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Introducing and Evaluating a Measure of Lexical Diversity Across Word Classes
No Arizona Univ, Appl Linguist, Flagstaff, AZ 86011 USA..
No Arizona Univ, Appl Linguist, Flagstaff, AZ 86011 USA..
Univ Gävle, English Linguist, Gävle, Sweden..
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Department of Language, Literature and Intercultural Studies (from 2013).ORCID iD: 0000-0002-7063-0070
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2026 (English)In: TESOL quarterly (Print), ISSN 0039-8322, E-ISSN 1545-7249Article in journal (Refereed) Epub ahead of print
Abstract [en]

Lexical diversity (LD) has been shown to be a strong predictor of second language (L2) proficiency. However, most current indices combine all word classes into a single measure and thus only capture the broadest patterns of lexical variation. In addition, researchers interested in examining usage patterns across word classes currently lack access to measures of LD that are both more linguistically interpretable and robust to text length. In response to these issues, this paper introduces a methodology for examining part-of-speech (POS)-specific LD indices (e.g., verb and noun diversity) that apply the moving-average type-token ratio (MATTR), a measure validated for its stability across text lengths and reliability in shorter texts. We also evaluate these measures by comparing them to traditional, so-called omnibus LD measures for interpreting L2 corpus data. The results show that examining LD within different parts of speech can help researchers disentangle the broader developmental trend observed with omnibus measures. These findings highlight how POS-specific LD provides more linguistically interpretable description of L2 lexical development, thus complementing traditional omnibus measures.

Place, publisher, year, edition, pages
John Wiley & Sons, 2026.
National Category
Studies of Specific Languages
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English
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URN: urn:nbn:se:kau:diva-110365DOI: 10.1002/tesq.70154ISI: 001769613600001Scopus ID: 2-s2.0-105039467194OAI: oai:DiVA.org:kau-110365DiVA, id: diva2:2065188
Available from: 2026-06-03 Created: 2026-06-03 Last updated: 2026-06-08Bibliographically approved

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Wang, Ying

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7891011121310 of 41
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