AI-Based Metaverse Technologies Advancement Impact on Higher
Education Learners
BHAVANA S., VIJAYALAKSHMI V.
School of Social Sciences and Languages, Vellore Institute of Technology
Chennai, INDIA
Abstract: - Avatars of real people inhabit the Metaverse. Some industry players have called it the "next big
bang" for the Indian EdTech market, which is expected to reach $30 billion by 2032. Technology dominates
21st- century education, whether it's university-based programmers, real-world technical training, or abstract
concepts taught in schools and universities. In India's education sector, researchers are still studying Augmented
Reality. There are few Augmented Reality studies in education. This research evaluates and explains the impact
of an Augmented Reality smartphone app on the learning passion of high school/college students. The study
examines how augmented reality affects classroom motivation. Core motivation theory boosts classroom
motivation. The attention, relevance, confidence, and satisfaction (ARCS) model affected how Augmented
Reality was perceived and how the material was updated. This study evaluated Augmented reality smartphone
apps using SEM model analysis. The study used the ARCS model to analyses Augmented Reality Education
Apps, their effect on higher education, and their relationship with respect to Attention, relevance, satisfaction,
and confidence are motivational variables with significant findings. The study found that using an augmented
reality smartphone application would help students learn and be more motivated.
Keywords: - ARCS Model, Artificial Intelligence, Animation, Virtual Reality, Metaverse, Higher Education.
Received: June 29, 2021. Revised: July 8, 2022. Accepted: August 5, 2022. Published: Septemebr 15, 2022.
1 Introduction
The term "augmented reality" refers to augmentation
that is more lifelike than the original. It is a method
that enhances the viewer's experience by retouching
the thing in front of the camera. Or, to put it another
way, augmented reality introduces the intangible
to the
visible realm. AR (augmented reality) is a term that
refers to the use of technology to superimpose exact
noises, pictures, and text on top of the world that
humans see. “Augmented reality (AR) is a technology
that, in certain situations, uses the camera on a
smartphone to add visual components to a live view”.
One of the most common methods for augmented
reality to permeate everyday life is smartphone
gaming, which is becoming increasingly popular.
According to CNET, the augmented reality app
'Pokémon Go' became a worldwide sensation in
2016, attracting more than 100 million players at its
peak. According to Forbes, it has received more than
two billion dollars and continues to get additional
money every day. “Mixed reality (MR), also known
as augmented reality, is the merging of the natural
and virtual worlds to create new settings and visuals
that coexist and communicate with real-world and
digital objects in real time”. Because it involves
current technology and can be used on mobile
devices, augmented reality has become more widely
available (Keller, J. M. (1987).
“Digital games are the most frequently mentioned
application (Park & Kim, 2022). Another well-known
application is healthcare, which employs AR or VR
to train students in medical or nursing skills (Huang
et al., 2021; Hwang et al., 2022; Zhang et al., 2021).
AR and VR have also been used to demonstrate new
products and provide virtual experiences (Bourlakis
et al., 2009). Another example frequently mentioned
in previous metaverse articles is the use of AR or VR
for military training (Daz et al., 2020). According to
a strict definition of the metaverse, the majority of
existing applications are AR or VR rather than the
metaverse. On the other hand, the effectiveness and
success of these applications determine the
metaverse's potential”. “The Metaverse is not a new
concept in education, as several researchers and
educators have discussed its implications for
learning. For example, Kemp and Livingstone (2006)
discussed how to combine Metaverse with learning
management systems using a virtual world called the
"Second Life." process (Kemp & Livingstone,
2006)”. Most individuals now own mobile devices
and have expanded their usage of them, making
augmented reality (AR) more available. AR
represents the future reality of the educational
system. The rate of change in the classroom is
unmatched everywhere else. Many children benefit
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
178
Volume 21, 2022
from the increased interactive components in
classrooms because of the introduction of technology.
It is still early days in India when it comes to research
into the use of augmented reality in education, and
there is a paucity of research on the implications and
consequences of the use of augmented reality in
education. For a wide range of educational topics,
there are augmented reality smartphone applications
available, and educational apps for smartphones are
becoming more widely available [16]. The potential of
augmented reality in education has not yet been fully
explored, and research into the topic has been
restricted.
2 Review of Literature
When it comes to making learning more entertaining,
multimedia components have made a huge impact.
