Investigating minimum text lengths for lexical diversity indices

•MATTR and two versions of MTLD are highly stable indices for analyzing short texts.•TTR, Root TTR, and Log TTR were not stable for any text length in the analysis.•Essay prompt and proficiency level had a small but significant effect on scores. Lexical diversity (LD) is an important feature of a se...

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Veröffentlicht in:Assessing writing 2021-01, Vol.47, p.100505, Article 100505
Hauptverfasser: Zenker, Fred, Kyle, Kristopher
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Sprache:eng
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Zusammenfassung:•MATTR and two versions of MTLD are highly stable indices for analyzing short texts.•TTR, Root TTR, and Log TTR were not stable for any text length in the analysis.•Essay prompt and proficiency level had a small but significant effect on scores. Lexical diversity (LD) is an important feature of a second language (L2) writer’s lexical knowledge, and indices of LD have been widely used in the field of writing assessment (e.g., Cumming et al., 2006; Engber, 1995). Research with longer native speaker (L1) texts has indicated, however, that many commonly used LD indices are sensitive to text length and may conflate lexical breadth and fluency. Because of the importance of measuring LD in L2 writing assessment research, it is essential to know the degree to which particular LD indices are resistant to text length effects and the minimum text lengths at which these indices produce stable values. In this study, we investigate text length effects for nine indices of LD in a corpus of 4542 L2 argumentative essays. The results indicate that MATTR (Covington & McFall, 2010) and two versions of MTLD (McCarthy, 2005; McCarthy & Jarvis, 2010) are the most stable of the indices included in the study. MATTR performs particularly well, maintaining a high degree of stability across all text lengths. Comparisons based on essay prompt and proficiency level are also discussed.
ISSN:1075-2935
1873-5916
DOI:10.1016/j.asw.2020.100505