A refined and concise model of indices for quantitatively measuring lexical richness of Chinese university students’ EFL writing

• Main Authors: Yang, Yang, Zheng, Ze
• Format: Article
• Language: English
• Published: Bastas 2024
• Online Access: http://psasir.upm.edu.my/id/eprint/114627/1/114627.pdf; http://psasir.upm.edu.my/id/eprint/114627/; https://www.cedtech.net/article/a-refined-and-concise-model-of-indices-for-quantitatively-measuring-lexical-richness-of-chinese-14707

In the existing literature, scholars have proposed various indices to measure the lexical richness (LR) of English as a foreign language (EFL) writing. However, there are currently issues of redundant indices and inconsistent usage. Attempting to address the research question of which indices are the most sensitive and effective ones to distinguish between different grade levels of Chinese university students’ EFL writing, this study aims to put forward a refined and concise model of indices that can truthfully reflect LR in EFL writing. A total of 180 compositions were selected from a Chinese EFL learner corpus: Spoken and written English corpus of Chinese learners. Scores of 28 LR indices of these compositions were computed using the software Lexical Complexity Analyzer, MATTR, and Coh-Metrix. One-way ANOVA or Welch’s ANOVA, depending on the variable’s homogeneity of variances, was conducted for each index. Two criteria were applied to determine which index of a measure should be included in the refined model: whether the difference of an index is significant among different grade levels and the effect size of ANOVA. Based on the quantitative results of ANOVAs and qualitative human judgment based on literature, six indices of the six LR measures were included in the refined model: lexical density, lexical sophistication-I, verb sophistication-II, number of different words-expected sequence 50, corrected TTR, and squared verb variation-I. This refined model addresses the issues of redundancy and inconsistency in previous studies, providing a more accurate and efficient tool for assessing LR in EFL writing.