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Nicklin, Christopher; Vitta, Joseph P. – Language Testing, 2022
Instrument measurement conducted with Rasch analysis is a common process in language assessment research. A recent systematic review of 215 studies involving Rasch analysis in language testing and applied linguistics research reported that 23 different software packages had been utilized. However, none of the analyses were conducted with one of…
Descriptors: Programming Languages, Vocabulary Development, Language Tests, Computer Software
Taichi Yamashita – Language Testing, 2025
With the rapid development of generative artificial intelligence (AI) frameworks (e.g., the generative pre-trained transformer [GPT]), a growing number of researchers have started to explore its potential as an automated essay scoring (AES) system. While previous studies have investigated the alignment between human ratings and GPT ratings, few…
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Second Language Instruction
J. Dylan Burton – Language Testing, 2024
Nonverbal behavior can impact language proficiency scores in speaking tests, but there is little empirical information of the size or consistency of its effects or whether language proficiency may be a moderating variable. In this study, 100 novice raters watched and scored 30 recordings of test takers taking an international, high stakes…
Descriptors: Nonverbal Ability, Language Fluency, Second Language Learning, Language Proficiency
Tajeddin, Zia; Khatib, Mohammad; Mahdavi, Mohsen – Language Testing, 2022
Critical language assessment (CLA) has been addressed in numerous studies. However, the majority of the studies have overlooked the need for a practical framework to measure the CLA dimension of teachers' language assessment literacy (LAL). This gap prompted us to develop and validate a critical language assessment literacy (CLAL) scale to further…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Language Tests
Chen, Fang; Chalhoub-Deville, Micheline – Language Testing, 2014
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Descriptors: Regression (Statistics), Language Tests, Language Proficiency, Mathematics Achievement
Bridgeman, Brent; Powers, Donald; Stone, Elizabeth; Mollaun, Pamela – Language Testing, 2012
Scores assigned by trained raters and by an automated scoring system (SpeechRater[TM]) on the speaking section of the TOEFL iBT[TM] were validated against a communicative competence criterion. Specifically, a sample of 555 undergraduate students listened to speech samples from 184 examinees who took the Test of English as a Foreign Language…
Descriptors: Undergraduate Students, Speech Communication, Rating Scales, Scoring
Enright, Mary K.; Quinlan, Thomas – Language Testing, 2010
E-rater[R] is an automated essay scoring system that uses natural language processing techniques to extract features from essays and to model statistically human holistic ratings. Educational Testing Service has investigated the use of e-rater, in conjunction with human ratings, to score one of the two writing tasks on the TOEFL-iBT[R] writing…
Descriptors: Second Language Learning, Scoring, Essays, Language Processing
Chodorow, Martin; Gamon, Michael; Tetreault, Joel – Language Testing, 2010
In this paper, we describe and evaluate two state-of-the-art systems for identifying and correcting writing errors involving English articles and prepositions. Criterion[superscript SM], developed by Educational Testing Service, and "ESL Assistant", developed by Microsoft Research, both use machine learning techniques to build models of article…
Descriptors: Grammar, Feedback (Response), Form Classes (Languages), Second Language Learning