A Deep Learning Model with Virtual Reality Technology for Second Language Acquisition

Abstract

Attention is considered a sufficient condition for transforming input into absorption in the field of second language acquisition and is a major cognitive factor influencing second language learning. The temporal characteristics of attentional shift are a more accurate reflection of second language learners’ thinking processes. Based on this, this study uses deep learning techniques and VR technology to explore the attentional patterns of the second language (English) learners when processing online tasks. The experiments show that the linear attentional control model of young second language learners is closely related to their online task performance, which can visually explain the effect of their linear attentional control on online task completion. The model also has a high regression/prediction accuracy.