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Danwei Cai; Ben Naismith; Maria Kostromitina; Zhongwei Teng; Kevin P. Yancey; Geoffrey T. LaFlair – Language Learning, 2025
Globalization and increases in the numbers of English language learners have led to a growing demand for English proficiency assessments of spoken language. In this paper, we describe the development of an automatic pronunciation scorer built on state-of-the-art deep neural network models. The model is trained on a bespoke human-rated dataset that…
Descriptors: Automation, Scoring, Pronunciation, Speech Tests
Erik Voss – Language Testing, 2025
An increasing number of language testing companies are developing and deploying deep learning-based automated essay scoring systems (AES) to replace traditional approaches that rely on handcrafted feature extraction. However, there is hesitation to accept neural network approaches to automated essay scoring because the features are automatically…
Descriptors: Artificial Intelligence, Automation, Scoring, English (Second Language)
Yoonseo Kim – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
This study explores the potential of OpenAI's ChatGPT-4 (gpt-4-0613) as an automated essay scoring (AES) tool in a trial involving 300 essays from an American university's academic English program placement test. Three prompting strategies (minimal/detailed rubric, require/not require rationale, and with/without scoring examples) were tested for…
Descriptors: Automation, Scoring, Artificial Intelligence, Placement Tests
Ikkyu Choi; Jiangang Hao; Chen Li; Michael Fauss; Jakub Novák – ETS Research Report Series, 2024
A frequently encountered security issue in writing tests is nonauthentic text submission: Test takers submit texts that are not their own but rather are copies of texts prepared by someone else. In this report, we propose AutoESD, a human-in-the-loop and automated system to detect nonauthentic texts for a large-scale writing tests, and report its…
Descriptors: Writing Tests, Automation, Cheating, Plagiarism
Somayeh Fathali; Fatemeh Mohajeri – Technology in Language Teaching & Learning, 2025
The International English Language Testing System (IELTS) is a high-stakes exam where Writing Task 2 significantly influences the overall scores, requiring reliable evaluation. While trained human raters perform this task, concerns about subjectivity and inconsistency have led to growing interest in artificial intelligence (AI)-based assessment…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Artificial Intelligence
Zhao, Ruibin; Zhuang, Yipeng; Zou, Di; Xie, Qin; Yu, Philip L. H. – Education and Information Technologies, 2023
Grading assignments is inherently subjective and time-consuming; automatic scoring tools can greatly reduce teacher workload and shorten the time needed for providing feedback to learners. The purpose of this paper is to propose a novel method for automatically scoring student responses to picture-cued writing tasks. As a popular paradigm for…
Descriptors: Artificial Intelligence, Automation, Scoring, Visual Aids
Dongkwang Shin; Jang Ho Lee – ELT Journal, 2024
Although automated item generation has gained a considerable amount of attention in a variety of fields, it is still a relatively new technology in ELT contexts. Therefore, the present article aims to provide an accessible introduction to this powerful resource for language teachers based on a review of the available research. Particularly, it…
Descriptors: Language Tests, Artificial Intelligence, Test Items, Automation
Ekaterina Voskoboinik; Anna von Zansen; Nhan Chi Phan; Yaroslav Getman; Tamás Grósz; Mikko Kurimo – Language Testing, 2025
Automated speaking assessment (ASA) of second language proficiency benefits both learners and educators. However, developing these systems for less commonly taught languages like Finnish and Finland Swedish is hindered by the need for large datasets with equal representation of all proficiency levels. Traditional machine learning algorithms used…
Descriptors: Second Languages, Language Tests, Speech Tests, Finno Ugric Languages
Yue Huang; Joshua Wilson; Henry May – International Journal of Artificial Intelligence in Education, 2025
Automated writing evaluation (AWE) is an artificial intelligence (AI)-empowered educational technology designed to assist writing instruction and improve students' writing proficiency. The present study adopted a quasi-experimental design using the inverse probability of treatment weighting method to explore the long-term effects of an AWE system…
Descriptors: Writing Evaluation, Automation, Computer Uses in Education, Artificial Intelligence
Han, Chao – Language Testing, 2022
Over the past decade, testing and assessing spoken-language interpreting has garnered an increasing amount of attention from stakeholders in interpreter education, professional certification, and interpreting research. This is because in these fields assessment results provide a critical evidential basis for high-stakes decisions, such as the…
Descriptors: Translation, Language Tests, Testing, Evaluation Methods
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
Liu, Houjun; MacWhinney, Brian; Fromm, Davida; Lanzi, Alyssa – Journal of Speech, Language, and Hearing Research, 2023
Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that transcription is very time intensive. Methods that can reduce the required time and effort could help in promoting the use of LSA for clinical practice and research. Method: This article describes an automated pipeline, called Batchalign, that takes raw…
Descriptors: Automation, Language Tests, Computational Linguistics, Morphology (Languages)
Ockey, Gary J.; Neiriz, Reza – Assessment in Education: Principles, Policy & Practice, 2021
As our understanding of the construct of oral communication (OC) has evolved, so have the possibilities of computer technology undertaking the delivery of tests that measure this ability. It is paramount to understand to what extent such developments lead to accurate, comprehensive, and useful assessment of OC. In this paper, we discuss five…
Descriptors: Speech Communication, Computer Assisted Testing, Speech Tests, English (Second Language)
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)
Advancing Language Assessment with AI and ML--Leaning into AI Is Inevitable, but Can Theory Keep Up?
Xiaoming Xi – Language Assessment Quarterly, 2023
Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…
Descriptors: Artificial Intelligence, Theory Practice Relationship, Language Tests, Man Machine Systems

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