=Paper=
{{Paper
|id=Vol-3104/paper187
|storemode=property
|title=Extended Reality in Digital Learning: Influence, Opportunities and Risks’ Mitigation
|pdfUrl=https://ceur-ws.org/Vol-3104/paper187.pdf
|volume=Vol-3104
|authors=Oleksandr Burov,Olha Pinchuk
|dblpUrl=https://dblp.org/rec/conf/icteri/BurovP21
}}
==Extended Reality in Digital Learning: Influence, Opportunities and Risks’ Mitigation==
https://ceur-ws.org/Vol-3104/paper187.pdf
Extended Reality in Digital Learning: Influence, Opportunities
*
and Risks’ Mitigation
Oleksandr Burov1, Olga Pinchuk1
1
Institute for Digitalisation of Education of the National Academy of Educational Sciences of Ukraine,
M.Berlyns'koho St., 9, Kyiv, 04060, Ukraine
Abstract
The paper discusses AR/VR/MR/XR technologies in learning namely their influence/ opportunity and risks’
mitigation. Main aspects are as follows: methodology (factors influencing a student’s cybersickness in
AR/VR/MR/XR, the improved model of the cognitive activity in synthetic learning environment). It has
been developed the technique and ICT to study psychophysiological changes in normal and stressed condi-
tions. The experimentation results demonstrated that decrease in myocardial tension index under cognitive
performance conditions in immersive activity over time of observation was more significant and this fact
could be accounted in measurement of influence of the synthetic environment on students, as well as the
technique to measure AR/VR/MR influence. The technique proposed by the authors is based on modified
ICT and used in previous research: to assess influence of AR/VR/MR/XR as changes of short cogni-
tive/perceptual tests (3 minutes before the work and afterwards) with registration of physiological indices
informative in our research.
Keywords
ICT, synthetic learning environment, AR/VR/MR, cybersickness.
1 Introduction
Transformational effects created by information and communication technologies (ICT) in various
fields of activity attract the attention of researchers because of changes in skills needed [1]. The dy-
namics of this sector depend on global challenges and broader trends that determine the long-term
priorities of science and technology in the 4th Industrial Revolution [2]. One can highlight current
trends in (1) technology: development of 3D modeling tools for biomedical engineering as a life sup-
port technology; creation of effective forms of visualization of information, content and knowledge as
technologies of knowledge engineering; (2) content industry: the emergence of additional media prod-
ucts in the form of games, virtual realities (VR) and their integration with other media products and
social networks through the creation of common stories as a convergence of content delivery models
[3]. Note that converging nano, bio-, info- and cognitive technologies create a qualitatively new envi-
ronment for human life [4]. Thus, due to the development of advanced algorithms and programs for
processing, storage and transmission of images of various nature in the near future is expected to in-
crease the efficiency of virtual scene technology and augmented reality (AR), three-dimensional (3D)
modeling, in particular for biomedical engineering [5]. As a result of the technological evolution of
AR (from VR helmets in the 1970s, AR displays and the first mobile AR applications in the 1990s to
"smart" AR glasses today), the preconditions for the use of AR technologies for virtual training of
doctors and surgeons have been created [6]. AR technology will "collect" all the necessary information
for operations (received in the process of conditions’ monitoring from sensors and video cameras) in a
single image, adapted to the rapid perception and learning [7]. That created conditions for a significant
improvement in the quality of professional activity for the near future, including mobile [8]. However,
the main obstacle predicted by experts will be the lack of specialists, both relevant professional skills,
3L-Person 2021: VI International Workshop on Professional Retraining and Life-Long Learning using ICT: Person-oriented Approach, co-
located with 17th International Conference on ICT in Education, Research, and Industrial Applications: Integration, Harmonization, and
Knowledge Transfer (ICTERI 2021), October 1, 2021, Kherson, Ukraine
EMAIL: alexander.burov@gmail.com (A.1), opinchuk100@gmail.com (A.2)
ORCID: 0000-0003-0733-1120 (A.1); 0000-0002-2770-0838 (A.2)
© 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
in particular, and relevant digital competencies in general [9]. Another drawback of extended reality
technologies is the insufficient understanding of the psychophysiological "cost" of activity in the vir-
tual environment [10] due to insufficient knowledge of the characteristics of human consciousness in a
synthetic environment [11] and possible cybersickness [12]. The latter has been researched and char-
acterized in VR for decades, but we don’t know as much about the extent it affects users of
AR/VR/MR/XR technologies. Typically, VR users experience more symptoms on the disorientation to
nausea end of the scale, whereas AR users are more likely to experience headaches and eyestrain [13].
