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Okim Kang; Maria Kostromitina; Xun Yan; Ron I. Thomson; Talia Isaacs – Language Assessment Quarterly, 2025
There has been much debate in assessment research about the inclusion of Global English accents in high-stakes listening tests. This study explored test-takers' attitudes toward the inclusion of different English accents in the Duolingo English Test (DET) 2021 test version and their associations with listening test scores. One hundred sixty…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Software
Sok, Sarah; Du, Qian; Lee, Jerry Won – International Journal of Bilingual Education and Bilingualism, 2023
Various examinations are administered at universities across the US as a means of assessing bilingual/multilingual international teaching assistants' (ITAs') proficiency in spoken English before they are permitted to teach. While such exams are taken by students in a range of academic disciplines, recent research suggests that communicative…
Descriptors: Oral Language, Language Tests, English (Second Language), Second Language Learning
Kang, Okim; Thomson, Ron; Moran, Meghan – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2019
This study examines the effect of incorporating a variety of international English accents into a simulated TOEFL listening comprehension test in growing recognition of internationalization of language teaching and learning in the field of TESOL. Although some high-stakes English proficiency exams have begun incorporating speech samples produced…
Descriptors: Pronunciation, Listening Comprehension Tests, Language Variation, English (Second Language)
Miao, Yongzhi – Language Testing, 2023
Scholars have argued for the inclusion of different spoken varieties of English in high-stakes listening tests to better represent the global use of English. However, doing so may introduce additional construct-irrelevant variance due to accent familiarity and the shared first language (L1) advantage, which could threaten test fairness. However,…
Descriptors: Pronunciation, Metalinguistics, Native Language, Intelligibility
Hannah, L.; Kim, H.; Jang, E. E. – Language Assessment Quarterly, 2022
As a branch of artificial intelligence, automated speech recognition (ASR) technology is increasingly used to detect speech, process it to text, and derive the meaning of natural language for various learning and assessment purposes. ASR inaccuracy may pose serious threats to valid score interpretations and fair score use for all when it is…
Descriptors: Task Analysis, Artificial Intelligence, Speech Communication, Audio Equipment
Boonsuk, Yusop; Karakas, Ali – Acta Educationis Generalis, 2020
Introduction: In recent years, the number of test-takers of international tests of English has grown at an exponential rate. Those whose first language is not English, i.e. non-native English speakers (NNES), constitute the predominant majority of these test-takers, largely based in non-Anglophone contexts. Thus, the state of whether the…
Descriptors: Language Variation, English (Second Language), Second Language Learning, Second Language Instruction
Wei, Jing; Llosa, Lorena – Language Assessment Quarterly, 2015
This article reports on an investigation of the role raters' language background plays in raters' assessment of test takers' speaking ability. Specifically, this article examines differences between American and Indian raters in their scores and scoring processes when rating Indian test takers' responses to the Test of English as a Foreign…
Descriptors: North Americans, Indians, Evaluators, English (Second Language)