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Xinming Chen; Ziqian Zhou; Malila Prado – International Journal of Assessment Tools in Education, 2025
This study explores the efficacy of ChatGPT-3.5, an AI chatbot, used as an Automatic Essay Scoring (AES) system and feedback provider for IELTS essay preparation. It investigates the alignment between scores given by ChatGPT-3.5 and those assigned by official IELTS examiners to establish its reliability as an AES. It also identifies the strategies…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Kornwipa Poonpon; Paiboon Manorom; Wirapong Chansanam – Contemporary Educational Technology, 2023
Automated essay scoring (AES) has become a valuable tool in educational settings, providing efficient and objective evaluations of student essays. However, the majority of AES systems have primarily focused on native English speakers, leaving a critical gap in the evaluation of non-native speakers' writing skills. This research addresses this gap…
Descriptors: Automation, Essays, Scoring, English (Second Language)
Fu, Shixuan; Gu, Huimin; Yang, Bo – British Journal of Educational Technology, 2020
Traditional educational giants and natural language processing companies have launched several artificial intelligence (AI)-enabled digital learning applications to facilitate language learning. One typical application of AI in digital language education is the automatic scoring application that provides feedback on pronunciation repeat outcomes.…
Descriptors: Affordances, Artificial Intelligence, Computer Assisted Testing, Scoring
Biju Theruvil Sayed; Zein Bassam Bani Younes; Ahmad Alkhayyat; Iroda Adhamova; Habesha Teferi – Language Testing in Asia, 2024
There has been a surge in employing artificial intelligence (AI) in all areas of language pedagogy, not the least among them language testing and assessment. This study investigated the effects of AI-powered tools on English as a Foreign Language (EFL) learners' speaking skills, psychological well-being, autonomy, and academic buoyancy. Using a…
Descriptors: Artificial Intelligence, Language Tests, Success, Speech Skills
Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning
Sari, Elif; Han, Turgay – Reading Matrix: An International Online Journal, 2021
Providing both effective feedback applications and reliable assessment practices are two central issues in ESL/EFL writing instruction contexts. Giving individual feedback is very difficult in crowded classes as it requires a great amount of time and effort for instructors. Moreover, instructors likely employ inconsistent assessment procedures,…
Descriptors: Automation, Writing Evaluation, Artificial Intelligence, Natural Language Processing
Park, Kwanghyun – Language Assessment Quarterly, 2014
This article outlines the current state of and recent developments in the use of corpora for language assessment and considers future directions with a special focus on computational methodology. Because corpora began to make inroads into language assessment in the 1990s, test developers have increasingly used them as a reference resource to…
Descriptors: Language Tests, Computational Linguistics, Natural Language Processing, Scoring
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
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis