Structural Equation Modeling of Vocabulary Size and Depth Using Conventional and Bayesian Methods

Frontiers in Psychology

article

Rie Koizumi¹  Yo In’nami² 

[1] School of Medicine, Juntendo University;Faculty of Science and Engineering, Chuo University

关键词: vocabulary size;    vocabulary depth;    factor structure;    model testing;    Bayesian structural equation modeling;   

DOI  :  10.3389/fpsyg.2020.00618

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

In classifications of vocabulary knowledge, vocabulary size and depth have often been separately conceptualized ( Schmitt, 2014 ). Although size and depth are known to be substantially correlated, it is not clear whether they are a single construct or two separate components of vocabulary knowledge ( Yanagisawa and Webb, 2020 ). This issue has not been addressed extensively in the literature and can be better examined using structural equation modeling (SEM), with measurement error modeled separately from the construct of interest. The current study reports on conventional and Bayesian SEM approaches (e.g., Muthén and Asparouhov, 2012 ) to examine the factor structure of the size and depth of second language vocabulary knowledge of Japanese adult learners of English. A total of 255 participants took five vocabulary tests. One test was designed to measure vocabulary size in terms of the number of words known, while the remaining four were designed to measure vocabulary depth in terms of word association, polysemy, and collocation. All tests used a multiple-choice format. The size test was divided into three subtests according to word frequency. Results from conventional and Bayesian SEM show that a correlated two-factor model of size and depth with three and four indicators, respectively, fit better than a single-factor model of size and depth. In the two-factor model, vocabulary size and depth were strongly correlated ( r = 0.945 for conventional SEM and 0.943 for Bayesian SEM with cross-loadings), but they were distinct. The implications of these findings are discussed.

【 授权许可】

CC BY