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applied
sciences
Article
Immersive Virtual-Reality-Based Streaming Distance Education
System for Solar Dynamics Observatory: A Case Study
Joongjae Lee 1, Jaeheung Surh 2, Wooseong Choi 3and Bumjae You 1,4,*
Citation: Lee, J.; Surh, J.; Choi, W.;
You, B. Immersive Virtual-Reality-
Based Streaming Distance Education
System for Solar Dynamics
Observatory: A Case Study. Appl. Sci.
2021,11, 8932. https://doi.org/
10.3390/app11198932
Academic Editor: Jiro Tanaka
Received: 1 September 2021
Accepted: 20 September 2021
Published: 25 September 2021
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4.0/).
1Center of Human-Centered Interaction for Coexistence, Hwarangno 14-gil 5, Seongbuk-gu,
Seoul 02792, Korea; arbitlee@chic.re.kr
2NAVER Clova, Seongnam 13561, Korea; jae.surh@navercorp.com
3Hana Institute of Technology, Grace Tower, 127 Teheran-ro, Gangnam-gu, Seoul 06236, Korea;
ws.choi@hanafn.com
4Artificial Intelligence and Robotics Institute, Korea Institute of Science and Technology (KIST),
Seoul 02792, Korea
*Correspondence: ybj@kist.re.kr
Abstract:
The combination of immersive virtual reality (VR) environments and distance education
has led to a new educational paradigm. In this study, an immersive VR-based distance education
system is proposed to enable multiple remote users to send, share, and experience images from
the Solar Dynamics Observatory (SDO) via streaming. In contrast to the conventional system in
which only experts use SDO data, the proposed system provides a head-mounted-display-based
visualization platform that can be easily used by experts and non-experts. Real-time SDO image
streaming must be possible to realistically observe changes in the Sun and increase involvement.
Thus, multichannel-based SDO image transmission was applied to increase the network bandwidth
utilization. To improve the social presence of participants, realistic avatar models controlled by
the motions synchronized with the user are provided. In addition, free communication is possible
through verbal interactions. This allows multiple remote users to participate simultaneously without
having to be physically present. A user study with 20 subjects showed that the participants could
observe SDO images in a more immersive manner by using the proposed system. In addition,
they experienced social presence because of the user avatar models and an enriched educational
experience by conversing with and listening to experts.
Keywords:
distance education; immersive learning; Solar Dynamics Observatory (SDO); streaming;
virtual reality (VR)
1. Introduction
The recent developments in virtual reality (VR) and networking technology have
facilitated the use of VR in classrooms and distance education programs. VR in education
promotes active interactions among students and avoids distractions in the classroom.
Representative applications include medical education [
1
–
3
], vocational training [
4
,
5
], and
virtual field trips [
6
,
7
]. VR in education can overcome physical (spatiotemporal) constraints
and enable learning that is not influenced by the dangers or restrictions of the real world.
Distance education allows remote non-contact teaching and learning between teachers
and students and between physically distant students [
8
,
9
]. It allows students to receive
education at any time and place and adjust their progress accordingly. However, it is
difficult to develop personal interactions between teachers and students and assess students’
abilities. Moreover, it is challenging for students to actively participate in the classroom,
and teachers cannot immediately answer students’ questions. In addition, students should
take greater responsibility for their learning, as they must decide when, where, and how
to learn.
There are two main advantages of VR-based distance education. First, it resolves
imbalances in educational opportunities between countries and regions. Rural areas
Appl. Sci. 2021,11, 8932. https://doi.org/10.3390/app11198932 https://www.mdpi.com/journal/applsci
Appl. Sci. 2021,11, 8932 2 of 19
that receive less support for educational infrastructure can benefit from experts. Physi-
cal constraints such as time and distance can be overcome by networking, and the im-
balance problem can be solved by sharing various educational content. For example,
massive open online courses (MOOCs)
(https://www.mooc.org/, accessed on 1 Septem-
ber 2021) and other online programs provide various and rich educational content via
educational platforms in which anyone can participate without qualification restrictions.
Second, it provides a socially immersive virtual educational environment. Distance ed-
ucation generally uses videos by default, such as MOOCs or online education methods
employing video conferencing tools. However, direct interaction between teachers and
students is challenging compared with offline education [
10
]. For example, in video-
conference-based education, the participants are displayed as thumbnails in a graphical
user interface. This makes it easy to become distracted and lose focus. In contrast, immer-
sive VR (IVR)-based distance education provides an improved educational environment
using a head-mounted display (HMD) in which the remote participants feel like they are
in the same space, in comparison to desktop VR and cave automatic virtual environment
(CAVE) VR. Moreover, due to the recent global COVID-19 pandemic, there has been a need
for non-contact distance education from elementary to higher education [
11
–
13
]. The need
for team-based VR remote education that requires collaboration is also increasing [14,15].
VR education covers various disciplines including engineering, computer science, as-
tronomy, biology, medicine, chemistry, manufacturing, physics, and surgical medicine [
16
].