While these symptoms may not sound debilitating, when AR headsets are used for extended periods of
time, these symptoms can have a significant impact and, as indicated by a recent study, be as severe as
those associated with VR exposure.
Purpose. To develop the model of risks related to AR/VR/MR/XR technologies in learning, as well
as ICT structure and technique to study influence of these technologies at the learner performance and
cybersickness.
2 Methodology
The life cycle of technologies, innovative technological products and services will only accelerate.
In such conditions it is natural that scientists connect their hopes for creation of the positive integrated
reality under conditions of convergence of physical and virtual learning environments. In these condi-
tions, the role of research and development in the field of educational applications of ICT, in particular
in general secondary education, remains extremely important. Corporate learning has pioneered such
applications, drawing on best practices in VR and AR, artificial intelligence, including the use of chat
bots, knowledge bases, including video content creation, micro-learning and mobile learning. These
processes push the evolution of tools, forms and methods of teaching in general education as well.
We adhere to the opinion that the potential of the information and educational environment saturat-
ed with digital technologies, first of all, should be considered from the standpoint of the development
of cognitive activity of learning subjects. If students learn information images, including real natural
phenomena and processes, through experimentation with various digital tools and technologies (simu-
lations, computer simulations, virtual and augmented reality, etc.), it will provide creative activity in
an integrated (real and virtual) learning environment, will affect the cognitive motivation of students,
will contribute to the formation of appropriate digital competencies [14].
An important role in identifying areas for possible transformation of the education system is shared
access to new digital technologies. According to world experts, the tools of virtual reality VR, aug-
mented reality AR and augmented virtuality AV, mixed MR and extended reality XR (the latter in-
cludes all previous ones as well) are developing at the highest rate. The fourth industrial revolution is
accompanied by the transition of production and, consequently, education in a synthetic environment
of activity (both production and training). Education reform requires the accelerated implementation
of augmented reality tools into the educational process, as well as the preparation of future employees
to interact with artificial intelligence systems, as well as robotic systems.
The difference between these terms and means is that they are different combinations of real (RR)
and virtual reality, forming variants of an immersive learning environment in which perception is the
result of a synthesis of consciousness and feeling [15, p.16]. The most widespread over time from this
spectrum are augmented, virtual, mixed and extended realities, for which the following types are dis-
tinguished:
supplemented - market-oriented AR, location-based AR, overlay-based AR, projection-based
AR; all these types can be used in the educational process [16];
virtual - non-immersive VR, full immersive VR, shared VR, web VR;
mixed - options for combining real, augmented reality, augmented virtuality and virtual reality.
Augmented reality includes the whole spectrum, from "complete real" to "complete virtual" in the
concept of the continuum of reality-virtuality, proposed by Paul Milgram. With the development of
technical means of virtualization of reality and means of registration of indicators of human sensory
systems and the impact on them there is a specialization and separation of new types of immersive
environments. For example, SR (substitutional reality), 360 virtual reality (or 360 VR, which allows to
observe the object from any angle), etc. It can be expected that the range of synthetic "realities" will
further expand, accounting the possible relationships of human sensory systems, cognitive models of
activity and real reality [9].