Human anatomy education takes use of the
opportunity to use technology to enhance the
learning experience because of all the issues that
have been discussed thus far. Visual anatomical
representations of complex structures can aid in their
comprehension [10]. It is possible to use augmented
reality (AR) and make it portable or mobile, moving
away from the conventional VR/VE settings of being
in a purpose-built environment. “Mobile Augmented
Reality (MAR) is a type of augmented reality that is
portable or mobile. Emerging and affordably priced
mobile technologies, such as those found in
smartphones, have made it possible for MAR
applications to be practical [6]”. Despite the
tremendous advantages of learning human body
anatomy, there are certain obstacles associated with
it. There are several hurdles, including the storage of
cadavers, moral issues, the quality and restricted
quantity of cadavers available, limited lab opening
hours, and a poor level of information retention.
In this study analysis of “how Augmented Reality
applications affect higher education was conducted
using the ARCS model of Learning Motivation
Dimensions models, developed by the researchers”.
3 Research Model
“This model (Keller 1983, 1987, 2016) is a
motivational design approach that is comprised of a
synthesis of various motivational concepts and
theories that are clustered into four categories:
Attention (A), Relevance (R), Confidence (C), and
Satisfaction (S). Figure:1. The Attention, Relevance,
Confidence, and Satisfaction (ARCS) model”.
Fig. 1: ARCS- Model
The ARCS Model, which is employed in the
suggested SEM Model, is the fundamental source of
the study paradigm. ARE stands for Animation.
The ARCS Model, which is employed in the
suggested SEM Model, is the fundamental source of
the study paradigm. ARE stands for Augmented
Reality Education App; ARA stands for Augmented
Reality Attention; ARR stands for Augmented
Reality Relevance; ARC stands for Augmented
Reality Confidence; ARS stands for Augmented
Reality Satisfaction, and ARHE stands for
Augmented Reality and Higher Education. Figure 2:
A proposed SEM analysis for the impact of an
Augmented Reality application on higher education,
based on the ARCS model of learning motivation.
This model is used to assess the effectiveness of
motivational stimuli on learner motivation and
performance. Many researchers have recently
applied the ARCS model to educational design for
learning. ARCS model in educational design can
successfully increase learner motivation, according
to studies. The ARCS model categories are as
follows:
• Attention refers to learners' responses to
instructional stimuli provided by course content in
an AR/AI application. It increases their attention to
studies by using AR/AI applications while they are
studying.
• Relevance refers to assisting learners in connecting
prior learning experiences to the instructions
provided. The information provided in the
application is pertinent to the course.
• Confidence refers to the importance of setting high
expectations for their student's performance in the
learning task. They will understand the concept
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
179
Volume 21, 2022
clearly and have confidence in their subject if they
use AR/AI applications while learning.
• Learners will be satisfied at the end of the learning
process when they are allowed to practice new
knowledge or skills. They will be satisfied after
using the AR/AI applications for educational
purposes.
In this study, the ARCS model was used as a global
learning model that was created to be effective in
both professional learning situations, such as
corporate training, and classroom settings. In this
study, the AR used the ARCS model of Learning
Motivation Dimensions models to analyse how
augmented reality applications affect higher
education.
In this study, the ARCS model was used as a global
learning model that was created to be effective in
both professional learning situations, such as
corporate training, and classroom settings. In this
study, the researchers used the ARCS model of
Learning Motivation Dimensions models to analyse
how augmented reality applications affect higher
education.
Fig. 2: ARCS- Model – Proposed SEM Model
4 Result and Discussion
A questionnaire was issued to around 597 Google
students, and responses were categorized based on a
variety of factors, including gender, level of
education, and use of Virtual reality. According to
Table 1, respondents with ages ranging from below
18 to 18-21, 22-25, 26-29, and 30 and up
participated, accounting for 34 percent, 43.4 percent,
21.3 percent, 8.0 percent, and 21.6 percent,
respectively. Respondents with gender classifications
ranging from 441 male to 155 female and others 1
participated, accounting for 73.9 percent, 26.0
percent, and 0.2 percent, respectively; respondents
with ages ranging from below 18 to 18-21, 22-25,
26-29, Participants' educational levels were as
follows: 44 were Diploma students, 141 were Higher
Secondary students, 280 were
Of undergraduate students, 108 were Postgraduate
students, and 24 were Ph.D. Scholars, represented 7.4
percent, 23.6 percent, 46.9 percent, 18.1 percent, and
4.0 percent, respectively, in the survey.
