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Direct linkShin, Jinnie; Gierl, Mark J. – Language Testing, 2021
Automated essay scoring (AES) has emerged as a secondary or as a sole marker for many high-stakes educational assessments, in native and non-native testing, owing to remarkable advances in feature engineering using natural language processing, machine learning, and deep-neural algorithms. The purpose of this study is to compare the effectiveness…
Descriptors: Scoring, Essays, Writing Evaluation, 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
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
Franco, Horacio; Bratt, Harry; Rossier, Romain; Rao Gadde, Venkata; Shriberg, Elizabeth; Abrash, Victor; Precoda, Kristin – Language Testing, 2010
SRI International's EduSpeak[R] system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to…
Descriptors: Feedback (Response), Sentences, Oral Language, Predictor Variables
