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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
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
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)
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)
Charles Hulme; Joshua McGrane; Mihaela Duta; Gillian West; Denise Cripps; Abhishek Dasgupta; Sarah Hearne; Rachel Gardner; Margaret Snowling – Language, Speech, and Hearing Services in Schools, 2024
Purpose: Oral language skills provide a critical foundation for formal education and especially for the development of children's literacy (reading and spelling) skills. It is therefore important for teachers to be able to assess children's language skills, especially if they are concerned about their learning. We report the development and…
Descriptors: Automation, Language Tests, Standardized Tests, Test Construction
de Jong, Nivja H.; Pacilly, Jos; Heeren, Willemijn – Assessment in Education: Principles, Policy & Practice, 2021
Fluency in terms of speed of speech and (lack of) hesitations such as silent and filled pauses ('uhm's) is part of oral proficiency. Language assessment rubrics therefore include aspects of fluency. Measuring fluency, however, is highly time-consuming because of the manual labour involved. The current paper aims to automatically measure aspects of…
Descriptors: Language Fluency, Speech Skills, Second Languages, Indo European Languages
Gordon Matthew – Technology, Pedagogy and Education, 2025
In most universities in South Africa, English is still preferred as the medium of instruction. However, most schools in South Africa have adopted a home-language education approach. Those school students then have a lower English proficiency compared to other students from English schools. Providing these students with instructional assistance…
Descriptors: Eye Movements, Captions, English (Second Language), Second Language Learning
Davis, Larry; Papageorgiou, Spiros – Assessment in Education: Principles, Policy & Practice, 2021
Human raters and machine scoring systems potentially have complementary strengths in evaluating language ability; specifically, it has been suggested that automated systems might be used to make consistent measurements of specific linguistic phenomena, whilst humans evaluate more global aspects of performance. We report on an empirical study that…
Descriptors: Scoring, English for Academic Purposes, Oral English, Speech Tests
Gong, Kaixuan – Asian-Pacific Journal of Second and Foreign Language Education, 2023
The extensive use of automated speech scoring in large-scale speaking assessment can be revolutionary not only to test design and rating, but also to the learning and instruction of speaking based on how students and teachers perceive and react to this technology. However, its washback remained underexplored. This mixed-method study aimed to…
Descriptors: Second Language Learning, Language Tests, English (Second Language), Automation
Clark, Tony; Endres, Heidi – Assessment in Education: Principles, Policy & Practice, 2021
An effective diagnostic test can play a key role in language learning, allowing strengths and weaknesses in students' linguistic development to be identified and addressed. This paper describes the online Cambridge English diagnostic test, assessing English grammatical knowledge at A2 level. As most language tests focus on proficiency or…
Descriptors: Diagnostic Tests, High School Students, Computer Assisted Testing, Grammar
Wang, Zhen; Zechner, Klaus; Sun, Yu – Language Testing, 2018
As automated scoring systems for spoken responses are increasingly used in language assessments, testing organizations need to analyze their performance, as compared to human raters, across several dimensions, for example, on individual items or based on subgroups of test takers. In addition, there is a need in testing organizations to establish…
Descriptors: Automation, Scoring, Speech Tests, Language Tests
Rafatbakhsh, Elaheh; Ahmadi, Alireza; Moloodi, Amirsaeid; Mehrpour, Saeed – Educational Measurement: Issues and Practice, 2021
Test development is a crucial, yet difficult and time-consuming part of any educational system, and the task often falls all on teachers. Automatic item generation systems have recently drawn attention as they can reduce this burden and make test development more convenient. Such systems have been developed to generate items for vocabulary,…
Descriptors: Test Construction, Test Items, Computer Assisted Testing, Multiple Choice Tests
Daniels, Paul – TESL-EJ, 2022
This paper compares the speaking scores generated by two online systems that are designed to automatically grade student speech and provide personalized speaking feedback in an EFL context. The first system, "Speech Assessment for Moodle" ("SAM"), is an open-source solution developed by the author that makes use of Google's…
Descriptors: Speech Communication, Auditory Perception, Computer Uses in Education, Computer Assisted Testing
Cullinan, Dan; Barnett, Elisabeth; Kopko, Elizabeth; Lopez, Andrea; Morton, Tiffany – MDRC, 2019
Colleges throughout the United States are evaluating the effectiveness of the strategies used to decide whether to place students into college-level or developmental education courses. Developmental, or remedial, courses are designed to develop the reading, writing, or math skills of students deemed underprepared for college-level courses, a…
Descriptors: College Students, Student Placement, Developmental Studies Programs, Remedial Programs
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