Among them, the representative VR content includes applications related to astronomy. For
example,
Apollo 11 VR HD
(https://immersivevreducation.com/products-vr-experiences/
apollo-11, accessed on 1 September 2021) developed by Immersive VR Education allows
ordinary people to vividly experience the process of lunar exploration performed by
the first astronaut to land on the Moon. Split Light Studio developed an educational
Solar System VR App (http://splitlightstudio.com/pages/movies_solar_system.html
, ac-
cessed on 1 September 2021) that involves a tour of the planets and the Moon. Although it
can help users understand the planets with colorful graphics, the contents are produced
manually and cannot reflect the ever-changing appearances of celestial bodies.
On 11 January 2010, the U.S. National Aeronautics and Space Administration (NASA)
launched the
Solar Dynamics Observatory (SDO)
(https://www.nasa.gov/pdf/418329
main$_$SDO$_$PressKit.pdf, accessed on 1 September 2021) that can continuously observe
the Sun, as shown in Figure 1. This allows anyone, and not just experts, to observe the
changes in the Sun. In this study, an IVR-based distance education system was proposed
to enable multiple remote users to share and experience SDO images in real time via
streaming. The requirements for building the IVR-SDO distance education system are
as follows:
R1
:Low-barrier of entry for people who are interested in SDO. The system must be easy to
use, even for non-experts. Only limited experts, such as space scientists or aeronautical
meteorologists, have shown interest in existing SDO data. Although not well-known to
the public, the SDO data provided on the web can be easily accessed by ordinary people.
However, expert knowledge is still required to handle the data. Hence, it is necessary to
lower the barrier to entry for the general public by providing a more accessible education
method. Low-priced HMDs can replace expensive large-screen displays, and the limitations
of place can be overcome by eliminating the need for remote visits using a network.
R2
:Streaming immersive data visualization platform. The system should provide users with
immersive data visualization of SDO images via streaming through an HMD-based visual-
ization platform. Streaming is required because it is practically difficult to archive large
SDO images at a local site. An HMD is used because in desktop VR and CAVE, the user
recognizes the screen, thus lowering immersion. A virtual space can immerse users by
freely adjusting the size of the Sun image and arranging it in various ways.
R3
:Realistic avatar-based embodied interactions. To improve the social presence of participants,
a realistic avatar model should be provided and controlled based on motions synchronized
with the user. Furthermore, free communication using verbal interactions is possible.
Appl. Sci. 2021,11, 8932 3 of 19
R4
:Physically distributed multiuser support for group learning. It should enable group learning
in which many physically distant users can participate together without being physically
present. This is achieved by making them feel as if they are receiving education in the
same space.
Figure 1.
Solar Dynamics Observatory (SDO): Investigating the causes of solar variability and how
space weather results from that variability.
The remainder of this paper is organized as follows. Section 2introduces related
work. Section 3details the IVR-SDO distance education system. Specifically, the proposed
system structure, network structure, and multichannel-based data transfer method for
SDO image streaming are described. Section 4presents the quantitative experiment results
for the network utilization of the proposed IVR-SDO distance education system and the
qualitative preference analysis results from user experiments. Finally, Section 5provides
the conclusions and directions for future research.
2. Related Work
2.1. Solar Dynamics Observatory
The objective of SDO is to help understand the Sun’s influence on Earth and near-Earth
space by studying the solar atmosphere on small scales of space and time and in many wave-
lengths simultaneously [
17
]. SDO sends solar observation images to Earth at a continuous
science data downlink speed of 130 Mbps, which are then stored. The SDO images captured
at multiple wavelengths can be used to observe various events such as flares, active regions,
and coronal holes by employing the web-based
Hellioviewer
(https://helioviewer.org, ac-
cessed on 1 September 2021). Furthermore,
JHelioviewer
(http://www.jhelioviewer.org/,
accessed on 1 September 2021), the open source data visualization tool, has improved
usability, focusing on space weather analysis [
18
]. However, the entry barrier is too high for
non-experts to operate easily. When SDO images are visualized, the placement and resizing
of the images are also limited by the monitor size. NASA provides
SDO Solarium
(https:
//www.nasa.gov/solarium, accessed on 1 September 2021) (Figure 2a) and the video wall
of the NASA Museum
Sun Video Wall
(https://www.nasa.gov/content/goddard/sdo/
national-air-and-space-museum-debuts-must-see-sun-video-wall, accessed on 1 Septem-
ber 2021)
(Figure 2b)
for the general public to easily experience the SDO images, which
are again used only by experts. Because large displays are utilized for exhibition and
education, SDO images can be experienced with greater immersion than when using a
dedicated viewer.
Appl. Sci. 2021,11, 8932 4 of 19
Figure 2.
People experiencing SDO images via facilities provided by NASA to the general public:
(a,b) Solarium in the NASA SDO Exhibit; and (c) Sun Video Wall in the NASA museum.
