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Yufan Zhao; Vahid Aryadoust – Language Testing, 2025
This study examined the semantic features of the simulated mini-lectures in the listening sections of the International English Language Testing System (IELTS) and the Test of English as a Foreign Language (TOEFL) based on automatized semantic analysis to explore the content validity of the two tests. Two study corpora were utilized, the IELTS…
Descriptors: Semantics, Computational Linguistics, Academic Language, Second Language Learning
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
Hitoshi Nishizawa – Language Testing, 2024
Corpus-based studies have offered the domain definition inference for test developers. Yet, corpus-based studies on temporal fluency measures (e.g., speech rate) have been limited, especially in the context of academic lecture settings. This made it difficult for test developers to sample representative fluency features to create authentic…
Descriptors: High Stakes Tests, Language Tests, Second Language Learning, Computer Assisted Testing
Aryadoust, Vahid; Foo, Stacy; Ng, Li Ying – Language Testing, 2022
The aim of this study was to investigate how test methods affect listening test takers' performance and cognitive load. Test methods were defined and operationalized as while-listening performance (WLP) and post-listening performance (PLP) formats. To achieve the goal of the study, we examined test takers' (N = 80) brain activity patterns…
Descriptors: Listening Comprehension Tests, Language Tests, Eye Movements, Brain Hemisphere Functions