Bayesian model in the conjugation of Arabic triliteral verb by second language learners.

Abstract

One of accurately assumed model for understanding how native speakers of flective languages use morphological structures is Bayesian model. This model explains that the ability of native speakers to predict other inflective forms of conjugation of  Arabic triliteral verb is influenced by their knowledge of other inflective forms, which they are already familiar with, and also by the natural predictability of the inflective form candidates they want to conclude. The objective is to test empirically whether the Bayesian model in that phenomen also applies to Arabic learners in predicting morphological forms of Arabic as L2. As experimental research, we obtained data from  answers sheet of respondents in predicting word forms in imperfective verb conjugations. Data analysis utilized Descriptive Analytics and Generalized Linear Mixed Model (GLMM). The results stated that prior information makes it easier for respondents to predict forms derived from unknown roots