Investigating the role of psychological needs in predicting the educational sustainability of Metaverse using a deep learning-based hybrid SEM-ANN technique

Abstract

ABSTRACT Metaverse is an immersive three-dimensional (3D) virtual world inhabited by avatars beyond the physical realm. The COVID-19 pandemic has disrupted the education system and the need to accelerate the digitalization of education has received a lot of attention. Metaverse can be an alternative solution for sociocultural interaction and to continue education. Accordingly, this study aimed to identify key factors in predicting the educational sustainability of Metaverse. The study empirically tested the role of psychological needs (i.e. hedonic motivation, affiliation, dominance, achievement, and autonomy) in predicting educational sustainability. The study employed a hybrid method integrating covariance-based structural-equation-modeling (CB-SEM) and deep artificial neural network (ANN) model. The CB-SEM results indicated that the need for autonomy and hedonic motivation significantly predicted the educational sustainability of Metaverse. Further, deep ANN models indicated that hedonic motivation was the most important input factor, followed by autonomy, affiliation, dominance, and achievement. Findings have practical implications for developers of the Metaverse environments and theoretical contributions for educators who manage and implement such environments.