2.2. Virtual Reality in Education
Kavanagh et al. conducted a systematic review of the motivations for using VR in
education and addressed the potential problems and limitations [
19
]. VR education systems
were found to improve the intrinsic motivation of students. In addition, they introduced
and compared the latest VR technologies that can address the problems of VR education,
including cost, user experience, and interactions. Carruth examined the factors influencing
the effect of VR education and found their increasing use for studying and evaluating
buildings [
20
], as students can explore problem spaces and test solutions in a virtual space.
Furthermore, he reported that the effects of VR education appear in a wide range of areas,
from surgery education to manufacturing and assembly.
Jensen and Flemming investigated the advantages and disadvantages of using HMDs
in education and training [
21
]. HMD is ideal for teaching most techniques and enables
immersive education, as corrections can be made using repetitive practice without any risk
when learners are exposed to challenging educational situations. They noted that there were
significant barriers to using HMDs remain due to cybersickness symptoms, lack of suitable
software, and the technical limitations of peripherals. Nevertheless, VR as an educational
tool is growing explosively and enjoying increased user preference with the emergence of
affordable and easy-to-use immersive HMDs and peripherals. For example, in [
22
], the
knowledge acquisition, satisfaction, and comfort of students when the same pharmacology
artifact was displayed in CAVE2 and a mobile handheld device with stereoscopic lenses
attached were investigated. The results showed that the students preferred the mobile
handheld device over CAVE2, which is more cost-effective and accessible. VR-based
education is also often used for training and learning complex operational tasks. Hou
et al. suggested an efficient educational framework based on AR/VR for operating oil
and gas facilities, which is a complex process that requires expertise [
23
]. According
to the experimental results, compared to paper-based education, the AR/VR education
system can save manpower, increase efficiency by reducing the movement distance during
work, and shorten the learning time for improving learning performance. The AR/VR
education system can enhance education quality to prevent errors and failures during
work, considering effectiveness and safety concerns. However, it has the limitation that the
data of the actual work environment cannot be synchronized to the mixed reality system in
real time. Patle et al. showed that combining VR with operator training simulators enabled
more effective training by providing the operator with a realistic experience [24].
VR-based education creates a virtual environment that supports multiple users.
Senond Life (SL)
(https://secondlife.com/, accessed on 1 September 2021), a leading on-
line virtual world developed by Linden Lab, San Francisco, had approximately one million
users in 2013. It allows users to create avatars and interact with objects or other avatars and
meet and socialize with others, participate in private and group activities, build virtual as-
sets and services, shop, and trade. Julian conducted a study on virtual learning experiences
that allow students of English as a foreign language (EFL) to learn a second language in a
3D multiuser virtual environment, SL [
25
]. He observed whether language education and
learning could be facilitated if SL provided visual and language support to EFL learners.
In addition, he demonstrated that the virtual learning experience could be optimized by
accepting the culture and world knowledge of learners and simulating real-life scenarios.
Appl. Sci. 2021,11, 8932 5 of 19
Providing such an immersive collaboration environment can promote learner participation
and motivation, make them actively learn, and increase creativity, making it different from
traditional classroom-based education methods. Increasing the completeness of immersive
simulation can further increase participation and produce positive learning effects.
Recently, many education systems using networks and cloud services have been
developed. VR field trips compared the effects of a live teacher using networked depth
cameras and a standalone pre-recorded teacher on student learning [
26
]. The video-
based standalone education method was relatively simple to deploy because additional
equipment or setting time was not necessary and could provide more content as less
time was needed for communication with students. In contrast, the live teacher had the
advantage of reducing misunderstandings by answering student concerns, making it more
attractive to the students. Abichandani et al. performed solar energy education on virtual
solar cells, solar modules, and solar arrays using a cloud-based VR education system [
27
].
Feedback from students indicated that their participation and knowledge acquisition were
high. However, although this system is highly scalable and accessible as a cloud-based
service, user immersion is low, given that it is a web browser-based desktop VR system.
He et al. demonstrated that network-based VR could simulate a polluted gas diffusion
process in real time in a cloud-computing environment [
28
]. They also simulated polluted
gas diffusion in real time in a large-scale scene using an online PC, notebook, and mobile
device. Ding et al. proposed a VR education system to scientifically and systematically
improve the physical level of college students [
29
]. Users of this system can render scenes
in the cloud and experience VR using a mobile device. Moreover, related data can be
collected using the Internet of Things, and users can interact with VR scenes in real time.
3. IVR-Based SDO Streaming Distance Education System
3.1. IVR-SDO Streaming Education System Architecture
Figure 3shows an overview of the proposed SDO distance education system. The
system comprises an SDO client, a data relay server, and an SDO image transmission
server. The SDO client comprises hardware such as the HTC Vive HMD, controller, and
PC system. The HMD tracks the user ’s head pose using a tracking sensor attached to the
HMD while providing immersive visualization. Users can engage in voice conversations
using a built-in microphone and earphones. The Vive controller tracks hand movements
by 1:1 mapping of the user’s hand and offers a ray-pointing feature that helps explain the
content when the controller button is pressed.
