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Benefits and applications of virtual reality (VR) in higher education have seen much interest both from research and industry. While several immersive VR applications for higher education have been described, a structured analysis of such applications on the market does not exist. We use design elements from research for applying VR in higher education to analyze available VR apps. The analyzed VR applications were acquired from pertinent online stores to capture the market’s state. We analyze the current picture of the available apps by categorizing them based on design elements and learning content. The aims are to map what types of apps are available, to study what expected types cannot (yet) be found, to compare the current state of the literature and the educational VR app market, as well as to scrutinize the most frequently used design elements for VR in education.
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Virtual Reality Applications for Higher Educations: A Market Analysis
Jaziar Radianti and Tim A. Majchrzak
University of Agder,
Kristiansand, Norway
Jennifer Fromm and Stefan Stieglitz
University of Duisburg–Essen,
Duisburg, Germany
Jan vom Brocke
University of Liechtenstein,
Vaduz, Liechtenstein
Benefits and applications of virtual reality (VR) in
higher education have seen much interest both from
research and industry. While several immersive VR
applications for higher education have been described,
a structured analysis of such applications on the market
does not exist. We use design elements from research for
applying VR in higher education to analyze available
VR apps. The analyzed VR applications were acquired
from pertinent online stores to capture the market’s
state. We analyze the current picture of the available
apps by categorizing them based on design elements
and learning content. The aims are to map what types
of apps are available, to study what expected types
cannot (yet) be found, to compare the current state of the
literature and the educational VR app market, as well as
to scrutinize the most frequently used design elements
for VR in education.
1. Introduction
Head-Mounted Display (HMD) Virtual Reality (VR)
is steadily gaining popularity [1, 2]. It is not merely
used for entertainment but also for education purposes
for several reasons. VR is immersive and can bring
students into realistic scenes and experiences, which
may not be achievable in the real world [3]; think, e.g.
of experimentation in harmful environments. The visual
experience can be strengthened with audio. Moreover,
VR can be designed in a very interactive way, allowing
the users to touch, grab, assemble-disassemble objects,
moving around in the virtual world and many other
possibilities [4]. Some universities have explored and
initiated “Accelerated Immersive Education” to open up
the possibilities to create a global classroom curriculum,
allowing students from different parts of the world to
access the same learning materials [5].
Immersive VR technologies become more
accessible, both considering those that require high
budgets – such as Oculus Quest – and those for low
budgets – such as Google Cardboard [6, 7]. However,
it has not been systematically analyzed what kinds of
apps are available on the market that support learning
in the context of higher education. To the best of our
knowledge, no comprehensive market analysis exists,
yet. Therefore, we set out to close this gap. We explore
the VR app market to understand the current situation
of the possibility to adopt VR in teaching.
Consequently, the main contribution of this article
is the first overview of the app market for immersive
VR in higher education. We expect this to be a
valuable resource for researchers and input to future
theory building papers in the field as well as relevant
to educators in practice. This article also compares
the current state of the art of HMD applications in
the literature and the reality of app availability in the
educational VR app market.
The remainder of this article is structured as follows.
In Section 2, we discuss previous studies of VR in
the education app market. We then elaborate on our
data sources and methodology in Section 3. Section 4
presents our frameworks for analysis. The results from
our market analysis are given in Section 5 before we
discuss them in Section 6. Section 7 draws a conclusion.
2. Previous Works
We found several systematic literature reviews of
VR applications in education [8, 9, 10, 11, 12]. For
example, Freina and Ott [8] analyzed scientific articles
with regard to the advantages and drawbacks of VR
use in education. Kavanagh et al. [10] instead focused
on application areas and motivations of VR use in
education. The systematic review of Chavez and Bayona
[9] analyzed the current state of the literature with regard
to design elements of educational VR apps and their
Proceedings of the 54th Hawaii International Conference on System Sciences | 2021
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effects on the learning process. Wohlgenannt et al. [11]
focused on scientific literature about VR applications
in higher education and created a systematic mapping
of design elements implemented to teach different
types of learning content. The most recent systematic
literature review analyzed 38 scientific articles about
VR applications in higher education with regard to
technology type, applied learning theories and research
methods, application domain, learning content, and
design elements [12]. The authors provide a systematic
mapping of fourteen design elements implemented to
teach different types of learning content [12]. Both,
Wohlgenannt et al. [11] and Radianti et al. [12], suggest
to extend their work by conducting a comprehensive
market analysis of educational VR apps.
Our literature review revealed that there is indeed a
research gap in this regard. We found several analyses of
mobile app markets with a focus on education; however,
there was no specific focus on VR apps [13, 14, 15, 16].
For example, Shuler [13] analyzed the 100 top-selling
paid apps in the education section of the iTunes App
Store with regard to target age, subject, and price.
