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Kyle, Kristopher; Eguchi, Masaki; Choe, Ann Tai; LaFlair, Geoff – Language Testing, 2022
In the realm of language proficiency assessments, the domain description inference and the extrapolation inference are key components of a validity argument. Biber et al.'s description of the lexicogrammatical features of the spoken and written registers in the T2K-SWAL corpus has served as support for the TOEFL iBT test's domain description and…
Descriptors: Language Variation, Written Language, Speech Communication, Inferences
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Kyle, Kristopher; Choe, Ann Tai; Eguchi, Masaki; LaFlair, Geoff; Ziegler, Nicole – ETS Research Report Series, 2021
A key piece of a validity argument for a language assessment tool is clear overlap between assessment tasks and the target language use (TLU) domain (i.e., the domain description inference). The TOEFL 2000 Spoken and Written Academic Language (T2K-SWAL) corpus, which represents a variety of academic registers and disciplines in traditional…
Descriptors: Comparative Analysis, Second Language Learning, English (Second Language), Language Tests
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Kyle, Kristopher; Crossley, Scott – Language Testing, 2017
Over the past 45 years, the construct of syntactic sophistication has been assessed in L2 writing using what Bulté and Housen (2012) refer to as absolute complexity (Lu, 2011; Ortega, 2003; Wolfe-Quintero, Inagaki, & Kim, 1998). However, it has been argued that making inferences about learners based on absolute complexity indices (e.g., mean…
Descriptors: Syntax, Verbs, Second Language Learning, Word Frequency
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Crossley, Scott; Kyle, Kristopher; Salsbury, Thomas – Modern Language Journal, 2016
This study investigates relations between second language (L2) lexical input and output in terms of word information properties (i.e., lexical salience; Ellis, 2006a). The data for this study come from a longitudinal corpus of naturalistic spoken data between L2 learners and first language (L1) interlocutors collected over a year's time. The…
Descriptors: Language Usage, Language Research, Second Language Learning, Computational Linguistics
Crossley, Scott A.; Kyle, Kristopher; Allen, Laura K.; Guo, Liang; McNamara, Danielle S. – Grantee Submission, 2014
This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…
Descriptors: Computational Linguistics, Essays, Scoring, Writing Evaluation