Figure 3. Overall system architecture for IVR-SDO streaming distance education.
Appl. Sci. 2021,11, 8932 6 of 19
3.1.1. SDO Client
The main components of the SDO client are the I/O module, rendering engine, net-
work module, and SDO image transfer module.
For generating realistic human avatars that represent users’ presence, the rapid 3D
avatar creation method proposed by Lim et al. was used [
30
]. This method can quickly and
automatically create a user avatar within 2 min using a single depth camera and turntable.
For the simplicity of implementation, this study uses only a head and hand model instead
of a full-body avatar model. The I/O module tracks the head and hand poses using an
HMD and a controller to control the avatar according to the user’s motions. To support
voice conversations between users, the voice I/O is controlled through the microphone
and earphones attached to the HMD. The rendering engine consists of a sound engine and
graphics engine, which enables verbal interaction by combining the avatar engine that
controls the avatar model according to the user’s motions with the voice sent from remote
users, which renders SDO images received from the network module in a 3D virtual space
in an immersive manner.
The network module transfers the necessary data, such as SDO images, voices, and
head and hand poses, to the network for SDO distance education. The SDO image transfer
module merges the SDO images that are split-transmitted from the relay server via multiple
channels to their original size and decodes them using the JPEG2000 decoder.
3.1.2. SDO Image Server
When a request is received by the SDO image transfer module, the SDO images
in the repository are sent to the relay server. The images are sent with a frame size of
approximately 1 MB using multiple channels. This method can fully utilize the network
resources. The sender splits the total image into the maximum data size that can be sent
for each channel, and the receiver merges them to the original size. This study transmits
10 types of 1 MB SDO images in 30 fps using six channels.
3.1.3. Relay Server
The SDO client and image server have considerable networking loads because large
SDO images are transmitted. Furthermore, if the SDO image server also takes charge of
user management, the complexity increases with the number of users. The relay server for
each channel reduces this problem. For example, six-channel video relay servers, and a one-
channel relay server are allocated for transmitting SDO images and data, respectively. Thus,
independent relay servers are allocated to different types of media. Although the relay
server suffers from increased transmission time compared to the direct data transmission
method, it reduces the data transmission load of the SDO image server and achieves
scalability by increasing the number of relay servers. Problem channels are restored
without affecting the other channels using a relay server for each channel. This study
used relay servers for six-channel video, one-channel voice, and one-channel avatar/hand
motion data. Here, the difference between the SDO and other data channels is that the
SDO video channel is only used for downloading as a simplex channel that only transmits
data in one direction, whereas the voice, head, and hand channels are full duplex channels
that transmit data in both directions.
3.1.4. SDO Data Specification
The SDO data, transmitted through the network in Figure 3, consist of SDO im-
ages, voices, and motion data of the avatar. The detailed data specifications are listed
in
Table 1
. Figure 4shows examples of 10 types of SDO atmospheric imaging assembly
(AIA) ultraviolet wavelength images occupying most of the network bandwidth, and two
types of illuminance/magnetism measurement images of the Helioseismic and Magnetic
Imager (HMI).
Appl. Sci. 2021,11, 8932 7 of 19
Figure 4.
Examples of 10 types of SDO AIA ultraviolet wavelength images and HMI illumi-
nance/magnetism measurement images.
Table 1. Data specification for IVR-SDO streaming education system.
Data Type Data Specification Data Size/s
SDO image
• 4096 ×4096 resolution
300 MB/s
• 1 MB/frame
• 10 types
• 30 fps
Voice
• 44.1 KHz sample rate
368.64 KB/s
• 2 channels
• 2 byets/sample
• 2048 samples
• 45 fps
Hand/head poses
• Hand pose (22 joints ×2 hands ×4×4 pose matrix)
172.8 KB/s• Head pose (4 ×4 pose matrix)
• 60 fps
3.2. Network Configuration for IVR-SDO Streaming Education System
Because the IVR-SDO distance education system requires a high bandwidth, it uses
the Korea Research Environment Open Network (
KREONET
) (https://www.kreonet.
net/eng/, accessed on 1 September 2021) as the backbone. KREONET supports high-
performance network infrastructure to provide diverse science technology information
resources, supercomputing, GRID, and e-science applications to approximately 200 re-
search and development institutes. As shown in Figure 5, SDO images that are periodically
transmitted from NASA connected to KREONET are stored in the network attached storage
(NAS) of the Korea Astronomy and Space Science Institute (KASI), considered the Asian
data hub. The SDO image server transmits user-requested SDO images stored in the NAS
to the relay server. The SDO client receives SDO images via streaming by connecting to the
relay server. Unlike SDO images, the voice and hand/head pose data are relayed through
independent channels and transmitted to the SDO client.