Hayes [14] collected 1 076 educational mobile apps
listed on – a website to help educators find
educational digital resources. The author focuses on the
potential of mobile apps to support 21st century skills
such as creativity, critical thinking, communication, and
collaboration. Penchenkina [15] identified 117 mobile
apps affiliated with Australian universities in the Google
Play Store and proposed a typology of mobile apps
in higher education based on their primary purpose,
secondary purpose, and design elements. The most
recent market analysis analyzed the top 10 premium and
top 10 free math and literacy preschool apps from the
Apple App Store, Google Play Store, and Amazon with
regard to their educational features [16].
A search for market analyses focusing on both –
VR as a technology and education as an application
domain – yielded only scarce results [17, 18]. Stojˇ
c et
al. [17, 18] present 16 Google Cardboard VR apps and
describe how these can be used in geography education.
Karsli and Karsli [18] searched the Steam Store, Google
Play Store, Apple App Store, and the Oculus Store for
VR apps that were developed for language learning. The
authors identified 15 apps and examined these in terms
of their general features, the language skills they aim
to develop, and the language learning activities [18]. It
becomes apparent that current market analyses of VR
apps in education are limited to a small number of
apps in a specific education domain (i.e. geography,
language learning). With our study, we contribute a
comprehensive market analysis of VR apps in education.
3. Data Sources and Methodology
In the following, we first explain how we selected the
app markets included in our analysis. Then, we explain
our filtering approaches for selecting apps, starting with
the semi-automated and followed by the manual one.
Eventually, we elaborate on our coding process.
3.1. Selection of App Markets
To understand the immersive VR app markets, we
explored the well-known app stores, which was done
until March 2019. We selected three main VR app
stores, i.e., Steam1, Vive2, and Google Play3. The
web crawl technique [19] was used to systematically
browse the web, identify the hyperlinks in the pages and
automatically add them to the list of URLs to visit each
market. We used the Python package Beautiful Soup 4.
For the Vive and Google Play stores, which
specifically focus on games, we crawled all apps
available by March 2019, while for the Steam Store, we
only crawled the VR apps. Note that we were aware of
other VR app stores such as Oculus, iTunes Apple, and
Play Station. However, these stores prohibit crawling
activities (and provide no free API access which would
otherwise serve our needs to identify matching apps),
and hence we did not review them. We deemed existing
markets to be sufficient as many VR mobile apps
available in iTunes were likely to be available in Google
Play. Likewise, many VR apps available in Oculus may
have been covered in either Steam or Vive, or both. For
example, the app Star Chart for Oculus consisting of a
real-time simulation of the visible stars from the Earth,
planets, and 88 star constellations is accessible in Vive
and Steam. Most accessible VR apps in the Play Station
store are entertainment-oriented.
We obtained 5 632 apps in total. The datasets were
organized in a spreadsheet, consisting of information
on the source of the market, URL link to each
identified app, app name, and the description of the
app. To proceed with the market analysis, we conducted
both semi-automatic and manual filtering processes to
include and exclude the apps.
3.2. Semi-Automatic Approach
A two-step semi-automatic approach for inclusion
and exclusion of apps was conducted. First, we ran an
inclusion process that was only applied to the Steam
results, as we had included all games in the crawling
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process, and not the VR-apps only. The inclusion
keywords were virtual reality,VR,oculus,
vive and immersive. The screening process was
done by developing a simple script that would go
through the description text and mark the app being
relevant or not relevant.
Second, the inclusion process that was valid for
all apps from the three markets where we used
more intuitive keywords that would fit our goal,
i.e., to find education- or learning-oriented apps.
Thus, we adopted the following keywords for this
second semi-automatic process: learn,learning,
educate,train,trained,training, and
Third, we ran an exclusion process. To achieve
this, we carried out a content analysis of all apps
from the three markets. To understand which
relevant keywords could be used for including the
apps, we used the software KH Coder 3, which
supports text mining and quantitative content analysis
[20]. Several pre-processing activities were done,
such as removing punctuation marks, stop words,
and converting conjugated or inflected adjectives and
verbs into their word stem and ignoring prepositions,
adjectives, and adverbs. The tool helped us to extract
clusters of words that frequently appeared together. The
result of this process was a list of word clusters, which
then were selected in a way that it allowed us to find
good enough keywords for inclusion criteria.
The selections of the following keywords were
adequate to exclude irrelevant apps: sairento,
regatta,marine life,air combat,space
bit attack,fightttris,legion,janus,
sandbox,adventure game,3D printing,
sport,soccer,jam studio,railway,
horror,mix reality,baskhead training,
sailing,chinese cook,fighting, and fun
game. In all these three semi-automatic processes,
a quick human checking was performed to ensure
excluded apps were truly not relevant. The results
of the crawling and semi-automatic filtering can be
summarized as follows in Table 1.
