Assessing Augmented Reality Possibilities in the Study of School

Computer Science

Vasyl P. Oleksiuk

1,2 a

and Olesia R. Oleksiuk

3 b

Ternopil Volodymyr Hnatiuk National Pedagogical University, 2 M. Kryvonosa Str., Ternopil, Ukraine

Institute for Digitalisation of Education of the National Academy of Educational Sciences of Ukraine, 9 M. Berlynskoho

Str., Kyiv, 04060, Ukraine

Ternopil Regional Municipal Institute of Postgraduate Education, 1 V. Hromnytskogo St., Ternopil, Ukraine

Keywords:

Educational Augmented Reality, Mobile Learning, School Computer Science, STEM Project, Augmented

Reality Applications.

Abstract:

The article analyzes the phenomenon of augmented reality (AR) in education. AR is a new technology that

complements the real world with the help of computer data. Such content is tied to speciﬁc locations or

activities. Over the last few years, AR applications have become available on mobile devices. AR becomes

available in the media (news, entertainment, sports). It is starting to enter other areas of life (such as e-

commerce, travel, marketing). But education has the biggest impact on AR. Based on the analysis of scientiﬁc

publications, the authors explored the possibilities of using augmented reality in education. They identiﬁed

means of augmented reality for teaching computer science at school. Such programs and services allow

students to observe the operation of computer systems when changing their parameters. Students can also

modify computer hardware for augmented reality objects and visualize algorithms and data processes. The

article describes the content of author training for practicing teachers. At this event, some applications for

training in AR technology were considered. The possibilities of working with augmented reality objects in

computer science training are singled out. It is shown that the use of augmented reality provides an opportunity

to increase the realism of research; provides emotional and cognitive experience. This all contributes to

engaging students in systematic learning; creates new opportunities for collaborative learning, develops new

representations of real objects. The authors studied the relationship between some factors that inﬂuence the

introduction of augmented reality in school computer science, such as: the age of teachers, student interest,

the use of gadgets in education, play and entertainment style of learning. Several augmented reality STEM

projects have been selected. On the basis of expert evaluation, the attitude of teachers to these projects was

determined and the most rated of them were evaluated.

1 INTRODUCTION

Today, the topical areas of research for scholars in ed-

ucation are the didactic potential of digital technolo-

gies and methods of their application. Modern digital

tools create opportunities to complement real space

with contextual, dynamic, visual content. Accord-

ingly, such technologies are increasingly being imple-

mented and explored in education.

Augmented reality (AR) is a technology that en-

riches human sensations with digital data and thus

mixes the real and virtual environment. It uses virtual

information as an additional useful tool. As a result,

https://orcid.org/0000-0003-2206-8447

https://orcid.org/0000-0002-1454-0046

a new, more informative and stimulating environment

is created.

The principle of the AR program is to use the sen-

sors of the device to read the environment and supple-

ment it with digital, interactive content.

AR applications can be used on different devices

such as desktops, laptops, mobile devices. But most

AR programs work on smartphones, tablets. Smart

glasses, headphones, and other controllers can be fur-

ther connected to mobile devices. Built-in cameras,

GPS sensors, gyroscopes and other sensors are used

to recognize objects, images and scenes. After suc-

cessful recognition, relevant digital content becomes

available and is displayed on screen. The purpose of

their application is to combine the real environment

Oleksiuk, V. and Oleksiuk, O.

Assessing Augmented Reality Possibilities in the Study of School Computer Science.

DOI: 10.5220/0010927900003364

In Proceedings of the 1st Symposium on Advances in Educational Technology (AET 2020) - Volume 2, pages 5-19

ISBN: 978-989-758-558-6

with digital content. This enables the user to receive

more information about the environment than is avail-

able to him in the real world. The advantage of AR is

not only to increase the available information in the

environment, but also to create an attractive represen-

tation of the world. For this reason, AR is used in

many industries such as marketing, design, medicine,

entertainment, tourism, education (Iatsyshyn et al.,

2019; Hruntova et al., 2018; Rashevska and Soloviev,

2018; Striuk et al., 2018; Zelinska et al., 2018).

The ability to improve the visualization of objects

and processes in the learning environment through in-

teractive digital content has generated interest in the

using of AR applications for educational purposes.

New possibilities of AR technologies for teaching

and learning has been analyzed in (Shepiliev et al.,

2021). Iatsyshyn et al. (Iatsyshyn et al., 2019, 2020)

described examples of AR applications in such in-

dustries as the entertainment and gaming industries,

tourism, sales and presentations, education.

Classiﬁcation of directions of using of augmented

reality in education and practice of using AR appli-

cations are given in the publications (Ranok, 2020;

Yuen et al., 2011). The analysis of the papers shows

that AR is implemented to different disciplines of ele-

mentary and secondary school (Coimbra et al., 2015;

Matsokin and Pakhomova, 2020; Matviienko, 2015;

Midak et al., 2021) and in the higher education insti-

tutions (Barkatov et al., 2020; Klochko et al., 2020;

Lavrentieva et al., 2019, 2020). These and many

other researchers have found that AR technologies in-

crease the level of success and motivation of pupils

and students (Gutierrez and Fernandez, 2014; Kesim

and Ozarslan, 2012).

Scientists say that learning in the AR can have a

positive impact on the development of spatial imagi-

nation, the formation of abstract concepts, the trans-

fer of knowledge, the acquisition of digital skills and

experience. Dyulicheva et al. (Dyulicheva et al.,

2020), Kolomoiets and Kassim (Kolomoiets and Kas-

sim, 2018), Osadchyi et al. (Osadchyi et al., 2020),

Tkachuk et al. (Tkachuk et al., 2017) identiﬁed AR as

an important prerequisite for implementing effective

strategies to achieve the goals of inclusive education.

Now, AR is not only useful for studying individual

subjects or individual students. It can also be applied

to the development of new approaches to learning, in

particular the concept of STEM (Shapovalov et al.,

2018; Valko et al., 2019).

AR technologies can be an effective tool of orga-

nizing interaction and collaboration to present learn-

ing outcomes. Other studies, such as (Coimbra et al.,

2015; Matsokin and Pakhomova, 2020) concluded

that AR is particularly suited for teaching subjects

that need to form difﬁcult for understanding in the

real world concepts (Kravtsov and Pulinets, 2020;

Valko et al., 2019). Matviienko (Matviienko, 2015)

described his experience in creating a computer mu-

seum. He used augmented reality technology to vir-

tualize objects. The author developed an interdisci-

plinary study excursion in the museum.

The common practice of using AR in education

is to create supplementary books. Some didactic as-

pects of mixed reality books have been studied by

Kravtsov and Pulinets (Kravtsov and Pulinets, 2020),

Panchenko et al. (Panchenko et al., 2020). When AR

is used, books are transformed into dynamic sources

of information. Augmented reality technology has

made it possible to “revive” its pages (Ranok, 2020).

Now this technology is used in cognitive books such

as encyclopedias, atlases, books about space, struc-

ture of the Earth, dinosaurs, for reproduction of his-

torical events. Gradually, from coloring books and

fairy-tales, augmented reality technology is being ex-

tended to the production of educational products.

That is, they are gradually moving from game tech-

nology to learning. For example, students use special-

ized software for joint study of mathematics, physics,

chemistry, geometry (Coimbra et al., 2015; Iatsyshyn

et al., 2019; Kramarenko et al., 2019; Matviienko,

2015; Zinonos et al., 2018). These studies have shown

the beneﬁts of using AR books as a tool to increase

children’s motivation. Books in the AR have also

proven to be effective means of concepts formation.

AR technology is developing quite rapidly. As

a consequence, research in education does not have

time to provide theoretical understanding or develop

a systematic methodology for creating appropriate

learning tools. We believe that the use of AR tech-

nology is a modern trend, and therefore research in

this ﬁeld is relevant and timely.

The purpose of this study is to explore the pos-

sibilities of using augmented reality technology at

school, in particular when teaching computer science.