2.1 Factors influencing a student’s cybersickness in AR/VR/MR/XR
It is important that the synthetic environment is not natural for humans, and its impact on his/her
mental and physiological processes remains insufficiently studied. Until now, among the factors influ-
encing the synthetic environment with different forms of virtualization on a person and his health, it is
proposed to distinguish the following:
1) personal: internal (inherent in man) - hereditary, gender, age, ethnic; physiological - interpupil-
lary distance, flicker fusion frequency threshold, postural stability, strength and mobility of nervous
processes, plasticity, cardiovascular system, vestibular apparatus; mental - consciousness, cognitive
features, spatial operations, thinking; health - diseases, disorders of the visual system;
2) technological: optical factors; reflection factors; factors related to spatial tracking; sound factors;
factors related to the form factor;
3) operational – adaptation, the degree of control, head movements, general visual (other sensors,
in addition) flow, speed linear and rotational acceleration, speed of self-movement, density and height
of the visual scene above the terrain, brightness level, vection (illusion of self-movement), duration,
cognitive workload. The model of influencing factors demonstrates their systemic nature (Figure 1).
adaptation
the degree of control
head movements
optical factors
general visual flow
reflection factors
speed linear and rotational acceleration
factors related to spatial tracking
speed of self-movement
sound factors
density and height of the visual scene above the ter-
factors related to the form factor
rain
brightness level
T e c hnol ogi c al vection duration
cognitive workload
Ope rat i onal
P e rsonal
Internal Physiological Mental Health
hereditary interpupillary distance consciousness diseases
gender flicker fusion frequency cognitive features disorders of the visu-
age threshold spatial operations al system
ethnic postural stability thinking
strength and mobility of
nervous processes
plasticity
cardiovascular system
vestibular apparatus
Figure 1. Factors influencing the synthetic environment
For learning, the most significant factors are that relate to the person features/abilities and opera-
tional ones.
There is increasing interest in determining any risks of using such technology and any aftereffect
from exposure. But the duration of the aftereffects from virtual environment (VE) exposure are not
well studied to date even after 20-years study [17]. Head-mounted display manufacturers provide gen-
eral usage guidance, but this is ad hoc and there is limited recent evidence comparing early virtual
environment studies with experiences from modern head-mounted displays. The primary objective of
the study [18] was to explore response activation and inhibition after participants experienced a typical
virtual environment in a head-mounted display. The evidence of participant fatigue in the reaction
time tests was found. This work confirms safe use of virtual reality experiences in modern head-
mounted displays for short duration exposures (15 min) and identifies issues with reaction time testing
that are in need of further investigation. Duration of VR activity in many researches are limited by 15-
45 minutes. In modern devices (f.e., Oculus Glasses) it is recommended the time of take at least a 10
to 15 minute break every 30 minutes, independently on age, sex, mental health level etc.
But there is only a few studies that aimed to assess the physiological “cost” of cognitive work in
VR. The investigation of VR-induced aftereffects on various basic cognitive abilities and its relation-
ship with cybersickness. Previous studies suggest an adverse effect of VR exposure on simple reaction
times. Aftereffects on other basic cognitive abilities have rarely been studied. The authors propose a
general aftereffect of VR exposure on reaction times that is only slightly related to subjective degrees
of cybersickness. Taken together, however, usage of VR systems, even if inducing moderate levels of
cybersickness, leads only to minor decrements of cognitive performance [19]. The question aroused in
relation to day-to-day stability-instability of cognitive tasks performance: was this characteristic of
only selected professionals or our findings had more general nature for people working with digital
technologies? Future psychophysiological VR-induced aftereffects needs to be studied in relation to
age, experience and prolonged (cumulative) usage of learning/training/work with VR.
VR technologies make learning more visual, enable trainees to be activated, and more fully engage
them in the learning process. These technologies facilitate and simplify the collaboration of people
who are at a distance, who can meet with the help of AR, prepare joint documents, lead projects and
perform many other work almost as effectively as with personal contact in real world. Teachers and
students have the opportunity to use virtual laboratories to study the world around them, develop
skills, as well as to demonstrate their development and automated assessment [20].