Table 1. Semi-automatic checking results
Stages Steam Vive Google Total
Crawling results 3 986 1 396 250 5 632
Inclusion (Steam) 3 291 4 937
Inclusion (All) 521 93 41 655
Exclusion (All) 370 161 41 572
3.3. Manual Filtering Approach
For the next process, we merged all results into a
single list consisting of 572 VR apps. In the manual
process, the authors manually read all app descriptions
and excluded all apps that were not relevant. It was
done by three parties, which categorized the same list
as “VR app for education”, “questionable”, and “not
relevant”, and compared the results. Any discrepancies
were discussed until a single option was agreed: to
include or to exclude the app. This process was
considered as a cross-validation process, ensuring the
list was better representing what we looked for, and
eliminating bias and misinterpretation. In addition, we
removed duplicates, because after merging the apps
from different stores, some duplicates were found.
The final list ready for coding contained 120 apps, as
illustrated in Table 2.
Table 2. Manual checking results
Stages # of Apps
Merged list after inclusion-exclusion 572 Apps
Duplication check 477 Apps
List of apps ready to code 120 Apps
3.4. Coding Process
The coding process was carried out to classify the
apps into meaningful categories. A series of frameworks
organized as a concept matrix [21] has been prepared
to categorize the apps. Our goal was to identify the
following: the application areas, the design elements,
and the learning contents, as presented in Section 4.
The coding process was done by two co-authors who
went through the app descriptions and each app URL
in our list, observed the comments from the users of
the apps, and watched the video trailer of each app.
These two persons who went through all the apps also
were a way for ensuring intercoder-reliability. We found
some discrepancies on interpreting the categories, and
we solved it through a discussion with all co-authors
until agreed categories were achieved.
4. Framework
We applied and extended the frameworks for VR
design elements and learning contents proposed by
Radianti et al. [12], which were developed to understand
the design elements and learning contents of VR that
have been proposed in the literature. As argued in
Section 2, it is the most recent and at the same
time most comprehensive paper proposing such a
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classification scheme. However, in this work, we did
some modifications, expanded some definitions, and
renamed some categories based on the new elements
discovered in the app market. These cater for the
differences between scientific literature and situation on
the app markets, as well as to changes in the rapidly
evolving field of VR in education. The modification of
the definitions are signified with italic text.
4.1. Design Element Framework
Realistic surroundings: The virtual environment is of
high graphic quality and has been designed to replicate
a specific environment in the real world.
Passive observation: Students can look around the
virtual environment. This design element also applies
to applications in which users can travel along a
pre-defined path and look around while doing so.
However, they are neither able to move around on their
own nor to interact with virtual objects or other users.
Moving around: Students can explore the virtual
environment on their own by teleporting or flying
Basic interaction with objects: Students can select
virtual objects and interact with them in different ways.
This includes retrieving additional information about an
object in written or spoken form, taking and rotating it,
zooming in on objects to see more details, and changing
an object’s color or shape. Some apps allow using hand
gestures to interact with objects.
Assemble, disassemble, and dissect objects: Students
can select virtual objects and put them together,
including the creation of new objects by assembling
several individual objects. On the contrary, the students
can also disassemble objects to learn about small parts
of the objects such as machines, or dissect an animal
such as a frog, to learn about its anatomy.
Interaction with other users: Students can interact
with other students or teachers and attend a virtual
class. The interaction can take place in the form of
an avatar and via communication tools such as instant
messaging or voice chat. Some designs incorporate the
real-time communication feature. This design element
also includes the possibility of students visiting each
other’s virtual learning spaces.
Role management: The VR application offers different
functionalities for different roles. A distinction is
made between the role of a student and the role
of a teacher. For a teacher, the VR application
offers extended functionalities, such as assigning and
evaluating learning tasks or viewing the learning
progress of students.
Screen or result sharing and virtual presentation:
The VR application allows students and teachers to
stream applications and files from their local desktop
onto virtual screens. This allows them to share and
edit the learning content from their local desktops with
other users in the virtual environment, or to present the
content directly in the virtual world.
User-generated content: Students can create new
content, such as 3D models, and upload this new content
to the virtual environment. This design element also
applies when the user-generated content can be shared
with other users so that they can use it in their virtual
environment as well. This design element does not apply
when students can only access virtual objects that were
created by developers and provided by a library in the
virtual environment.
Instructions: Students have access to a tutorial or
to instructions on how to use the VR application and
how to perform the learning tasks. The instructions
can be given by text, audio, or a virtual agent. The
virtual agents can be a virtual instructor or a virtual
narrator. The text instruction can be presented in a
virtual dashboard, or virtual presentation tools such as
TV, Video or projector.