Objectives of the study are:

1. To analyze the experience of using AR technolo-

gies in education;

2. To ﬁnd out the possibilities of using augmented

reality technology in teaching computer science;

3. To experimentally test the attitude and readiness

of teachers to use AR in teaching of computer sci-

ence.

4. To deﬁne some STEM projects with augmented

reality technologies. Assess opportunities for

their implementation in secondary schools

Object of study is the process of teaching com-

puter science in secondary school.

AET 2020 - Symposium on Advances in Educational Technology

Subject of research is augmented reality technol-

ogy as a mean of teaching computer science in sec-

ondary school.

2 PROBLEM STATEMENT

In the Ukrainian education system, postgraduate insti-

tutes are responsible for implementing innovations in

primary and secondary schools. These institutions re-

main an important component in the process of com-

puter science teacher training. This article will de-

scribe the experience of trainings organization at the

Ternopil Regional Municipal Institute of Postgradu-

ate Education (TRMIPE). The purpose of these train-

ing’s is to develop teachers’ skills for augmented re-

ality application. The article will explore the ser-

vices and their functionality for the computer science

lessons. Augmented reality allows the student to vi-

sualize complex spatial connections and abstract con-

cepts. Therefore, with their help, the teacher can de-

velop abilities that are difﬁcult to form in a traditional

learning environment (Oleksiuk et al., 2017; Pono-

mareva, 2021; Spirin et al., 2018; Vlasenko et al.,

2019).

Technologies for augmenting reality with digital

objects (perhaps not just digital ones) can be condi-

tionally positioned between two polar variants of pos-

sible realities: the reality we live in and virtual reality

(VR) (ﬁgure 1).

Reality is a philosophical term that means what

actually exists in physical space, and physical space

itself. Virtual reality is the absolute absence of real

objects. It is a technically created world that is trans-

mitted to man through his senses: sight, hearing,

touch and others.

Quite often, a combination of these realities is

called Mixed Reality (MR). Virtual reality can be

ﬁlled with people, weather, events, and more. If

images of these objects are broadcast from the real

world, then the result will be augmented virtual real-

ity (AV) technology. At the current level of develop-

ment, AV technology is virtually unused, but in the

future it can be much more impressive than AR and

VR.

Azuma (Azuma, 1997) identiﬁed augmented real-

ity features such as:

• combining the real and the virtual world;

• interactivity;

• combining the real and the virtual world.

The augmented reality system is the mediator be-

tween man and reality. Therefore, it must generate

a signal for one of the human’s perception organs.

Therefore, according to the type of presentation of in-

formation in the AR system, they can be classiﬁed

such as visuals, audio, and audiovisuals.

By type of sensors for the acquisition of data from

the physical space there are AR systems:

• Geo-location. They focus on signals from GPS or

GLONASS positioning systems.

• Optical. Such systems process the image obtained

from the camera. The camera can move with or

without the system.

Augmented reality systems can be classiﬁed by

user interaction. In some systems, the user has a pas-

sive role. He only watches the system react to changes

in the environment. Other systems also require active

user intervention. There he or she can control the op-

eration of the system and modify its virtual objects.

According to this feature, the systems are divided into

ofﬂine and interactive.

Let’s look and analyze the program tools that are

most appropriate to use when teaching computer sci-

ence at school. Based on the analysis of articles and

sites, we can say that there are very few such applica-

tions and services. Therefore, teachers and scholars

are looking for ways to use augmented and virtual re-

ality to improve and support school-based learning.

But to make the right choice, they need to know the

requirements for existing applications and services

and the limitations of using them. As the experience

suggests, most Ukrainian schools do not have high-

end AR or VR devices.

The beneﬁts of AR are the ability to increase moti-

vation, emotional perception of the students’ learning

content. The highest level of application of these tech-

nologies is the involvement of students in the creation

of their own virtual worlds. At the same time, teachers

should also be interested in implementing such inno-

vations. They should have as little doubt as possible

about the capabilities of AR technologies and their

own capabilities.

Among augmented reality applications, there are

those that can be used in the study of various subjects,

not just computer science.