Cognitive activity in VR is the brightest manifestation of the immersive environment for educa-
tion/training. Virtual Reality glasses, helmets, 360° panoramic cameras and screens, as well as CAVEs
give new opportunity for learning, and have some specific features in comparison with more tradition-
al digital devices:
If in the real world the user interacts with the digital world through a "window“ (computers, tab-
lets and mobile gadgets) observing what is happening "from the outside“, "immersion" is the condi-
tion in which the user loses awareness of the facts actually occurring in an artificial world.
If in the real world the user involves almost only vision (other sensors are not involved or they
supply non-observational information), in “immersion”, the user experiences the virtual world with
involved his/her senses and is able to interact with the virtual environment.
Sensory useful (target) load approaches 100% and requires 100% attention and concentration,
regardless of the significance of the task. Sensory "hunger" (with monotonous operator activity) can
be replaced by sensory exhaustion.
The question is what could be VR/AR/MR consequences for health? How safe are virtual reality tech-
nologies for human health? The long-term consequences of using these technical means are not yet
clear. But it is already obvious that they are invading the work of the human body. And we are talking
not only about the curvature of the spine due to the prolonged wearing of a heavy device on the head,
but also about the impact on the user's eyes. The headset forms a wide field of image; it is a rather
complex device that interferes with the normal operation of the visual apparatus. A systematic study of
the impact of immersions in virtual reality on human health in general and on his mental health is still
an open question [21]. Medical and physiological studies over the past quarter century have shown
[22] that immersing a person in a specially designed virtual reality can significantly affect his/her
mental health (treatment of depression, elimination of alcohol dependence and other mental disorders.
However, all these studies are still quite fragmented, and the proposed methods require a qualified
psychotherapist that is not applicable in education/training [23].
Further research of the problem should focus on the detailed development of types of threats to par-
ticipants in the educational process, as well as methods of counteraction. A special point should be
resistance to cyber-hazards, which can use the experience of training emergent industries’ operators
primarily diagnosing the current state of the person and necessary adjustments in order to optimize its
activities.
2.2 Model of the cognitive activity in synthetic learning environment
As it was stated [24], VR/AR/MR/XR are the brightest manifestation of the immersive environment
for education/training, and have some specific features in comparison with more traditional net-
works/devices, and the object of activity (mental) is not external in relation to the human, but internal
one [25]. The model of the cognitive work (P. Anokhin’s model of the activity functional system that
has been developed by authors for cognitive activity) can be specified for the case of VR/AR, where
activation of the sensory (affector) inputs (Figure 2) happen not so from the outer environment, as
from the Virtual Act Program without activating the Act Program mechanism (as in physical activity).
Figure 2. Theoretical scheme of the functional system of learning activity in VR/AR/MR, where the
cognitive contour is associated with the “internal” activity (modified from [25]). Note: “Afferent In-
puts” are: V -visual, A - audial, H – haptic, M – motion
In other words, the chain “Act acceptor – Act program – Act – Object – Result” in traditional ac-
tivity transforms into the chain “Act acceptor – Virtual act program – Cognitive object – Cognitive
result”. The most important feature of such a process is that all system elements and their interactions
are part of the human organism, i.e., its internal environment, in contrast with physical (or miksted)
activity, where its object is located outside the organism and activity takes place in whole or in part of
the external environment. We believe, that this model can explain, why such regulation can deplete
and imbalance the body: Act Program works in coordination with the Act Acceptor and Substratum
needed for the normal life and activity. But lack of the signals from the Act Program cannot activate
the general feedback from activity, only simulating it at the neurological level [25, p.352].
Another difference is influence of the Virtual act program on the Decision making block, because
both blocks and the Cognitive objects are parts of the same cognititve process. Besides, the Virtual act
program can influence on the Afferent inputs activating sensors participated in the particular cognitive
activity according to the work task.
As a result, all neurophysiological subsystems (blocks in the schema) are more active the more im-
mersive is the task performance. That is why the control of operational parameters in AR/VR/MR/XR
is so important to mitigate cybersickness, especially in learning process that can take hours of a human
activity, in general.