Interactions with a virtual agent: Students can talk
and discuss with a virtual agent when learning. It is
different from the instruction design element where the
virtual agents only provide instructions. This element is
especially used for language learning.
Immediate feedback: Students receive immediate
textual, auditory, or haptic feedback. The feedback
informs students about whether they have solved the
learning tasks correctly and whether interactions with
virtual objects were successful.
Knowledge test, questionnaire and exercise:Students
can check their learning progress through knowledge
tests, quizzes, or challenges.
Virtual rewards: Students can receive virtual rewards
for successfully completing learning tasks. Students
can be rewarded virtually by receiving achievements,
badges, higher ranks on a leader board, and by
unlocking exclusive content, such as hidden rooms or
additional learning content.
Making meaningful choices: Students learn in the
virtual environment through participating in a scenario
(role-playing) that can end in different ways. In this
scenario, they have to make decisions that affect the
outcome of the scenario. This design element does not
apply when the students’ decisions have no influence on
the outcome of the scenario.
Elevated Challenges: Students can receive more
advanced learning challenges, as soon as they complete
a certain task.
Alternative learning venue: Students can enter different
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types of learning venues, depending on the learning
needs, for example, to enter a big auditorium with a lot
of audiences to train public speaking.
4.2. Learning Content Framework
Analytical and problem-solving: Whether the use of
VR can encourage students to improve their analytical
skills, such as collecting and analyzing data, writing
computer programs, or making complex decisions.
Communication, collaboration, soft skills: Whether
the use of VR is intended to strengthen the students’
ability to work in a team or whether students can
improve their communication skills (e.g., presenting
in front of an audience). This category also
includes soft skills, such as management and leadership
Procedural–practical knowledge: Where the use of
VR aims to assist students with internalizing procedures,
such as knowing how to perform a surgery or how to
perform firefighting procedures.
Declarative knowledge: Where the use of VR is
intended to help students memorize factual knowledge
(e.g., theoretical concepts and scientific principles).
This includes, for example, learning the names of
planets in our solar system.
Learning a language: Where the use of VR aims to
improve students’ foreign language capabilities, such as
reading, listening, writing, and speaking.
Behavioral impacts: Where the use of VR aims
to change the behavior of students by, for example,
improving their learning habits, awareness of mobbing,
and compliance to rules.
5. Results and Analysis
Recall that this work extends Radianti et. al.’ [12]
literature review, but extends the proposed framework
for the market analysis (as explained in Section 4).
Results are linked to this work as a point to compare
and to understand the gap between the findings in the
literature and in the VR app markets.
5.1. Classification Results
When investigating the teaching areas of VR,
we identified that procedural-practical and declarative
knowledge development jointly occupy the maximum
(and almost identical) portion of the learning outcomes
in both analyses. In their literature review, Radianti
et al. [12] found that 60% of the learning contents
teach developing such knowledge. In contrast, our
market analysis identified that a similar learning
outcome was targeted by 68.4% of the examined apps.
0%1% 1%1%1% 1%1%1%2% 2%2%2% 2%2%2%2% 2%3%3%3%
4%5% 6%
Surgical Medicine
Computer Science
Earth Science and Geology
Biochemistry and biotechnology
Business and Management
Restaurant and Bar
Biology and Zoology
Figure 1. Application domains (n=136)
However, when individually analyzed, such knowledge
development criteria exchange priorities in literature
and market analysis. The literature review prioritized
procedural-practical knowledge (34%) development
over declarative (26%), whereas our market analysis
emphasized more on declarative knowledge (43%)
development than procedural-practical (25.4%). Other
criteria kept identical ranking in both studies, although
some numerical ups and downs were articulated.
In the literature review, Radianti et al. [12]
summarized 17 application domains of VR that included
topics from Science, Art, Safety, and Language. Along
with these topics, our market analysis recognizes 10
more application domains broadly from Sport, History,
Training, Business, Management, and so on. Figure 1
demonstrates the application domains identified from
the market analysis. Radianti et al. [12] articulated
Engineering (24%) as the most concentrated application
domain in the review, but our market analysis shows
that most educational apps are developed for serving
needs in the Biology and Zoology domain (18%). In the
VR app stores, the app intended for Computer Science
domain is not so popular. In the study of Radianti et al.
[12], 10% of the reviewed articles were from Computer
Science in contrast to 1% of the apps in the app stores;
Astronomy achieves greater attention in practice (from
7% to 13%).