The Quiver application allows the teacher to cre-

ate coloring books with augmented reality. With the

app, students can interact with objects they create.

Painted images are transformed on the gadget screen

into augmented reality. There is an opportunity to

play with animated characters. The teacher can use

the Quiver app in the lesson as a tool for developing

creative skills or for pupils’ reﬂection.

WallaMe is a platform that can be implemented

to integrate augmented reality into the learning pro-

cess. WallaMe Ltd launched the application in 2015.

Using this app is an easy way for both teachers and

Assessing Augmented Reality Possibilities in the Study of School Computer Science

Figure 1: Reality-virtuality continuum (Milgram and Kishino, 1994).

students. WallaMe is a free iOS and Android applica-

tion. It allows users to hide and share messages in the

real world using augmented reality. These messages

appear as a result of changing the geolocation of the

smartphone. In addition, the WallaMe app provides

students and teachers with additional tools such as:

• a library of stickers;

• advanced drawing tools;

• tools for working with text;

• simple and minimalistic graphics and elements of

the interface;

• connection to a smartphone camera;

• comment option;

• accessible to all or private messages.

WallaMe allows a teacher to take a picture on a

smartphone and leave a picture or message there. The

object created in this way is linked to the image and

geographical coordinates. Another app user sees a

message icon on the map. He or she will only be able

to ﬁnd out it if he points his camera at this wall.

The application can be used in the study of com-

puter science to create knowledge maps or tests in

augmented reality. For example, a teacher creates a

geotag on a speciﬁc computer hardware device. The

learner should identify and add text with the charac-

teristics of this device. In the study of programming,

students can perform in augmented reality the task of

completing a code snippet, determining the values of

variables, ﬁnding errors. In the case of a positive ex-

perience, the teacher can use the application to create

integrated tasks, such as web quests (Wang, 2017).

One of the most popular mobile apps is Google

expedition. It is an immersive education application

that allows teachers and students to explore the world

through over 100 augmented-reality tours. In addi-

tion, the app offers more than 1,000 virtual reality

tours (edu.google.com, 2020). They can be used ef-

fectively by teachers of various subjects.

Unfortunately, as of now, only 2 expeditions are

available for computer science in AR mode:

• Computers. The tour allows students to learn and

explore how different components of a computer

function.

• Introduction to Computer Graphics. It covers top-

ics such as: History of Computer Graphic, Creat-

ing a 3D World, Modeling, Texturing and Shad-

ing, Ray Tracing and Light, Rendering.

Google Expedition provides collaborative learn-

ing opportunities. The teacher has the opportunity to

download the completed tours and invite students to

see them in augmented reality. Unfortunately, creat-

ing your own AR Tours with Tour Creator is not cur-

rently available. For now teachers can use an exter-

nal tool such as cospaces.io. The service allows them

to create or import three-dimensional models. These

objects can be offered to students for using on mobile

devices.

CoSpaces.Edu service provides great program-

ming experience. It enables students to learn by do-

ing, using the various tools available with the VR and

AR technologies. All features in CoSpaces.Edu can

be adapted to ﬁt different class subjects and learning

objectives. The platform uses a visual programming

language ideal for beginners or gets access to script-

ing languages for more advanced coding. With its fun

Lego-like colored blocks, CoBlocks is the ideal so-

lution for junior pupils. More advanced coders can

have fun coding scripts to add interactions and events

or even create games (Cospaces, 2020).

The platform enables the collaboration of the

teacher with several students. They can work on

individual or collaborative projects. Most of these

projects these projects can be saved in AR. Aug-

mented Reality lets students project their own cre-

ations onto any plane surface in the real world by

looking through the screen of their device.

The advantage of the system is the use of single

sign-on technology. It integrates well with cloud ser-

vices, including Google Workspace for Education.

AET 2020 - Symposium on Advances in Educational Technology

Drezek (Drezek, 2020) uses the CoSpaces ser-

vice to perform tasks for students such as creating

an animal habitat, creating a game about holiday tra-

ditions in virtual and augment reality to share with

the schools around the world. Michael says that stu-

dents in own space can experience what they design

and program in virtual and augmented reality.

