A regression analysis approach to measuring the influence of student characteristics on language learning strategies

Abstract

Mapping multivariate influence of learner characteristics on behavior highlights models in learning. To this end, we explored the relationships between strategies and learning characteristics and used regression analysis to understand how learner characteristics predict learning strategy choices. A cross-sectional research design with 175 students revealed high levels of strategy use, with statistically significant correlations within and between Strategy Inventory for Language Learning (SILL; Oxford, 1990) and Student Characteristics of Learning (SCL; Artelt, Baumert, Julius-McElvany, & Peschar, 2003) scales. Regression analyses revealed differences in the types of learner characteristics predicting strategy use, most notably between direct and indirect strategy categories. Instrumental motivation was predictive for both direct and indirect SILL subcomponents, while self-efficacy influenced memory, cognitive and compensation strategies, and persistence predicted reported levels of metacognitive and affective strategy choice. Moreover, a negative path coefficient existed from persistence to compensation strategies and from competition to memory strategies, indicating mediation and overall rich complexity in how learner characteristics influence behavior.