However, regardless of the differences in terms of
magnitude of similar subjects both in market analysis
and literature, the application domains vary to a great
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0,5% 0,5% 0,7% 0,9% 1,2%
2,6% 2,6%
4,2% 4,7% 5,2% 5,2%
Interaction with virtual agent
Elevated challenges
Making meaningful choice
Role Management
Interaction with other user
User Generated Content
Alternative learning venue
Knowledge test/ questionnaire/exercises
Assemble-Disassemble dissection
Immediate Feedback
Virtual Rewards
Screen/Result sharing/virtual presentation dashboard
Passive Obsrvation
Moving around
Basic Interaction
Realistic Surrounding
Figure 2. Design elements (n=426))
extent in the market. Therefore, the percentage of
the application domains are more equally distributed,
apart from the top five subjects. This may indicate
diversities in future trends in educational VR. We notice
that in our market analysis, health-related domains such
as medicine and surgical medicine are lower than in
the findings of Radianti et al. [12]. Moreover, no
application in Nursing domain, while, the literature
review [12] reported a 5% share of this domain in the
After examining the collected apps, we identified
three new design elements in addition to the ones
reported by Radianti et al. [12]: interaction with
virtual agents (0.5%), elevated challenges (0.5%), and
alternative learning venues (2.6%). The authors reported
that basic interaction (24%) and realistic surroundings
(17%), were the most frequently used VR design
elements for higher education. Our analysis provided
a similar outcome but prioritized realistic surroundings
(19%) over basic interaction (18.1%). Figure 2
illustrates the overall distribution of the elements used
for creating VR applications.
For effective VR support in higher education, the
finding indicates that creating real-life surroundings is
as vital as incorporating basic interactions with the
operational environment. With a little increase in
the contributing percentage, issues with instructions
ranked third in both analyses. However, the market
analysis prioritized enabling moving around (12.4%)
over immediate feedback (4.7%), which was reversely
reported in the literature review. Therefore, our study
reveals that VR support will be more interactive if the
user can move with the VR-devices rather than just
receiving some immediate feedback. The significant
hype of virtual rewards (from 2% to 5.2%) and screen
sharing (from 1% to 5.2%) indicates their importance to
include in VR applications for higher education.
5.2. Mapping Results
The mapping of learning content and design
elements is visualized in Figure 3 (next page).
Declarative knowledge has been employed in most
of the identified learning contents of the VR apps.
Elements, such as realistic surroundings, basic
interaction, moving around, and instructions, need
a better theoretical understanding of the subject
matters for designing related VR apps. However, we
have not evaluated whether these design elements
actually improve procedural-practical skills. Moreover,
out of the above-mentioned design elements, basic
interaction, instructions, and realistic surroundings
contribute to developing communication, collaboration,
and soft skills. Passive observation, along with the
influential design elements for previous learning
content, influences behavioral impacts related learning
outcomes. It is mostly observed for learning languages.
The mapping of learning content and application
domains is visualized in Figure 4. Apps in
Safety and Training domains are mostly tailored
to develop procedural-practical knowledge, whereas
apps in Biology and Zoology, Astronomy provide
declarative knowledge. Although teaching analytical
and problem-solving skills is essential to Engineering,
it is prevalent for Safety, Mathematics, Business and
Management. In theory, VR should support the
important learning outcomes for different application
domains, but we have no objective data about the
actually needed learning outcomes in each application
We also found several gaps in the markets. First,
all identified apps were claimed to be designed for
education, however, we could not identify what kind
of learning theories have been used to guide the app
development. Therefore, it was not yet completely
clear, how far the VR apps available in the app
stores could actually support the learning needs of
the students. Second, some learning contents were
only found in limited application domains, especially
those that targeted behavioral impacts and language
Page 129
128 10 912 27 22 4 4 12 24121
642 8 3 8 8 51 28 539 11 16 191
414 4 1 7 5 10 12 525411
510 22253910 62314
67 23176123 12
72 112 331
Declarative Knowledge
Analytical and Problem
Solving Skills
Collaboration and Soft
Behavioral impacts
Learning language
Passive Obsrvation
Basic Interaction
Interaction with other
Interaction with virtual
Immediate Feedback
Virtual Rewards
Realistic Surrounding
User Generated Content
Role Management
Moving around
Knowledge test/
Screen/Result sharing/
virtual presentation
Making meaningful
Alternative learning
Elevated challenges
Design Elements
Learning Content
Figure 3. Mapping of learning content and design elements
9 12 1 18 11 61245
4 1 17 24 3633113 11 3 4351 1
51 2 111 331 11 32
1 2 2 3 1 1 1 3 2
1 2 1 1 1 1
3 1
Procedural-Practical Knowledge
Declarative Knowledge
Analytical and Problem Solving Skills
Communication, Collaboration
and Soft Skills
Behavioral impacts
Learning language
Computer Science
Biology and
Earth Science and
Surgical Medicine
Biochemistry and
Restaurant and
Business and
Learning Content
Application Domain
Figure 4. Mapping of learning content and application domains
learning. These two categories were identified but were
not the most common reasons why VR apps were made.