Appl. Sci. 2021,11, 8932 8 of 19
Figure 5. Network configuration diagram for IVR-SDO system education.
3.3. Multi-Channel Based SDO Image Streaming
SDO image streaming is required for two reasons. First, it is practically impossible to
archive large SDO images at a local site for each user because of limited storage. As shown
in Table 1, transmitting SDO images requires a high bandwidth of 300 MB per second
(2.4 Gbps). Second, to realistically observe the changes of the Sun in SDO images generated
every 10 s, they must be sent and displayed at a rate of 30 fps or higher, similar to videos.
In this study, a multichannel transmission method was used to fully utilize the high
bandwidth of KREONET to transmit large SDO images with up to 10 spectrums in real
time. Because the size of an SDO image is approximately 1 MB, a network bandwidth of
300 Mbps or higher is required to transmit at 30 fps. This requirement can be satisfied
by using KREONET, which supports a bandwidth of 10 Gbps or higher. The maximum
transmission unit of the Ethernet is set to 1500 bytes by the IEEE 802.3 standard [
31
], and
up to 9198 bytes can be transmitted depending on the compatibility of the router. If the
transmitted data are of a larger size, the network splits the data, causing a delay. Because
the method of sending data based on a single channel cannot use the total bandwidth, the
bandwidth utilization is increased using multiple channels.
Figure 6shows the concept of multichannel-based SDO image streaming. As shown
in Figure 6a, the multichannel-based SDO image transfer module comprises a splitter and
merger. The splitter in the sender splits the input SDO image into chunks and transmits
them in parallel using the available multichannels. The merger in the receiver assembles
the split chunks of the SDO image into the original SDO image, thus completing reception.
An SDO header is added in front of each SDO image data, as shown in Figure 6b, to
implement the SDO image transmission protocol for handling user requests and responses.
The total SDO data with the SDO header added were split into chunks of unit size. Figure 6c
shows the transmission of the split chunks of the SDO image using the available channels.
This method shares channels instead of dedicating a specific channel for each SDO image.
Network utilization can be improved by checking the currently available channels and by
sending image data in parallel.
Figure 7shows the SDO image header for transmitting the SDO images through the
network. The fields of the SDO image header are as follows:
• Timestamp—64-bit UTC information;
• Type—16-bit SDO image information, indicating AIA or HMI;
• Channel—16-bit AIA or HMI channel information;
• Image data size—32-bit data size of SDO image;
•
Reserved #1, #2, #3—each 64-bit reserved space for expandability (e.g., channels other
than AIA or HMI, different image data format, and different resolution).
Figure 8shows the data transmission process of the split-and-merge approach for
multichannel-based SDO images. The SDO image input to the transmission queue of the
splitter (Figure 8a) is sent to the chunker where it is split into chunks of unit size (
Figure 8b
).
The split image chunks are sent to the sender through an available channel among the
multichannels (Figure 8c). If the transmission queue is not empty, the next SDO image is
Appl. Sci. 2021,11, 8932 9 of 19
split and transmitted at every set time interval during the transmission of the previous
image, and this whole process is performed in parallel (Figure 8d). The chunks that arrive
at the merger of the receiver are delivered to the dechunker and assembled into the original
SDO image (Figure 8e). The assembled SDO image is delivered to the receiving queue,
which completes the transmission (Figure 8f).
Figure 6.
Multichannel-based SDO image streaming: (
a
) multichannel data transmission using split–
merge method; (
b
) splitting image data into chunks after combining with SDO header;
(c) parallel
transmission of the split chunks of SDO image.
Figure 7. SDO image header format.
Figure 8.
Multichannel-based SDO image transmission using the split-and-merge approach:
(a) start
image transmission; (
b
) split the image; (
c
) transmit image chunks; (
d
) assemble image chunks;
(e) complete image assembly; and (f) complete image transmission.
Appl. Sci. 2021,11, 8932 10 of 19
3.4. Participant Interactions in VR Space
The education participants wore an HMD and earphones and stood with a controller
in their right hand. An expert connects to the system and explains the SDO image through
voice conversations. When the controller button is pressed, the object of explanation
is indicated by ray pointing in a virtual space to improve the students’ understanding
(Figure 9a). When students want additional information, they can ask questions via voice
conversation while indicating a virtual object by ray pointing (Figure 9b).
Figure 9. SDO image education and participant interactions in a virtual space: (a) SDO education using ray-pointing; and
(b) listening to the explanation of an expert on SDO images through voice conversation.
4. Experimental Results
This section describes the implementation of the proposed distance education system,
network utilization in multichannel-based data transmission, and the user
experiment results.
4.1. Implementation for IVR-SDO Streaming Distance Education System
Each SDO client system has an Intel Core i7-6850K with 32GB memory and an NVidia
GTX 1080 graphics card. The SDO clients used Vive HMDs with Vive controllers. The
system was implemented using the Coexistent Reality Software Platform (CRSF) 2.0 [
32
]
and Microsoft Windows 10. A relay server has an Intel Xeon W-2104 CPU with 32-GB
memory running Windows server 2016. A SDO image server has an Intel Xeon W-2104
CPU with 32-GB memory running Centos 7. We developed all software programs (SDO
client, SDO image server, and relay server) in Microsoft Visual Studio C++.
