodology of teaching foreign languages and in artificial intelligence. This system includes a range of tests assessing language ability at levels from A2 to C1 of the Common European Framework of Reference (CEFR), as well as an adaptive placement test. All test materials are calibrated according to the CEFR. ISTOK is an adaptive testing system deployed through neural network solutions and providing assessment of receptive and productive language skills (reading, listening, speaking and writing) by using artificial intelligence and/or neurolinguistic models. The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. The results of various testing cohorts with the total number of test takers exceeding 5,000 demonstrated high reliability and objectified test validity. The new approach to language skills testing can be used for various purposes in higher education institutions, as well and to identify and/or confirm language proficiency of personnel in different organisations and businesses, while the principles of training and practical use of neurolinguistic models will find wide application in various fields of applied research.
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
基于神经网络解决方案的国家通用语言能力智能测试系统的发展与展望
本文介绍了由语言学家、语言学家、外语教学方法专家和人工智能专家开发的通用语言能力智力测试系统(ISTOK)的认可结果。该系统包括一系列评估语言能力的测试,从欧洲共同参考框架(CEFR)的A2到C1水平,以及适应性分班测试。所有测试材料均根据CEFR进行校准。ISTOK是一个通过神经网络解决方案部署的自适应测试系统,通过使用人工智能和/或神经语言学模型,对接受性和生产性语言技能(阅读、听力、口语和写作)进行评估。ISTOK的开发过程意味着,除了写作测试项目外,还包括将由专业评估人员标记的写作和口语作业数据库和生产技能评估标准整合在一起,以及在人工智能的帮助下识别各种类型错误的算法。在总人数超过5000人的多个测试队列中,测试结果具有较高的信度和客观效度。新的语言技能测试方法可用于高等教育机构的各种目的,也可用于识别和/或确认不同组织和企业人员的语言能力,而神经语言学模型的培训原则和实际应用将在各种应用研究领域得到广泛应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Vysshee Obrazovanie v Rossii
Vysshee Obrazovanie v Rossii Social Sciences-Sociology and Political Science
CiteScore
2.40
自引率
0.00%
发文量
101
期刊最新文献
Mechanisms for Activating the Personal Potential of Students in the Context of Digitalization of University Education Russia’s State Policy on the Development of Science at Universities: Lessons from the 90s Image of Higher Educational Institutions: Features of Perception by Graduating Class Students The ADDIE Model in Instructional Design: NUST MISIS Case Study Online Education after the Pandemic: Student Problems and Opportunities Research Using Big Data Tools
×
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