Table 1. Demographic Profile of the respondents
(n=597).
Characteris
tics
Categories
Numbe
r of
respon
dents
Percenta
ge (%)
Age
below 18,
34
5.71
18-21,
259
43.41
22-25,
127
21.31
26-29,
48
8.01
30 above
129
21.61
Gender
Female
155
26.0
Male
441
73.92
Other
1
.22
Education
qualificatio
n
Diploma
44
7.43
Higher
Secondary
141
23.65
UG
280
46.96
PG
108
18.18
PhD
24
4.00
Table 2. Reliability study result for Impact of a
Virtual Reality Application on Higher Education
using the ARCS model of Learning Motivation
dimensions
Dimensions
Number of
Attributes
Cronbach’s
alpha
ARE
5.0
0.7712
ARA
5.0
0.7752
ARR
5.0
0.6972
ARC
5.0
0.77922
ARS
5.0
0.7712
ARHE
5.0
0.6832
ALL
TOTAL
Cronbach’s alpha
No. of. Items 30
0.9382
When doing research with Likert-type scales, it is
important to determine the Cronbach alpha value to
ensure accuracy and consistency. The influence of
the New Media and Higher Education scores is
depicted in Table 2 in terms of their variable and
overall dependability. According to George and
Mallery (2003: 231), Cronbach's alpha for all
measures is more than 0.931, indicating that the scale
has a high level of internal consistency. Furthermore,
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
180
Volume 21, 2022
as shown in Table 2, the alpha value for all
Cronbach's Ai Based Metaverse Technologies
Advancement Impact on Higher Education Learners
dimensions is 0.931, which is the highest possible
value. ARE- Augmented Reality Education app;
ARA- Augmented Reality Attention; ARR-
Augmented Reality Relevance; ARC- Augmented
Reality Confidence; ARS- Augmented Reality
Satisfaction; ARHE- Augmented Reality and Higher
Education; and overall analysis of reliability for the
impact of Augmented reality on perceptions are
0.771, 0.775, 0.697, 0.779, 0.771, and 0.683 for
ARE-
Augmented Reality Education app; ARA-
Augmented Reality
5 Hypothesis
The null hypothesis (H0) states that the postulated
model is well-fitting. According to the alternative
hypothesis, the proposed model does not provide a
satisfactory match.
Table 3. Summary of the model fit for the Structural
Equation Model .
Model Fit
Indices
Output/Resu
lt
Recommended
values
P value
0.1331
P-value >0.05
Chi-
square/deg
ree of
freedom
(x2/d.f.)
2.2531
≤ 5.00 (Hair et al.,
1998)
Comparati
ve Fit
index
(CFI)
0.9991
>0.90 (Hu and
Bentler, 1999)
RMSEA
0.0701
> 0.06 to 0.08 with
confidence interval
PCFI
0.0671
Sensitive to model
size
NFI
0.9981
≤ 1(Values close to
1 indicate a very
good fit)
PCLOSE
0.0001
< 05
Structural Equation Modeling (SEM) was used to
assess the model's fit with the data gathered. Using
AMOS version 23 in line with the recommendations
of Anderson and Gerbing, the structural model of the
survey instrument was tested to establish its accuracy
and validity (1988). For establishing the causal link
between variables and validating that the model is
consistent with the data set, structural equation
modelling (SEM) is very beneficial (Peter, 2011).
Table 4 displays the system fit index results from the
structural modeling of AMOS.
There are several qualities of a good template,
according to Gerbing and Anderson (1992). Chi-
square/DF value in Table 4 is 2.2533, which is less
than 5.00, showing that the two variables are well
matched. As an alternative to the chi-square test, the
data was analysed using Confirmatory Factor
Analysis (CFA) and the Normed Fit Index. Values
that are near to one indicate a very good overall
match, which is indicative of a very good match.
According to the PCLOSE value (0.000), which is
less than 0.005, and the Root Mean Square
Approximation Error (RMSEA) of 0.07, the model is
fully acceptable.
