Predicting achievement in distance language learning: a structural equation model

Getting increasingly common in many settings in higher education, distance language courses have become a vigorous area of research which requires sustained focus. Although the relevant literature has documented well various aspects of distance language learning, the factors affecting academic achievement have remained underresearched. This study investigates the predictive power of the sense of community, perceived learning and learner satisfaction as the possible factors having an influence on academic achievement. Data for this study come from a series of surveys administered to a total of 156 EFL learners and participants' final grades. Structural Equation Model (SEM) was used to analyse the data. Results indicated acceptable values of the goodness of fit indices for structural model (TLI =.96; CFI =.98; NFI =.95; RMSEA =.06 and SRMR =.04). Analysis of path coefficients revealed that two components of sense of community (i.e. teaching presence and cognitive presence), perceived learning and satisfaction are the significant predictors of academic achievement. The research findings bear implications for the design of distance language courses.