Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review
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 hi...
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ftmdpi:oai:mdpi.com:/2076-3417/11/5/2412/ 2023-08-20T04:06:08+02:00 Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review Stylianos Mystakidis Eleni Berki Juri-Petri Valtanen agris 2021-03-09 application/pdf https://doi.org/10.3390/app11052412 EN eng Multidisciplinary Digital Publishing Institute Computing and Artificial Intelligence https://dx.doi.org/10.3390/app11052412 https://creativecommons.org/licenses/by/4.0/ Applied Sciences; Volume 11; Issue 5; Pages: 2412 social virtual reality environments (SVREs) distance education open and distance learning (ODL) e-learning deep and meaningful learning (DML) systematic literature review (SLR) higher education (HE) Text 2021 ftmdpi https://doi.org/10.3390/app11052412 2023-08-01T01:14:11Z 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. Text DML MDPI Open Access Publishing Applied Sciences 11 5 2412 |
institution |
Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
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English |
topic |
social virtual reality environments (SVREs) distance education open and distance learning (ODL) e-learning deep and meaningful learning (DML) systematic literature review (SLR) higher education (HE) |
spellingShingle |
social virtual reality environments (SVREs) distance education open and distance learning (ODL) e-learning deep and meaningful learning (DML) systematic literature review (SLR) higher education (HE) Stylianos Mystakidis Eleni Berki Juri-Petri Valtanen Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
topic_facet |
social virtual reality environments (SVREs) distance education open and distance learning (ODL) e-learning deep and meaningful learning (DML) systematic literature review (SLR) higher education (HE) |
description |
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. |
format |
Text |
author |
Stylianos Mystakidis Eleni Berki Juri-Petri Valtanen |
author_facet |
Stylianos Mystakidis Eleni Berki Juri-Petri Valtanen |
author_sort |
Stylianos Mystakidis |
title |
Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
title_short |
Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
title_full |
Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
title_fullStr |
Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
title_full_unstemmed |
Deep and Meaningful E-Learning with Social Virtual Reality Environments in Higher Education: A Systematic Literature Review |
title_sort |
deep and meaningful e-learning with social virtual reality environments in higher education: a systematic literature review |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
https://doi.org/10.3390/app11052412 |
op_coverage |
agris |
genre |
DML |
genre_facet |
DML |
op_source |
Applied Sciences; Volume 11; Issue 5; Pages: 2412 |
op_relation |
Computing and Artificial Intelligence https://dx.doi.org/10.3390/app11052412 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/app11052412 |
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Applied Sciences |
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11 |
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5 |
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2412 |
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1774717073887330304 |