Perhaps, changing behaviours or learning language
are still not yet areas which developers consider be
meaningful. However, we found one app that focused
on biology and environment, but in the spirit, the app
teaches users for changing the attitude toward certain
animals that are important in the food supply chain, as
explained in the introductory narration of the app.
6. Discussion
Based on the analysis of the app market with the
help of the framework, we discuss our results. First,
we name lessons learned from the analysis. Second, we
give recommendations for the adoption of VR apps by
educators and for developers of VR apps for education.
Third, we discuss limitations of our work. Fourth, we
sketch directions for future research.
6.1. Lessons Learned
Our analysis of the market has led to several
insights. First, one of the keys for successful VR
apps for education is to have adequate information on
the usage and benefits of the app. The majority of
identified VR apps in this study adopted carefully the
Instruction design element, which is apparently a key
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for a successful VR app. This design element can
be manifested in various forms, ranging from virtual
narration, virtual agent, virtual dashboard, and audio
and text tutorials. The importance of the Instruction
design element, was not so obvious in the academic
literature [12].
Second, VR apps for computer science domain
are not so popular in the market compared to the
literature findings. It seems that such apps are frequently
developed in research. Thus, Computer Science might
not actually be one of the most meaningful application
domains for educational VR. One of the possible
explanations is that the VR apps developed in the
literature can be biased by the subjects of the authors
– likely researchers in this field who typically create
software artifacts as part of their work anyway. From
the market perspective, it is not yet so intuitive and
common that people would go to the VR app stores to
find e.g. how to learn coding and programming. Until
now, coding skills can be improved by using other forms
of digital learning tools instead of HMD VR.
Third, we have analyzed the selected 120 apps for
education from the VR app stores. The educational
content of these apps looks promising, but only few are
really deep (i.e. comprehensive, sophisticated) enough
that the learning process would not be concluded in just
one session. Many reviewed apps seem to target one
time use by design. Thus, they are rather supplements
to enhance the understanding of students on a specific
topic. This might be owed to the immaturity of the field,
and to the experimental nature of many apps.
Fourth, high-quality, HMD-based VR learning
materials for higher education in fact are not always
offered through the VR app stores, e.g. for medicine
and nursing, safety and engineering domains. Such apps
use direct marketing, and they are often quite costly or
require a special agreement with the potential users.
Fifth, results of our market analysis only partly align
with findings from the scientific literature (cf. Sections 2
and 5). This could be explained by the novelty of the
field and by the rapid pace with which it is evolving;
however, it also hints to a need for additional research.
6.2. Recommendations
Based on the insights of this market analysis, we
have the following suggestions concerning possible
adoption of immersive VR in higher education, both for
lecturers and for VR developers.
Educators need to be aware that the current
possibilities to use VR in higher education are limited.
The technology allows for abundant possibilities and
examples of sophisticated apps exist; however, there
is no acknowledged way how to decide on the means
of virtualizing an existing course, there are no general
guidelines for app usage, and there is not much evidence
for effectiveness criteria for apps. All of this is owed to
the immaturity of the field combined with the relatively
low level of scientific coverage, which arguably is
strongest regarding the technological underpinnings. At
the same time, it is undeniable that VR offers the
chance for profound (positive) changes to education.
Our first recommendation is, thus, to embrace these
possibilities, to be bold in following ideas, yet to refrain
from unrealistic expectations. Although – as evidences
by papers like this – there is research that tries to
provide advise, adopting VR for a course will remain
experimental for the near future.
Educators need to also be aware of the limited scope
of apps offered in app markets. At the same time,
these app markets offer many VR apps not intended for
education. Our second recommendation is, thus, to be
open minded. Even if existing educational apps offer
limited functionality, they can serve as inspirations;
VR apps built for entertainment can showcase the
technology and help devising serious apps.
The third recommendation is to be patient.
Obviously, the field is evolving. If educators cannot
find the tools, the guidelines, or the evidence they
need, it would not be right to despair. Rather, it
is likely that revisiting the same VR teaching idea a
year later would reveal new possibilities, maybe even
an existing app. Developers need to be aware that
educators might neither have a complete understanding
of the technological underpinnings of their ideas nor
of the progress of the technology. Our fourth
recommendations is to work closely together. While
this would be a common value in software engineering,
putting particular emphasis on requirements engineering
is advisable.
Due to the missing theory and particularly the gaps
of understanding of didactic aspects of VR apps in
education, developers need to be agile. If educators
work exploratory and experiment with ideas, developers
need to follow pace. Apps that allow tailoring,
customization, frequent updates, and if need be a full
redesign should be favoured, even if they come with less
functionality than an app built in a more static fashion
could have. Therefore, the fifth recommendations is to
allow for as much change as possible.
