Mapping the predictive role of MLAT subtests for L2 achievement through regression commonality analysis

Abstract

Despite the widespread use and effectiveness of the Modern Language Aptitude Test (MLAT) composite score in predicting individual differences in L2 achievement and proficiency, there has been little examination of MLAT subtests, although they have potential for illuminating components of L2 aptitude and the mechanism of prediction. Here we use regression commonality analysis to decompose the predictive variance from the MLAT into unique components for each subtest alone and for each possible combination of subtests (duos, trios, etc.) that may have shared variance. The results, from a longitudinal study of 307 U.S. secondary students during 2 years of Spanish learning, provide strong evidence for the role of literacy-related skills in all subtests and in predicting all L2 outcomes. These and other results support a view of L1 literacy and language skills leading to metalinguistic development, which in turn leads to stronger L2 aptitude and achievement.