Fig. 3: Unstandardized Model Output
Fig. 4: Standardized Model Output
Indicated in Figures 3 and 4, To summaries, ARE
TOTAL stands for Augmented Reality Education;
ARA TOTAL stands for Augmented Reality
attention; ARR TOTAL stands for Augmented
Reality relevance; ARC TOTAL stands for
Augmented Reality self-assurance; ARS TOTAL
stands for Augmented Reality contentment; ARHE
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
181
Volume 21, 2022
TOTAL stands for Augmented Reality and Higher
Education.
Table 4. Regression Weights: Maximum Likelihood
Estimates
Inde
pen
dent
Rel
atio
nsh
ip
Dep
end
ent
Es
ti
m
at
e
S.
E.
C.
R
.
P
ARA
_TO
TAL
<---
AR
E_T
OT
AL
0.6
5
2
0.
0
42
15.
35
3
**
*
ARR
_TO
TAL
<---
AR
E_T
OT
AL
0.6
6
1
0.
0
43
15.
54
7
**
*
ARC
_TO
TAL
<---
AR
E_T
OT
AL
0.6
7
7
0.
0
48
14.
18
6
**
*
ARS
_TO
TAL
<---
AR
E_T
OT
AL
0.6
9
6
0.
0
45
15.
53
2
**
*
ARH
E_T
OTA
L
<---
AR
A_T
OT
AL
0.1
2
9
0.
0
66
1.9
36
.0
53
ARH
E_T
OTA
L
<---
AR
R_T
OT
AL
-
.00
8
0.
0
74
-
.10
5
.9
16
ARH
E_T
OTA
L
<---
AR
C_T
OT
AL
0.1
4
0
0.
0
65
2.1
35
.0
33
ARH
E_T
OTA
L
<---
AR
S_T
OT
AL
0.6
6
8
0.
0
63
10.
65
8
**
*
6 Essential Tests of Individual
Parameters
Table 5 displays the standardised coefficients and
relevant test results. An increase in the dependent or
mediating variable's standard regression coefficient
corresponds to an increase in the predicted variable's
standard regression coefficient by one unit. The
standardized estimate, standard error, and standard
error estimate are shown in Figure 5.) "Critical
Ratio" (also known as the Critical Ratio, abbreviated
C.R.), Column P denotes the chance that the
experiment was a total failure, as stated by the null
hypothesis.
Table 5. Standardized Regression Weights:
Maximum Likelihood Estimates
Independ
e nt
Relation
s
hip
Dependent
Esti
m ate
ARA_TO
T
AL
<---
ARE_TOT
AL
0.692
ARR_TO
T AL
<---
ARE_TOT
AL
0.697
ARC_TO
T AL
<---
ARE_TOT
AL
0.663
ARS_TOT
A L
<---
ARE_TOT
AL
0.697
ARHE_T
O
TAL
<---
ARA_TO
TAL
0.116
ARHE_T
O
TAL
<---
ARR_T
O TAL
-.007
ARHE_T
O
TAL
<---
ARC_T
O TAL
0.136
ARHE_T
O
TAL
<---
ARS_TO
T AL
0.639
Statistics about the model that was used to make the
predictions. Uniform equations may be used to
determine
the contributions of each predictor variable
to each outcome variable. The ARCS model of
Learning Motivation Dimensions structural
architecture was used to analyses the influence of an
Augmented Reality application on higher education,
as seen in Figure 2. Confirmatory factor evaluations
of 30 items were performed by 597 students who
used the ARCS model for learning motivation
dimensions to analyses an Augmented Reality
application's impact on higher education. The ARCS
model of learning motivation dimensions was used to
choose the questions from among the elements of
analysis on the impact of an augmented reality
application on higher education. Augmented reality
applications, as seen in Figure 2, play a significant
role in higher education learning.
7 Conclusion
A study of how Augmented Reality applications
affect higher education was conducted using the
ARCS model of Learning Motivation Dimensions
models, developed by the researchers. This study
verifies and assesses the effect of an Augmented
Reality application on higher education by utilising
the ARCS model of learning motivation factors and
the positive characteristics of using an augmented
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
182
Volume 21, 2022
reality app.
AR Education app increases learning engagement
and interest, and its learning is gamified. Its learning
has a significant positive impact on students, and it
helps to improve collaboration capabilities-
Interactive lessons in which all students participate
in the learning process.
