Application of Virtual Reality Technology for University English Culture Parenting

Abstract

Seeing something as reality (VR) is the term used to describe the visual perception of virtual reality, general assembly designs, patterns, and their conversion into part entities. In this manuscript, Application of Virtual Reality Technology for University English Culture Parenting (VRT-TTEDNN-BBWOA-UECP) is proposed. Initially, Virtual reality technology (VR) can offer English learners virtual experiences, such virtual chats or simulations of real-life situations, to practice communication skills and University English Culture Parenting. The data are taken from English language content database which contains eye movement of 19 students data are collected as input. Afterward, data are fed to pre-processing. In pre-processing, removes noise from data using Learnable Edge Collaborative Filtering (LECF). Then the preprocessed data are given to Temporal and Topological Embedding Deep Neural Network (TTEDNN) for classifying the eye track samples of the students as positive (+) and Negative (-). In general Temporal and Topological Embedding Deep Neural Network does not express some adaption of optimization strategies for determining optimal parameters to promise accurate classification. Hence, BBWOA is proposed to enhance weight parameter of Temporal and Topological Embedding Deep Neural Network. The proposed technique is executed by python, efficacy of VRT-TTEDNN-BBWOA-UECP technique is assessed by support of numerous performances such as accuracy, precision, F1-score and error rate is analysed. The performance of VRT-TTEDNN-BBWOA-UECP technique is analysed with existing techniques likes deep learning method by virtual reality technology for second language acquisition (VRT-CNN-SLA), 5G joint AI technology in innovation with reform of university English education (VRT-KNN-IUEE), big dyadic affect in parent-child multi-modal interaction: introducing dami-p2c dataset with preliminary analysis (VRT-GAN-PCMI) respectively.