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Download full textOsama Koraishi – Language Teaching Research Quarterly, 2024
This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Artificial Intelligence
Xiaoling Bai; Nur Rasyidah Mohd Nordin – Eurasian Journal of Applied Linguistics, 2025
A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…
Descriptors: Artificial Intelligence, Feedback (Response), Evaluators, Writing Skills
Direct linkMoussalli, Souheila; Cardoso, Walcir – Computer Assisted Language Learning, 2020
Second/foreign language (L2) classrooms do not always provide opportunities for input and output practice [Lightbown, P. M. (2000). Classroom SLA research and second language teaching. Applied Linguistics, 21(4), 431-462]. The use of smart speakers such as Amazon Echo and its associated voice-controlled intelligent personal assistant (IPA) Alexa…
Descriptors: Artificial Intelligence, Pronunciation, Native Language, Listening Comprehension
Blanchard, Daniel; Tetreault, Joel; Higgins, Derrick; Cahill, Aoife; Chodorow, Martin – ETS Research Report Series, 2013
This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.
Descriptors: Language Tests, Second Language Learning, English (Second Language), Writing Tests
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