Apart from classroom instruction, the AR Education
app allows us to learn practically. AR aids in
keeping a person's attention on a specific item or
topic for a longer period. AR animated content aids
learning by drawing our attention to the subject and
motivating us to study. AR technology can render
difficult-to-imagine objects and turn them into 3D
models, making it easier to grasp abstract and
difficult content. AR education app helps students
understand theorizing knowledge and its interaction
draws students' attention and helps them understand
the subject better and faster. When compared to
traditional methods of learning, AR education app
learning garners more attention. Through
visualisation and total immersion in the subject
matter, the AR App can help you achieve better
results. AR App, in addition to
schooling/college/professional training, can greatly
benefit from the use of AR. The AR App assists the
student in understanding the concept practically. The
AR App applies to all levels of education and
training. There is also no need for a full curriculum
with the AR App. It has the potential to be even
more effective in supplementing current pedagogical
materials. AR Apps provide numerous opportunities
for diversifying and shaping boring classes. AR
Apps classes are very interactive, which boosts
learning confidence. AR Apps allow students to
learn even after class and outside of the classroom.
The concept is easily understood thanks to the
gamification of AR Apps. In comparison to
traditional education AR apps for learning more
clearly understand the concept. AR applications help
to provide students with new opportunities to learn
how to communicate and collaborate for higher
education institutions.
8 Discussion
Augment Reality technology has a bright future
ahead of it and lots of space for improvement,
according to findings from an inquiry into the
technological characteristics of Augment Reality
technology in higher education. Using a smartphone
as a learning platform might help students learn and
retain new information by making it easier for them
to interact
with it. Educators and industry leaders will
work together
to figure out the best methods to
implement qualities in the classroom. An
implementation may be excessively expensive since
individual schools lack the necessary cash and rely on
the subsidies that have been established, especially
NGO-based schools/Colleges, government-aided
schools, and colleges. In education, the emerging
reality is a useful tool that offers a wide range of
alternatives, but there is still much room for growth
and expansion. Educators should exercise caution
while implementing Augmented Reality technology
in the classroom so as not to restrict the capacity of
teachers and students to utilise multimedia teaching
approaches. To establish the finest possible
combination of new media technology with higher
education, teachers' capacity to use augmented
reality technology must be increased.
9 Future Work
In future work, we will use the ARCS model to
construct AI-based metaverse technologies that have
a big participation impact on learners in higher
education. The 597 participants are a restriction for
this study. The research findings are so severely
circumscribed that a sample this small cannot
adequately represent the entire body of work. The
value will increase with a larger sum. This study was
conducted in a city to further analyse the planned
project for a suburb where the colleges and
institutions are located. To increase a learner's level
of engagement in the learning process, we will also
investigate expanding our suggested model to
include a social network-based learning
environment.
References:
[1] Burton, E. P., Frazier, W., Annetta, L., Lamb, R.,
Cheng, R., & Chmiel, M. (2011). Modeling
Augmented Reality Games with Preservice. Jl. of
Technology and Teacher Education, 19(3), 303-
329.
[2] Danakorn Nincareana, Mohamad Bilal Alia *,
Noor Dayana Abdul Halima , Mohd Hishamuddin
Abdul Rahmana, Mobile Augmented Reality: the
potential for education, www.sciencedirect.com
[3] Ganguly, P.K.: ‘Teaching and Learning of
Anatomy in the 21 Century: Direction and the
Strategies’, The Open Medical Education Journal,
2010, 3, (5-10)
[4] Höllerer, T.H., and Feiner, S.K.:
‘Telegeoinformatics: Location-Based
Computing and Services.’: ‘Chapter 9: Mobile
Augmented Reality’ (Taylor & Francis Books
Ltd., 2004)
[5] Kesim M and Ozarslan Y 2012 Augmented
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
183
Volume 21, 2022
reality in education: current technologies and
the potential for education Procedia-Social and
Behavioral Sciences 47 297-302
[6] I. C. S. da Silva, G. Klein, and D. M. Brand ao,
“Segmentedand detailed visualization of
anatomical structures based on AR for health
education and knowledge
discovery,”Advancesin Science,
vol.2,no.3,pp.469–478,2017
[7] M. Akc ayır and G. Akc ayır, “Advantages and
challenges associated with AR for education: a
systematic review of the literature,”Educational
Research Review,vol.20,pp.1–11,2017
[8] Paalman, M.H.: ‘New frontiers in anatomy
education’, The Anatomical Record, 2000, 261,
(2), pp. 47
[9] Hwang, G. J., & Chien, S. Y. (2022). Definition,
roles, and potential research issues of the metaverse
in education: An artificial intelligence
perspective. Computers and Education: Artificial
Intelligence, 3, 100082.