Appl. Sci. 2021,11, 8932 11 of 19
Figure 10 shows the network configuration of the proposed system. Every host is
connected to KREONET, having a bandwidth of 10 Gbps or higher, using the Mellanox
40G network interface card. The SDO image server unidirectionally transmits 10 types of
SDO images through the six channels at 30 fps to the relay server. When the three users
access the relay server, the SDO image received through the six channels is merged. Then,
the image is rendered in a virtual space. In contrast, the voice, hand, and head pose data
are transmitted and received bi-directionally through the relay server. Figure 11 illustrates
the educational experience when using the IVR-SDO streaming distance education system.
With the help of a pointer, an expert explains the solar phenomena in detail. Students also
look at the SDO images and ask questions while listening to the explanation. Remote users
are placed in one virtual space; the user’s head and hand motions are tracked by the Vive
HMD and controller and synchronized with their avatar. By pressing the controller button,
the ray exiting the virtual hand is aimed at the desired point.
Figure 10.
Network configuration for IVR-SDO streaming distance education for user experiment.
Users A and B are students, and User C is an expert.
4.2. Network Utilization
Streaming large images for realistic SDO distance education requires a high network
bandwidth. This study used the multichannel-based data transfer method mentioned
in Section 3.3 to utilize the high-bandwidth network resources provided by KREONET.
Figure 12
shows the data transfer rate and network utilization results according to the
number of channels when the SDO images are split-transmitted in six channels from the
SDO server to the relay server. The data transfer rate and network utilization for stable
transmission were verified in an actual transmission experiment while increasing the
number of channels by one to fully utilize the network bandwidth when large data such as
SDO images are transmitted. The experimental results in Figure 12b show that the data
transfer rate and network utilization increased linearly in proportion to the number of
channels and 10 SDO image data can be transmitted without delay.
Appl. Sci. 2021,11, 8932 12 of 19
Figure 11.
Experiencing the IVR-SDO streaming distance education system: (
a
–
d
) Users A and B
(students) receive explanations about the SDO images from User C (expert) and ask questions; (
e
–
h
)
display as seen from the viewpoint of User C (expert).
Figure 13 shows the changes in the network utilization of the relay server when
the three participants, Users A, B, and C, enter the distance education system at regular
intervals. When the education participants access the relay server, the SDO images are
relayed. Hence, network utilization gradually increases at each point in time when the
server is accessed. Quantitatively, the relay server receives approximately 287 Mbps of
data from the SDO image server and relays three times (855 Mbps) the received data to the
three participants.
Appl. Sci. 2021,11, 8932 13 of 19
Figure 12.
Experiment results using the multichannel-based SDO image streaming module. The
data transfer rate and network utilization increased in proportion to the number of channels:
(a) multichannel-based
SDO image streaming from the SDO image server to the relay server;
(b) measurement
results of data transfer rate and network utilization according to the number
of channels.
Figure 13.
Increase in the network utilization of the relay server when three users connect to it one
by one while SDO images are transmitted to the relay server.
Appl. Sci. 2021,11, 8932 14 of 19
4.3. Subjective Measures
In this section, user preferences such as the level of immersion, perceived engagement,
comfort, and desirability of the IVR-SDO distance education system are examined, similarly
as in [
14
,
26
], especially [
26
], who researched the efficacy of VR in distance team-based
learning for students as an engaging platform. To acquire a subjective evaluation on the
VR-TBL experiences, we utilized the well-established Likert-type questions. We modified
the survey to suitably fit our research and performed two pre-tests with the volunteers
before the user study to verify that the questionnaire reflects the intent of our research.
4.3.1. Participants
We recruited 20 unpaid participants (seven females) aged 24–54 years with a mean age
of 29.9 (SD = 7.14) ) from Kwangwoon University, Center of Human-Centered Interaction
for Coexistence (CHIC), and the Korea Institute of Science and Technology (KIST). All
participants majored in engineering fields such as computer science, robotics, mechanical
engineering, and electronic engineering. Before beginning the tests, participants were asked
to answer some binary or 5-point Likert questions (i.e., 1 = strongly disagree to 5 = strongly
agree). Participants reported some experience interacting in virtual environments (e.g.,
gaming). Most participants were not highly experienced with the VR education system
(mean ±SD = 2.12 ±1.6). Two participants had experience using a VR education system.