In our opinion, the highest level of implementa-

tion of AR in the teaching of computer science is

the development of students own elements and scenes

in augmented reality. According to (Boonbrahm and

Kaewrat, 2014; Cakir and Korkmaz, 2019; Youm

et al., 2019) one of the most popular and productive

means of achieving this goal is the Unity engine and

the Vuforia library. One of the many advantages of

Unity is that it is a free game engine that has the pos-

sibility to deploy to many different platforms as iOS

and Android. This, combined with the Vuforia AR

platform, makes it possible to assign a virtual camera

in the 3D scene that is linked to an image tracker. This

combination can then be deployed to a smart phone or

tablet. Finally, it is possible to utilize the camera on

the device in order to mix the 3D scene with the cam-

era image (Kjellmo, 2013).

We compared these tools according to the main

criteria (type of tool, equipment, interaction with the

student, place in training, cost). Table 1 contains a

comparative analysis.

In addition to AR services created by IT ﬁrms,

there are also authoring AR applications to support

computer science training. Let’s look at some of

them.

AR-CPULearn is based application for learning

CPU. It was created by scientists of Universiti Ke-

bangsaan (Malaysia). AR-CPULearn was imple-

mented as an exercise activity for computer organi-

zation and operating system students in higher ed-

ucation. This applications offer for execution some

exercises with overlaid multimedia information. For

example, answer a few questions based on a train-

ing video; name the main components of the moth-

erboard, explain how the processor and motherboard

work (Boonbrahm and Kaewrat, 2014).

The Mixed Reality Laboratory (Bond University

and CQUniversity, Australia) is involved in the de-

velopment of mixed reality applications for solutions

to complex pedagogical problems. In our opinion

the “Network and ICT modeling” project is the most

exciting startup of this lab. The purpose of this

project is to use the augmented reality visualization

method to help students understand the theoretical

model of open systems interconnection (OSI) and

its implementation as a stack of TCP/IP protocols

(www.mixedrealityresearch.com, 2019).

The application simulates in augmented reality

the construction of simple computer networks. This

simulation uses a ﬁve layer TCP/IP model to visual-

ize how packets are interpreted and distributed. The

simulation utilizes augmented reality markers which

are detected and tracked in 3D space by smartphones

cameras. When students are focusing a camera on the

marker then they can see a multiple network devices

such as modems, routers, switches, wireless AP etc.

These devices can be connected to the network. Vi-

sually, this will be shown as lines on the smartphone

screen.

The application visualizes packets from devices

that generate trafﬁc. This visualization corresponds

to the TCP/IP model. The demo shows not only traf-

ﬁc but also individual packages and their headers. Vi-

sualization in augmented reality is dynamically trans-

formed as the network topology changes. The appli-

cation also demonstrates signal conditioning between

wireless devices. The student can select any device

as the source and as the recipient when transmitting

trafﬁc. As a consequence, he or she will see the vi-

sualization and model of this process in augmented

reality.

3 RESULTS AND DISCUSSION

We continued our research on augmented reality

training. The training was conducted at TRMIPE

from September to November 2019. Participants

of the trainings were 2 groups of computer science

teachers (20 people in each group). They could

choose augmented reality topics. We used different

techniques to teach different topics (table 2).

We have conducted a survey to verify attitude and

readiness of computer science teachers to use AR in

teaching. The participants of the training ﬁlled out

a questionnaire. They evaluated AR applications by

the factors of frequency and usefulness of their use

in training. The questionnaire was based on the us-

ability measurement software (Serdiuk, 2014). The

questionnaire contained 12 questions. The answer

options were formed according to the 5-point Lik-

ert scale. They determined the ratio of the respon-

dents from completely negative (0 points) to com-

pletely positive (4 points). This distribution prevented

the respondents from making unreasonable choices

about the mean of the answer. We avoided ques-

tions in the negative form when forming the ques-

tionnaire. We also used the Likert scale to deter-

mine respondents’ age (from 0 points – age over

60 years to 4 points – age 20-30 years). The

entire table of respondents’ scores can be down-

Assessing Augmented Reality Possibilities in the Study of School Computer Science

Table 1: Augmented reality program tools.

