The 9th International Conference on English Language Teaching (ELT) In China (ELT2020)

       The current paper partially replicates an earlier study (Treffers-Daller, Parslow, & Williams, 2018) indicating that lexical diversity (LD) measures can help to discriminate between CEFR levels. We adapt Treffers-Daller et al.’s study to investigate the extent to which vocabulary measures are able to predict second language (L2) writing task (International English Language Testing System (IELTS)) scores. We use the same LD measures as in the earlier paper, along with a variety of vocabulary tools. In addition, the study adopts a recent approach (Clenton, De Jong, Clingwall, & Fraser, 2020) and investigates the multi-faceted construct of participant productive vocabulary knowledge. Our aim, therefore, is to contribute to discussions on how productive vocabulary knowledge and lexical diversity measures can help in the assessment of second language learners’ written work at different proficiency levels.
        We assess (n = 70) L1 Japanese undergraduate learners of (L2) English (CEFR B2). We adopt three different productive vocabulary tasks: Lex30 (Meara & Fitzpatrick, 2000) (a task based on word association responses); G_Lex (Fitzpatrick & Clenton, 2017) (a gap-fill task); and, the Productive Vocabulary Levels Test (PVLT; Laufer & Nation, 1999) (a sentence completion task). The performance of each of the productive vocabulary tasks has been shown (Clenton et al., 2020) to vary according to the quantity and quality of the productive vocabulary knowledge elicited.  Participants responded to (6) different IELTS writing questions. For processing, we maintained a constant text length, and following recent research (Kyle, 2020) we flemmatized all writing samples.
       Our results reflect Treffers-Daller et al.’s (2018) findings to the extent that basic measures of LD such as TTR (Templin, 1957) explain more variance in writing scores than sophisticated measures such as D (Malvern et al. 2004) or MTLD (McCarthy 2005). A simple count of different words (defined as flemmas) proved to be the best predictor of variance in overall IELTS essay scores. Our data also reveal that higher IELTS task scores tended to reflect a higher quality of productive vocabulary knowledge. We discuss these findings in terms of second language acquisition, with specific implications for pedagogy.
 

productive vocabulary knowledge; lexical diversity; IELTS writing