Using an ANN-based computational model to simulate and evaluate Chinese students’ individualized cognitive abilities important in their English acquisition

AbstractFrom a psycholinguistic perspective of view, there are many cognitive differences that matter to individuals’ second-language acquisition (SLA). Although many computer-assisted tools have been developed to capture and narrow the differences among learners, the use of these strategies may be highly risky because changing the environments or the participants may lead to failure. In this paper, we propose an artificial neural network (ANN)-based computational model to simulate the environment to which students are exposed. The ANN computational model equips English teachers with the ability to quickly find the predicting factors to learners’ overall English competences and also provides teachers with the ability to find abnormal students, based on reviewing their individualized ANN trajectories. Finally, by observing the compound effects of cognitive factors using the same evaluation scale, new hypotheses about the mutual relationships among the phonological awareness, phonological short-term memory,...