6.3. Limitations
There are three kinds of limitations relevant for
our work. First, there are limitations to the design
and execution of our analysis. We only identified
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apps from the popular VR app stores. Moreover, we
could not crawl all VR markets such as Apple’s App
Store and Sony’s PlayStation Store, as crawling was
prohibited in these two markets. Furthermore, the
store markets may not offer an educational-professional
app for teaching medical students such as a tool for
conducting specific surgery procedures. Such apps
could be commercially marketed and directly offered to
the – relatively small – base of institutions that could
reasonably offer them to students. However, literature
has cited professional VR tools for conducting training
in the medical domain [22, 23]. Possibly apps are
too targeted to a specific audience, are a proprietary
solution, or circulate in a limited environment. In
these cases, access through the app stores may be
undesirable. Examples are the Osso VR platform5that
use HMD for medical training, and XVR simulation6for
emergency management. In other words, professional
VR apps for education that use direct-selling methods
are not covered in our survey. The two examples are
procedural-practical oriented apps. There may be more
similar apps targeting the same learning contents, which
are not fully captured from just surveying the VR apps
in the popular markets, and indicate the opposite: the
majority of accessible apps have declarative-knowledge
as learning content. This study focuses on apps that
use immersive VR technologies (HMDs). There may
be more advanced learning apps for higher education
using non-immersive technologies. It is also impossible
to know the barriers from the students who use these VR
Second, there are inherent limitations to the market
of immersive VR apps. So far, these markets have been
known as entertainment and game-oriented markets
instead of markets for VR apps for education. Thus, the
adoption rate of this type of app may not be as high as
those that are designed for entertainment. We also did
not analyze the popularity of the apps, such as how many
people have downloaded the apps, what ratings apps got,
and what kinds of comments have been given in reviews.
Such analysis would also be tricky, since for example the
amount of downloads does not necessarily relate to the
number of users from higher education institutions and
since ratings in app stores might be biased. In addition,
we notice that advanced immersive VR for education
is available but the companies would not market their
products through popular app markets (which aligns
with the first limitation).
Third, due to the rapid proliferation of the field, our
market analysis is a first step and a snapshot. It builds
on a solid framework, but it cannot yet draw from a
profound base of theoretical work in the field.
The limitations do not lower the value of our
work, particularly in the light of it being the first
comprehensive market study. However, future work
needs to try to address these limitations. They may
also become obsolete due to the technological and
content-oriented progress in the field.
6.4. Future Research Directions
While our recommendations target practice, the
market analysis’ results suggest much room for future
research. One strength of VR lies in its ability to
immersively engage users in the virtual environment for
teaching procedural knowledge, which is in fact not so
much available in the common app stores. This can be a
room for improvement.
Our mapping reveals which design elements are
most commonly implemented to design specific learning
outcomes. However, we have little knowledge on what
design elements can support learning effectively. In
future research, it has to be thoroughly evaluated in
experiments and real courses, which design elements are
useful and actually improve intended learning outcomes.
Furthermore, we require not only the technology but
also new didactic concepts that provide educators with
guidance on how to meaningfully integrate VR apps in
their courses. Research on VR technology for education
ought to be a truly interdisciplinary endeavour.
Many apps in the markets tried to “replace” teachers
with virtual agents in the app. However, the efficacy of
such replacement is yet unknown. It is rather a research
agenda on the design elements: how far the teacher’s
role can be replaced, in VR-based teaching, and how
to efficiently embrace VR-based teaching into the
curriculum. A case study that observes the usefulness of
the design elements in supporting the research contents
would provide significant contributions.
Future research should try to grasp the work on VR
technology for higher education in its full breadth and
theorize it. While the work with learning content, design
elements, and application domains is a first step, a kind
of morphological box for educational VR apps could
be helpful. It would support classification and allow
to abstract from single fields and single approaches,
allowing to understand the – likely recurring – building
blocks of successful apps.
7. Conclusion
We have examined and explored the market for
VR apps. Thereby, we gained important insights
on existing VR apps and extended the VR design
element framework of Radianti et al. [12]. We
Page 132
carefully examined existing apps in the popular VR app
stores such as Google Play,Steam and Vive, focusing
on the design elements and learning content. Our
market survey identified Biology/Zoology, Astronomy
and Engineering as the three most popular application
domains. However, results also shows that these
HMD VR apps have been developed for 27 application
domains, which indicate the trends of broader adoption
of VR for education. Results partly align with findings
from the literature, but there is a gap between scientific
work on VR for education and the reality on the app
The authors are grateful for Joshua Handali who
conducted the app market crawling and his participation
for selecting the most relevant apps. We also would
like to thank Isabell Wolhgennant who has laid down
a solid basis for making this market study is possible.