3 Results and Discussion
To date, it was confirmed that changes in efficiency of immersive cognitive activity with digital
units had strongly individual nature in day-to-day performance of the same complexity that could be
explained by the internal (physiological) and external influences on a human.This notion has been
confirmed by the high relationship between indicators of test performance (rate and reliability of prob-
lem solving) and physiological indices. Only the simultaneous activation of both paths (energy and
information) provides higher level of optimization of educational/training capacity - quality education
[9]. An unbalanced path and thus the strain of regulatory mechanisms of adaptation may be the cause
of functional impairment and eventually the case of violations of students’ health. It has been found
that:
Work with computer in “classroom” can blur attention because of low workload of non-active
sensors and their ability to be affected by unplanned external signals.
Higher workload of all or many sensors can be accompanied by more significant increase of ad-
verse changes in physiological support of activity.
Because involvement of a user into VR activity is very high (motivation, sensors workload), in-
formation environment coincides with cognitive one, but the latter is significantly individual.
It should be noted that the psychological/psychophysiological aspects of cybersecurity, inherent in
the human factor in human-machine systems, can be significantly enhanced in the synthetic environ-
ment, which is currently an unexplored area in general and in education in particular [26]. On the other
hand, the use of models for predicting the effectiveness of learning (included in adaptive systems)
allows to assess and predict the effectiveness of augmented and virtual reality for synthetic learning
environment [27] and human integration in general [28], epecially accounting modern trends in the
ICT evolution [29]. To realize such an approach, the methodology described above was used as a basis
to apply appropriate ICT that provides methodical maintenance of cybersickness risks’ measurement
and assessment, test generation and control, data storing, data analysis and necessary service for re-
searchers.
3.1 Method
In our previous research the cybersickness has been modeling in experimental study of cognitive
activity with measuring of its psychophysiological response to a human focused cognitive test perfor-
mance (high motivated, without external disturbances) with and without time pressure [25]. In addi-
tion, the technique included measurement of electropuncture diagnostics’ indices by Nakatani (24 reg-
ular points and 3 stress’ points), as well measurement of lipid metabolism using sweat collection be-
fore and after the test session for each subject. Subjects included 28 males of 18-40 year old.
The experiments differed by the test (permutation of random non-repeating digits from 0 to 9 in as-
cending order) workload: training Е1 (60 min); Е5 - free rate ("«auto-pace"), and Е6 - fixed rate calcu-
lated as average by results of the appropriate test performance in Е1. The E6 could be evaluated as the
model of immersive cognitive test performance (high motivation and time “pressure”, because accord-
ing to our previous study the individually “average” rate of task exposure was more difficult than
twice as slow or as fast). Duration of the test performance session was 3-hours long.
As indices of physiological “cost” of activity and the human state we registered a heart rate HR and
blood pressure (systolic BPs, diastolic BPd) by means of the cardio-monitor "Solveig". The indices
HR, BPs and BPd we registered during 10 min prior to the tests beginning (index “0”) and 10 min
after finishing (relaxation), as well as every 5 min during the test activity [25, p.352]. Clear changes
appeared in physiological response: increase of the level of low density lipids, energy balance (Elec-
tropuncture), heart rate (myocardial tension index after R. Baevsky) and blood pressure. The data re-
ceived have demonstrated quite individual nature of changes in time.
To study that phenomenon, we carried out the similar experiments, but with another analysis of da-
ta stored. The method of computer data processing was aimed to analyse physiological changes at dif-
ferent phases of test performance that would correspond phases of a human performance after Ego-
rov&Zagriadskii. Because diastolic blood pressure has been revealed as the most informative (sensi-
tive to the cognitive workload) physiological index, BPd was averaged for consequent 20-minutes
intervals and was represented at the “phase plane” (vector diagram where one point corresponded to
one 20-minutes interval). Vizualization of the physiological changes on the phase plane (Figure 3) has
confirmed that first 20…40 minutes of tests performance are accompanied by the higher systolic pres-
sure and/or at the end of the performance (this corresponds the phase of the “end gust effect” after
Egorov&Zagriadskii). But the first phase could have individual features from viewpoint of time struc-
ture, if to analyze it in more detailed way (f.e., minut-by-minut or in 5-minute intervals) that could be
significant accounting that VR/AR activity longer 40 minutes were not studied, and “normal” academ-
ic hour is 45 minutes.
