Many-facet Dichotomous Rasch Model Analysis of the Modern Language Aptitude Test.

Abstract

Researchers and practitioners have used the Modern Language Aptitude Test (MLAT) to assess language aptitude and identify possible language learning deficiencies in examinees since the 1950s. However, researchers have not assessed its psychometric properties using modern measurement theory methods. We use the dichotomous Rasch model to explore the psychometric properties of the MLAT, including data-model fit indices, item difficulty and student ability calibrations, reliability of separation, and differences in achievement across gender subgroups based on a sample of undergraduate and graduate university students (N=204). Our findings suggest that the MLAT has acceptable psychometric properties such that it can be meaningfully interpreted as a measure of language proficiency. Our findings confirm previous research that language performance across gender groups significantly differs. We found no significant interactions between gender subgroups and the difficulty of the five domains of the assessment. We discuss these results in terms of their implications for research and practice.