A shortcut in language testing: Predicting the score for paper-based TOEFL based on one sub-score

Pub Date : 2021-10-31 DOI:10.26858/IJOLE.V5I3.16200
Samsul Anwar, Faisal Mustafa
{"title":"A shortcut in language testing: Predicting the score for paper-based TOEFL based on one sub-score","authors":"Samsul Anwar, Faisal Mustafa","doi":"10.26858/IJOLE.V5I3.16200","DOIUrl":null,"url":null,"abstract":"Using standardized tests such as paper-based TOEFL with three subtests for classroom assessment is restricted by the length of the test, which is usually longer than the class duration. Therefore, it is significant to be able to predict other subtests by conducting only one subtest. Therefore, the current study aimed to calculate prediction coefficients, enabling teachers to predict scores in paper-based TOEFL by conducting only one subtest. The data to create the prediction models were obtained from 2,030 scores of Institutional TOEFL, i.e. paper-based TOEFL without writing subtest. The prediction coefficient was calculated by using linear regression analysis. The result shows that the listening comprehension sub-score predicts the TOEFL score more accurately (MSE of 520) than other sub-scores (MSE of 553 and 587). The intercept for listening comprehension sub-score was 373.07, 357.14 for structure & written expression, and 364.19 for reading comprehension. In addition, the slope for each sub-score was 4.07, 5.96, and 4.63, respectively. Therefore, a listening test should be used in predicting the overall TOEFL scores for an accurate prediction.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26858/IJOLE.V5I3.16200","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Using standardized tests such as paper-based TOEFL with three subtests for classroom assessment is restricted by the length of the test, which is usually longer than the class duration. Therefore, it is significant to be able to predict other subtests by conducting only one subtest. Therefore, the current study aimed to calculate prediction coefficients, enabling teachers to predict scores in paper-based TOEFL by conducting only one subtest. The data to create the prediction models were obtained from 2,030 scores of Institutional TOEFL, i.e. paper-based TOEFL without writing subtest. The prediction coefficient was calculated by using linear regression analysis. The result shows that the listening comprehension sub-score predicts the TOEFL score more accurately (MSE of 520) than other sub-scores (MSE of 553 and 587). The intercept for listening comprehension sub-score was 373.07, 357.14 for structure & written expression, and 364.19 for reading comprehension. In addition, the slope for each sub-score was 4.07, 5.96, and 4.63, respectively. Therefore, a listening test should be used in predicting the overall TOEFL scores for an accurate prediction.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
语言测试的捷径:根据一项分数预测托福笔试分数
使用标准化考试,如托福纸考和三个子测试进行课堂评估,受到考试长度的限制,通常长于课堂时间。因此,能够通过仅进行一个子测试来预测其他子测试是有意义的。因此,本研究旨在计算预测系数,使教师仅通过一个子测试就能预测托福笔试成绩。建立预测模型的数据来自机构托福(Institutional TOEFL)的2030份成绩,即不含写作子测试的纸笔托福。采用线性回归分析计算预测系数。结果表明,听力分对托福成绩的预测准确率(MSE为520)高于其他分(MSE分别为553和587)。听力分截距为373.07分,结构与书面表达分截距为357.14分,阅读分截距为364.19分。各分值的斜率分别为4.07、5.96和4.63。因此,听力测试应该用于预测托福的整体成绩,以准确预测。
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
×
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