Sustainable Educational Metaverse Content and System Based on Deep Learning for Enhancing Learner Immersion

Abstract

Social distancing has encouraged the use of various non-face-to-face services utilizing information and communication technology, especially in the education sector. Educators and learners are increasingly utilizing online technology to conduct non-face-to-face classes, which has resulted in an increased use of EduTech. Virtual education is expected to expand continuously. However, students involved in virtual education find it difficult to focus and participate in the classes. Hence, we propose a system that can improve learners’ focus and immersion in metaverse-based education. In this paper, we propose a sustainable educational metaverse content and system based on deep learning that can enhance learners’ immersion. We built an AI-based simulation that judges learning activities based on the learning behavior rather than on the learner’s device and program events and allows the user to proceed to the next level of education. In the simulation implemented in this study, virtual reality educational contents were created for 12 educational activities, and the effectiveness of four learning models in assessing the learning effectiveness of learners was evaluated. From the four models, an ensemble model with boosting was adopted considering its accuracy, complexity, and efficiency. The F1-score and specificity of the adopted learning model were confirmed. This model was applied to the system in a simulation.