Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review

Abstract

Deep and meaningful learning (DML) in distant education should be an essential outcome of quality education. In this literature review, we focus on e-learning effectiveness along with the factors and conditions leading to DML when using social virtual reality environments (SVREs) in distance mode higher education (HE). Hence, a systematic literature review was conducted summarizing the findings from thirty-three empirical studies in HE between 2004 (appearance of VR) and 2019 (before coronavirus appearance). We searched for the cognitive, social, and affective aspects of DML in a research framework and studied their weight in SVREs. The findings suggest that the use of SVREs can provide authentic, simulated, cognitively challenging experiences in engaging, motivating environments for open-ended social and collaborative interactions and intentional, personalized learning. Furthermore, the findings indicate that educators and SVRE designers need to place more emphasis on the socio-cultural semiotics and emotional aspects of e-learning and ethical issues such as privacy and security. The mediating factors for DML in SVREs were accumulated and classified in the resultant Blended Model for Deep and Meaningful e-learning in SVREs. Improvement recommendations include meaningful contexts, purposeful activation, learner agency, intrinsic emotional engagement, holistic social integration, and meticulous user obstacle removal.

Effect of Collaboration Mode and Position Arrangement on Immersive Analytics Tasks in Virtual Reality: A Pilot Study

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The Implementation of Deep Reinforcement Learning in E-Learning and Distance Learning: Remote Practical Work

“…In this table, we compare the presented result with 4 recent research articles on the implementation of DQN and RL techniques, and it shows the proposed result has an accuracy output between 17% and 99% in various methods that has a better consequence. Another literary review proposed by Mystakidis et al [26]…”

Deep Meaningful Learning

“…More specific, DML is influenced by factors of three types: learners' individual traits (e.g., personality, skills, emotions, motivation), contextual (e.g., teaching methods, assessment, teacher, class), and perceived contextual factors (e.g., workload, usefulness, relevance) [38]. In the context of distance education, a systematic review has integrated fifteen influencing factors into a blended model for deep and meaningful e-learning in social virtual reality environments [41]. Factors are organized in three classes: in relation to the learner (e.g., perceptions, technical skills), the implemented instructional design according to teacher perceptions and beliefs (e.g., learning theory, environment, activities), and the used technology (e.g., access, usability), before and during learning.…”