A Survey for Educational Metaverse: Advances and Beyond
Bibliographic record
Abstract
The Metaverse, a convergence of cutting-edge technologies such as Virtual Reality (VR), Augmented Reality (AR), Artificial Intelligence (AI), and blockchain, represents the next frontier in digital society’s evolution. Meanwhile, as societal emphasis on education intensifies, a multitude of novel technologies are being integrated into the educational landscape with the aim of improving overall educational outcomes. This trend has resulted in the conceptualization of the Educational Metaverse as an extension of Metaverse applications in this domain. Notwithstanding its advent, there exists a notable dearth of scholarly efforts dedicated to meticulously summarizing and analyzing the most up-to-date research findings on the Educational Metaverse. Thus, this study systematically reviews recent literature to examine the Metaverse’s role in education, a field that stands to benefit significantly from the integration of these technologies. From an interdisciplinary perspective, guided by the insights derived from clustering algorithms, approximately 90 recent publications were meticulously analysed to explore and synthesise various aspects pertaining to the Educational Metaverse. This comprehensive review meticulously explores its primary characteristics, progression of foundatonal technologies, and multiplicity of practical implementations, thereby unravelling the transformative potential it holds for revolutionising pedagogical practices. The findings underscore the Educational Metaverse’s capacity to enhance learner engagement and motivation through immersive experiences, while also addressing the educational needs of individuals with special requirements. The study highlights the importance of optimizing the Educational Metaverse’s technical architecture and developing pedagogical strategies that are inclusive and effective. Furthermore, it emphasizes the need to ensure educational equity and accessibility, allowing all learners to harness the benefits of this technological innovation. As the Metaverse emerges as a pivotal force in educational modernization, it is anticipated that its applications will continue to proliferate. The research further indicates that the future trajectory of the Educational Metaverse is poised towards comprehensiveness and integration, with technology advancements emphasizing real-time capabilities and security enhancements. It is anticipated to extend its reach into a broader array of scenarios, thereby enabling a wider cross-section of disciplines and populations to reap the benefits it affords.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".