This project has been funded with support from
the European Commission [Erasmus+ grant number
2018-1-LI01-KA203-000107]. This publication reflects
the views only of the authors, and the Commission
cannot be held responsible for any use which may be
made of the information contained therein.
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... We describe in this work three research cases from different study programs based on our project on VR in higher education. Although these are experimental, their embedding in the project combined with prior work on literature [6], learning [4], and the market for VR in higher education [10], allows us to draw conclusions. We offer these in the form of recommendations for educators, who soon hopefully can routinely use VR to offer students a richer learning experience. ...
... Furthermore, a recent analysis of VR app stores provides a comprehensive overview of VR learning apps already available on the market [10]. The authors concluded that available apps were mostly designed as short-term learning units that can be used more as a supplement to traditional lectures. ...
... Note that by the time of testing, there were only few apps for learning targeting higher education in the Oculus Quest VR app market [10], and especially for specialized topics such as cybersecurity. Thus, prior to the testing, we conducted preparation works and came up with the idea of watching 360°videos related to cybersecurity on the headset, which were accessible, but did not go into as much technical depth on the cybersecurity topic. ...
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... Historically, researchers within the IS field, such as Walsh & Pawlowski [15, p. 297], once pointed out that IVR is "[…] a technology in need of IS research", whereas most seminal IS studies [e.g., [16][17][18] have focused on virtual worlds or environments rather than IVR technology. Moreover, recent IS studies [6] [ [19][20][21] emphasize IVR technology from a broader perspective of education and learning, rather than safety training in particular. In other interrelated fields however, such as human-computer interaction (HCI), engineering, and educational sciences, several studies [10][11][12][13] [22][23][24] stress the importance of advancing the scientific discourse on VR and safety training, especially with an emphasis on producing prescriptive knowledge such as design principles. ...
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... In the educational sciences, formative features of learning are considered as feasible for evaluating training performance and learning [6]. The formative approach is also desired to incorporate into IVR training/learning environments [19][20], so that instructors and participants can inspect and evaluate critical factors of the training process. Hence, allowing the users to inspect fire hazardousness, its implications for the chain of cause-and-effect around (e.g., fire, smoke, and how to handle it onboard a train), is a feature that the IVR environment needs to implement for instant evaluation (during the training session) and post evaluation (after the training session) [9] [41]. ...
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Over half of educational apps on mobile-app markets are for preschoolers, but little research has examined whether the designs of preschool apps are truly educational. Preschoolers process information differently from older learners (i.e., shorter attention spans), so app designs should be guided by developmental science. This content analysis of popular Apple and Android math and literacy preschool apps uses a developmental framework to code and analyze apps’ educational features. Findings show a wide variety of features apps used. However, few provided developmentally appropriate guidance, like scaffolded feedback. This study offers insights for improving apps to meaningfully teach preschoolers.
Conference Paper
Differences in technological characteristics between expensive head-mounted displays like Oculus Rift and low-cost mobile-based Virtual Reality (VR) devices may affect the experience of the user and learning in virtual environments with an educational content and therefore are important to be studied. This paper describes a study that aims at finding differences in levels of spatial presence, usability, simulator sickness, satisfaction, workload and learning outcome between Oculus Rift and a low cost smartphone VR Headset, when users interact with an educational virtual environment. Our results do not show differences in the variables studied. It seems that mobile-based VR systems could provide acceptable levels of immersive user experience and contribute to the pedagogical use of VR.
Background: Consumer-available virtual-reality technology was launched in 2016 with strong foundations in the entertainment-industry. We developed an innovative medical-training simulator on the Oculus™ Gear-VR platform. This novel application was developed utilising internationally recognised Advanced Trauma Life Support (ATLS) principles, requiring decision-making skills for critically-injured virtual-patients. Methods: Participants were recruited in June, 2016 at a single-centre trauma-course (ATLS, Leinster, Ireland) and trialled the platform. Simulator performances were correlated with individual expertise and course-performance measures. A post-intervention questionnaire relating to validity-aspects was completed. Results: Eighteen(81.8%) eligible-candidates and eleven(84.6%) course-instructors voluntarily participated. The survey-responders mean-age was 38.9(±11.0) years with 80.8% male predominance. The instructor-group caused significantly less fatal-errors (p < 0.050) and proportions of incorrect-decisions (p < 0.050). The VR-hardware and trauma-application's mean ratings were 5.09 and 5.04 out of 7 respectively. Participants reported it was an enjoyable method of learning (median-6.0), the learning platform of choice (median-5.0) and a cost-effective training tool (median-5.0). Conclusion: Our research has demonstrated evidence of validity-criteria for a concept application on virtual-reality headsets. We believe that virtual-reality technology is a viable platform for medical-simulation into the future.