Students' Decisions to Study English at Foreign Language Centers Using Bayesian Model Averaging Algorithm

Abstract

Along with other languages, English is a powerful tool for communication as well as for the linguistic integration and growth of people. English is considered the universal language everywhere in the world. It is widely used around the world; it might be considered a foreign language of major global significance. On the other side, previous academics stated that factors affect students' decision to learn English at foreign language centers such as study program, tuition fee, location, promotion, social factors, psychological factors, etc. However, these studies just only choose a single model among alternative feasible models. This study utilizes the Bayesian model averaging approach to determine the optimal models for determinants influencing students' decision to study English at foreign language centers. The findings through the Bayesian model averaging algorithm revealed the best two models for determinants impacting students' decisions to learn English at foreign language centers.