4.3.2. Apparatus and Procedure
We orchestrated the experiment to elapse 1 h per subject a day. Prior to the experi-
ment, each participant was supplied with an overview of what the SDO is and the two
different education methods over 20 min. After this, each participant filled out a survey
prior to the experiment. The education method using the Hellioviewer for SDO images
and IVR-SDO distance education system were randomly assigned to the participants to
examine the satisfaction of the proposed system. The order of the two approaches was fully
counterbalanced across the 20 participants. The education method using the Helioviewer
allowed the viewer to observe solar events and SDO images based on the timeline, as
shown in
Figure 14
. The participants can exchange questions and answers while select-
ing and observing the SDO images of various spectra. In testing the IVR-SDO distance
education system, two remote students and one expert participated simultaneously while
wearing a Vive HMD and earphones and using a controller for hand interaction. From
the SDO image server, 10 types of images were streamed to the relay server at 30 fps, and
the students and expert accessing the relay server can see the SDO images through the
HMD. They can ask questions and receive explanations via voice conversation and feel
the presence of other users through the head avatars. After all tests were completed, each
participant was asked to answer a 16-question questionnaire with a 5-point Likert scale
from 1—strongly disagree to 5—strongly agree.
4.3.3. Result and Discussion
In Table 2, questions 1–12 ask about preferences for the IVR-SDO education system,
and question 13 asks about comfortableness for HMD-based learning, and questions 14 to
16 compare preferences between the IVR-SDO education system and Helioviewer.
Table 3
summarizes the statistical comparisons between the viewer-based education and IVR-
SDO education methods where there were statistically significant differences between
the two education methods using Wilcoxon Rank Sum tests. According to the results
on the preferences for the IVR-SDO education system, the participants gave a significant
preference to the proposed method for all questions except Q4 and Q7.
Appl. Sci. 2021,11, 8932 15 of 19
Figure 14.
Helioviewer: a solar and heliosphere image visualization tool that enables everyone anywhere to explore the
Sun’s variability.
The results demonstrate that the participants felt that they learned in the IVR-SDO
education environment better than in the viewer-based education environment. In addition,
the IVR-SDO education system provided the necessary tools for learning. Participants also
reported that they were so immersed in the IVR-SDO educational environment that they
forgot they were experiencing education in a virtual space. In the IVR-SDO educational
environment, they could more confidently express their thoughts or ideas than in the
viewer-based educational environment. This study indicates that participants felt that
they were participating in the IVR-SDO educational environment compared to the viewer-
based educational environment. Furthermore, they could easily use the technologies
applied to the proposed educational environment and it offered a comfortable educational
environment. All participants answered that education in the proposed environment was
interesting, and most participants felt that they would receive education if provided in the
IVR-SDO educational environment. Most participants agreed that the tool provided in the
IVR-SDO educational environment was useful in aiding discussion among participants.
Interestingly, all participants felt that learning in the IVR-SDO educational environment
was realistic, and that the expert explanations were helpful.
Appl. Sci. 2021,11, 8932 16 of 19
Table 2. Subjective questionnaire.
No. Question Description
Q1 I felt like I learned in this environment.
Q2 This environment provided the appropriate tools necessary for me to learn.
Q3 I forgot about my surroundings while experiencing this environment.
Q4 I felt confident expressing ideas in this environment.
Q5 I felt engaged in this environment.
Q6 I found that the technology was easy to use.
Q7 I found this to be a comfortable learning environment.
Q8 This was a fun experience.
Q9 I would take a lesson in this format if it was offered.
Q10 The tools provided by the learning environment were useful during the discussion.
Q11 The learning in this environment was realistic.
Q12 The explanations of an expert in this environment were helpful.
Q13 I felt that the HMD was comfortable enough that it did not interfere with learning.
Q14 Given a choice, I would choose this environment over the current dedicated viewer.
Q15 The learning in this environment was more helpful than the viewer-based learning.
Q16 The learning in this environment was more interesting than the viewer-based learning.
Table 3.
IVR-SDO education and viewer-based education methods compared in terms of question-
naire responses; Wilcoxon rank sum tests.
No. Z p No. Z p No. Z p
Q1 −3.934 <0.001 Q5 −4.053 <0.001 Q9 −3.510 <0.001
Q2 −3.938 <0.001 Q6 −3.891 <0.001 Q10 −3.578 <0.001
Q3 −3.985 <0.001 Q7 −1.867 <0.062 Q11 −3.971 <0.001
Q4 −1.265 <0.206 Q8 −4.035 <0.001 Q12 −4.008 <0.001
Overall, all participants agreed or strongly agreed regarding satisfaction with the
environment of IVR-SDO education, as shown in Figure 15. A possible explanation is that
the IVR-SDO education system may provide the sense of being in the same place with other
participants. This system also could allow participants to encourage their participation
to more actively communicate and share ideas. These experimental results have some
similarities with those of the teacher-guided educational VR research [
26
] on VR field
trips. Having a networked education VR setup provides some benefits over the standalone
approach of having a teacher’s recording in the VR space. Most notably, by streaming
the teacher’s video live, the misunderstandings in communication between the students
and the teacher can be resolved on the spot, leading to their reduction and higher gains in
test scores. Our research also streams the SDO images live to be immersively visualized
in the virtual space, peaking the participants’ interest further. Furthermore, similarly
to the results from the VR-TBL experiences research, the feasibility of having a remote
expert teach multiple participants while experiencing co-presence through an education
platform was further verified. However, to answer the question of whether the HMD
was sufficiently comfortable that it did not interfere with learning, only a relatively low
percentage of participants preferred it because of the weight of the headset. This finding
was similarly found in the VR-TBL experiences research and is one of the key issues that
must be addressed for long sessions of education in VR.
