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 summa-rizing 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.
Original language | English |
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Article number | 2412 |
Journal | Applied Sciences |
Volume | 11 |
Issue number | 5 |
DOIs | |
Publication status | Published - Mar 2021 |
Publication type | A2 Review article in a scientific journal |
Keywords
- Deep and meaningful learning (DML)
- Distance education
- E-learning
- Higher education (HE)
- Open and distance learning (ODL)
- Social virtual reality environments (SVREs)
- Systematic literature review (SLR)
Publication forum classification
- Publication forum level 1
ASJC Scopus subject areas
- General Materials Science
- Instrumentation
- General Engineering
- Process Chemistry and Technology
- Computer Science Applications
- Fluid Flow and Transfer Processes