[10] H. Huang, G.J. Hwang, S.C. Chang
Facilitating decision making in authentic contexts:
An SVVR-based experiential flipped learning
approach for professional training Interactive
Learning
Environments (2021), 10.1080/10494820.2021.200
0435.
[11] I. Wohlgenannt, A. Simons, and S. Stieglitz,
“Virtual reality,” Business & Information Systems
Engineering, vol. 62, no. 5, pp. 455–461, 2020.
[12] J. Díaz, C. Saldaña, C. AvilaVirtual world as a
resource for hybrid education Int. J. Emerg.
Technol. Learn.(iJET)., 15 (15) (2020), pp. 94-109
[13] J. Fromm, J. Radianti, C. Wehking, S. Stieglitz, T.
A. Majchrzak, and J. vom Brocke, “More than
experience? -on the unique opportunities of virtual
reality to afford a holistic experiential learning
cycle,” The Internet and Higher Education, vol. 50,
p. 100804, 2021.
[14] J. Radianti, T. A. Majchrzak, J. Fromm, and I.
Wohlgenannt, “A systematic review of immersive
virtual reality applications for higher education:
Design elements, lessons learned, and research
agenda,” Computers & Education, vol. 147, 2020.
[15] J. Radianti, T. A. Majchrzak, J. Fromm, S. Stieglitz,
and J. Vom Brocke, “Virtual reality applications for
higher educations: A market analysis,” in 54th
HICSS, 2021.
[16] Keller, J. M. (1983). Motivational design of
instruction. In C. M. Reigeluth (Ed.), Instructional-
design theories and models: An overview of their
current status. Lawrence Erlbaum Associates.
[17] Keller, J. M. (1987). Development and use of the
ARCS model of motivational design. Journal of
Instructional Development, 10(3), 2 – 10.
[18] Keller, J. (2016). ARCS Model.
[Webpage]. https://www.arcsmodel.com
[19] Kemp, J., & Livingstone, D. (2006). Putting a
Second Life “Metaverse” skin on learning
management systems. In Proceed- ings of the
Second Life education workshop at the Second Life
community convention (Vol. 20). CA, San
Francisco: The University of Paisley
[20] M. Bourlakis, S. Papagiannidis, F. Li Retail spatial
evolution: Paving the way from traditional to
metaverse retailing Electronic Commerce
Research, 9 (1) (2009), pp. 135-148
[21] Mutterlein, “The three pillars of virtual reality? ¨
investigating the roles of immersion, presence, and
interactivity,” in 5st HICSS, 2018.
[22] P. Pande, A. Thit, A. E. Sørensen, B. Mojsoska, M.
E. Moeller, and P. M. Jepsen, “Long-term
effectiveness of immersive vr simulations in
undergraduate science learning: Lessons from a
media-comparison study.,” Research in Learning
Technology, vol. 29, 2021.
[23] Paalman, M.H.: ‘New frontiers in anatomy
education’, The Anatomical Record, 2000, 261, (2),
pp. 4
[24] Pereira, C. E., Paladini, S., & Schaf, F. M. (2015).
3D autosyslab prototype-a social, immersive and
mixed reality approach for collaborative learning
environments. International Journal of Engineering
Pedagogy (iJEP), 2(2),
15. https://doi.org/10.3991/ijep.v2i2.2083
[25] Reyes, C. E. G. (2020). Perception of high school
students about using Metaverse in augmented
reality learning experiences in mathematics. Pixel-
Bit: Media and Education Magazine, 58, 143–159.
[26] S.M. Park, Y.G. KimA metaverse: Taxonomy,
components, applications, and open challenges
IEEE Access, 10 (2022), pp. 4209-4251
[27] Tlili, A., Huang, R., Shehata, B. et al. Is Metaverse
in education a blessing or a curse: a combined
content and bibliometric analysis. Smart Learn.
Environ. 9, 24 (2022).
https://doi.org/10.1186/s40561-022-00205-x.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
WSEAS TRANSACTIONS on SYSTEMS
DOI: 10.37394/23202.2022.21.19
Bhavana S., Vijayalakshmi V.
E-ISSN: 2224-2678
184
Volume 21, 2022