Appl. Sci. 2021,11, 8932 17 of 19
Figure 15. Responses to questions for each of the education methods.
For the questions comparing the preferences between the IVR-SDO education system
and Helioviewer, the following results were obtained: nearly 70% of participants agreed
or strongly agreed that, given the option, they would choose the proposed environment
over the current dedicated viewer (Q14, mean
±
SD = 4.20
±
1.02). Most participants
agreed or strongly agreed that learning in the proposed environment was more helpful
(Q15, mean
±
SD = 4.40
±
0.75) and interesting (Q16, mean
±
SD = 4.70
±
057) than
viewer-based learning.
The participants were asked to freely share their opinions after using the IVR-SDO
education system. Positive answers include: “It was nice to be able to see more diverse
images simultaneously and more realistically.”; “The education method was interesting,
and the virtual environment was impressive.”; “The great advantage is that it provides a
greater sense of immersion than a dedicated viewer, and that we can see various environ-
ments at once.”; “Above all, the greatest advantage is that it enables communication with
experts and among class participants.”; “My concentration was definitely higher than when
using the dedicated viewer, and I felt that it was more realistic.”; “It is more intuitive than
a normal screen and makes learning interesting. I think it will be possible to experience
realistic learning.” Participants provided a mixture of positive and constructive comments,
including “If I could select things using the controller, I would have used it like a viewer.”
and “It was a fresh experience. It would have been more interesting if 3D modeling of
the sun was possible.” Comments expressing hope for improvement included “The HMD
equipment was heavy” and “It was good in terms of immersion, but the dedicated viewer
seems to be better for intuitive explanation (operation).”
5. Conclusions
Existing VR educational contents are mostly provided in a standalone form. For
example, students study alone at home or individually experience the same content with
friends in a classroom. Such VR education can help improve individual educational
outcomes but lacks social education cultivated through collaboration. This can be overcome
by distance-education-based VR using network technology. Compared with general online
education, streaming educational content facilitates more vivid education. In this study,
an IVR-based distance education system was proposed to allow multiple remote users to
send, share, and experience SDO images via streaming. The proposed live-streaming-based
SDO online education has the following advantages. First, it enables real-time interactions
to encourage student participation, allowing them to share their opinions and overcome
their fear or reluctance in asking questions. Second, it can improve the sense of realism
more than pre-recorded content because the instructor can explain the material to the
students while sharing screens in real time. Third, avatars and voice interactions with
Appl. Sci. 2021,11, 8932 18 of 19
other remote participants provide a sense of immersion as if they are in the same place.
Fourth, live-streaming-based education can provide a collaborative environment and allow
participants to share their educational content. Furthermore, more enriching educational
content can be provided by inviting experts on the given subject online. However, the
following improvements in terms of usability should be made. Most students felt that
wearing the HMD for a long time was difficult. In addition, they expected explanations
on the SDO images would be displayed in the virtual environment, and that more diverse
interactions using the controller would be added.
Currently, only simple interactions, such as pointing to SDO images, are possible.
Hence, in the future, it is necessary to support more enhanced interaction functions, such
as scaling for the part where a solar event occurs, as well as search and time machine
functions for SDO images.
Author Contributions:
Conceptualization, methodology, J.L.; funding acquisition, project admin-
istration, B.Y.; software, J.S., W.C. and J.L.; validation, W.C. and J.L.; writing—original draft, J.L.;
writing—review and editing, J.L. and B.Y. All authors have read and agreed to the published version
of the manuscript.
Funding:
This work was supported in part by the Global Frontier Research and Development Pro-
gram on Human-Centered Interaction for Coexistence funded by the National Research Foundation
of Korea grant funded by the Korean Government (MSIP)(NRF-2010-0029759), and in part by the
Korea Institute of Science and Technology (KIST) Institutional Program under Project 2E31063.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in
the study.
Data Availability Statement: Not applicable.
Acknowledgments:
This work was supported by KREONET (Korea Research Environment Open-
NETwork), which is managed and operated by KISTI (Korea Institute of Science and Technology
Information). The SDO data were (partly) provided by the Korea Data Center (KDC) for SDO in
cooperation with NASA and KISTI (KREONET), which is supported by the “Next Generation Space
Weather Observation Network” project of the Korea Astronomy and Space Science Institute (KASI).
The authors thank Y. U. Kim and J. H. Jin for their support during the experiments.
Conflicts of Interest: The authors declare no conflict of interest.
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