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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
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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)
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Richardson, Mary; Clesham, Rose – London Review of Education, 2021
Our world has been transformed by technologies incorporating artificial intelligence (AI) within mass communication, employment, entertainment and many other aspects of our daily lives. However, within the domain of education, it seems that our ways of working and, particularly, assessing have hardly changed at all. We continue to prize…
Descriptors: Artificial Intelligence, High Stakes Tests, Computer Assisted Testing, Educational Change
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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
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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
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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
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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
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Bateson, Gordon – International Journal of Computer-Assisted Language Learning and Teaching, 2021
As a result of the Japanese Ministry of Education's recent edict that students' written and spoken English should be assessed in university entrance exams, there is an urgent need for tools to help teachers and students prepare for these exams. Although some commercial tools already exist, they are generally expensive and inflexible. To address…
Descriptors: Test Construction, Computer Assisted Testing, Internet, Writing Tests
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Jones, Daniel Marc; Cheng, Liying; Tweedie, M. Gregory – Canadian Journal of Learning and Technology, 2022
This article reviews recent literature (2011-present) on the automated scoring (AS) of writing and speaking. Its purpose is to first survey the current research on automated scoring of language, then highlight how automated scoring impacts the present and future of assessment, teaching, and learning. The article begins by outlining the general…
Descriptors: Automation, Computer Assisted Testing, Scoring, Writing (Composition)
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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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Rupp, André A.; Casabianca, Jodi M.; Krüger, Maleika; Keller, Stefan; Köller, Olaf – ETS Research Report Series, 2019
In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…
Descriptors: Automation, Foreign Countries, English (Second Language), Language Tests
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Chen, Jing; Zhang, Mo; Bejar, Isaac I. – ETS Research Report Series, 2017
Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essay Tests
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Yu, Guoxing; Zhang, Jing – Language Assessment Quarterly, 2017
In this special issue on high-stakes English language testing in China, the two articles on computer-based testing (Jin & Yan; He & Min) highlight a number of consistent, ongoing challenges and concerns in the development and implementation of the nationwide IB-CET (Internet Based College English Test) and institutional computer-adaptive…
Descriptors: Foreign Countries, Computer Assisted Testing, English (Second Language), Language Tests
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Gleason, Jesse – Hispania, 2014
Communicative approaches to language teaching that emphasize the importance of speaking (e.g., task-based language teaching) require innovative and evidence-based means of assessing oral language. Nonetheless, research has yet to produce an adequate assessment model for oral language (Chun 2006; Downey et al. 2008). Limited by automatic speech…
Descriptors: Scoring, Linguistics, Oral Language, Language Tests
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