The next step of analysis was carried out to study myocardial tension index’s variation (after R.
Baevsky) at the 1st 45-minutes interval of test performance (that could be considered as equivalent of
the academic hour) with 5-minut consequent phases. We compared physiological workload in experi-
ments E5 and E6 again. If in previous analysis with 20-minutes phases some individual differences
were registered, it has been revealed a clear trend in subjects’ myocardial tension between experi-
ments E5 and E6: the higher level of tension under “harder” conditions (experiment with time “pres-
sure”) during first 20 minutes (four phases) of test performance (Figure 4).
In other words, decrease in myocardial tension index under cognitive performance conditions in im-
mersive activity over time of observation was more significant and this fact could be accounted in
measurement of influence of the synthetic environment on students.
Figure 3. Physiological (blood pressure) changes on the phase plane in two subjects
Figure 4. Physiological (myocardial tension index) changes on the 45-minut phase plane in two sub-
jects
3.2 The technique to measure AR/VR/MR influence
The main difficulty in measuring influence of AR/VR/MR/XR on a human cognitive performance
is to differentiate psychophysiological effects of usual cognitive workload and synthetic “realities”,
especially in the education process. This is a general problem of assessment of Associations Between
Digital Technology Engagement and Mental Health/efficiency Problems. Even more, according to the
study [30], there is no evidence that associations between adolescents’ digital technology engagement
and mental health problems have increased over. These results are based on observation of 430,561
participants (adolescents) over period 1991-2019 in the United States and United Kingdom. But that
study did not take into account that everyday environment of todays’ young people is digital with re-
lated specifics. That is why measurement of possible influence of the synthetic environment should be
provided by means the same or similar digital tools.
The technique proposed by the article authors is based on modified ICT described above and used
in our research. But we plan to assess influence of AR/VR/MR/XR as changes of short cogni-
tive/perceptual tests (3 minutes before the work and afterwords) with registration of physiological in-
dices informative in our research.
Thest performance is controlled by appropriate ICT in on-line or off-line modes.
4 Concluding Remarks and Future Work
Augmented, virtual, mixed and extended realities become the part of a human everyday life in all
areas of life and activity. It is important that the synthetic environment is not natural for humans, and
its impact on his/her mental and physiological processes remains insufficiently studied. Factors
influencing a student’s cybersickness in AR/VR/MR/XR can be considered as: personal (internal,
inherent in human; physiological; mental; health); technological (technical means, ergonomic);
operational (adaptation, the degree of control, head movements, general visual flow, linear and
rotational acceleration, speed of self-movement, brightness level, vection (illusion of self-movement,
duration, cognitive workload).
It has been developed the theoretical scheme of the functional system of learning activity as a fur-
ther development of the TFS model for learning. It was highlighted that all neurophysiological subsys-
tems are more active the more immersive is the task performance. That was why the control of opera-
tional parameters in AR/VR/MR/XR was so important to mitigate cybersickness, especially in learn-
ing process that could take hours of a human activity, in general.
Decrease in physiological indices (myocardial tension index and blood pressure) under cognitive
performance conditions has been revealed in immersive activity over time of observation, and it was
more significant than in “normal” conditions. Those results were confirmed by use of the technique
“phase plane” proposed by authors.
That fact could be accounted in measurement of influence of the synthetic environment on students.
Application of developed ICT provides methodical maintenance of cybersickness risks’ measurement
and assessment, test generation and control, data storing, data analysis and necessary service for re-
searchers. Respectively, it was developed the technique to assess influence of AR/VR/MR/XR as
changes of short cognitive/perceptual tests (3 minutes before the work and afterwords) with registra-
tion of informative physiological indices. Future work is planned to provide evidence of such a tech-
nique efficiency for learning.
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