Name Software Equipment Interaction Place Cost

Quiver Application Mobile device One user Reﬂection Commercial, Free

WallaMe Application Mobile device Many users Quests, Learn-

ing Projects

Free

Google Expedition Application Mobile device Many users Demonstration,

STEM-projects

Free

CoSpaces Edu Application, Site Mobile device, PC Many users Programming,

development

Commercial, Free

Vuforia AR Application PC One user Development Commercial

Unity Application PC Many users 3D-modeling Commercial, Free

Poly Library PC Many users 3D-modeling Free

SketchUp Application, Site PC One user 3D-modeling Commercial, Free

with a state grant

Table 2: Augmented reality training topics.

Topic number The name of the topic Training technique

1. The concept of virtual and augmented reality Conversation

2. Types of augmented reality Mini-lection

3. Examples of augmented reality Demonstration

4. Checking mobile gadgets for support of AR technologies Work in groups

5. Prospects for the use of AR technologies in education Training exercise, brainstorming

6. Create your own augmented reality effects Individual work

7. Develop a list of required AR models for the computer

science course

Collaboration

loaded from the link https://drive.google.com/ﬁle/d/

1zIS8c0RForHw8KA49qBQGhynQvAcpzTy

To check the internal consistency of the question-

naire, we calculated the Alpha Cronbach coefﬁcient.

Its value (α

= 0.73) can be considered acceptable.

We considered the latent indicator of each question

to be the average of all respondents’ scores. Table 3

shows the list of questions and their respective mean

values.

We have selected the following signiﬁcant average

values of respondents’ scores:

• less than 1.5 points – the indicator is not almost

manifest;

• 1.5-2.0 – the indicator is weak;

• 2.0-2.5 – the indicator is sufﬁcient;

• more than 2.5 – the indicator is strong.

The obtained average values of the indicators are

shown in the following diagram (ﬁgure 2). Signiﬁcant

values of indicators are highlighted with colors.

As can be seen from the diagram, a weak mani-

festation is found in indicators related to the readiness

and use of AR in the real learning process. However,

the study found strong and sufﬁcient manifestations

of the indexes regarding the usefulness, motivation for

use and pedagogical potential of AR applications. At

the trainings we observed the interest of teachers, es-

pecially when they saw in AR their own digital world.

Another objective of our study was to determine

the dependencies between these indicators. To do

this, we used a correlation method. To determine the

speciﬁc correlation coefﬁcient, we checked the nor-

mality of the distribution of each indicator. We have

performed the Shapiro-Wilk test of normality. Here

are the results of the R-function shapiro.test for all in-

dicators:

• p-value(UGT) = 0.01297000;

• p-value(SUG) = 0.00004502;

• p-value(MAR) = 0.00186300;

• p-value(CAR) = 0.00386600;

• p-value(EAR) = 0.00124000;

• p-value(ARI) = 0.00024080;

• p-value(RAR) = 0.00066520;

• p-value(ARE) = 0.00531300;

• p-value(ARC) = 0.00011270;

• p-value(PAR) = 0.00019137;

• p-value(ARA) = 0.00235700.

Since the asymptotic signiﬁcance is less than 0.05,

the distribution is not normal. In this case, the Spear-

AET 2020 - Symposium on Advances in Educational Technology

Table 3: Questionnaire items.

Question

The content of the question

Average of

code respondents’ scores

UGT How often do you use gadgets in teaching? 2.38

SUG How often do your students use their own gadgets in learning? 1.90

MAR How often do you use AR apps in computer science teaching? 1.80

CAR How often do your colleagues use AR in computer science teaching? 1.90

EAR How easy is it for you to learn AR technologies? 1.98

ARI Using AR in computer science teaching can be interesting 2.43

RAR I feel ready to use AR 1.83

ARE AR is entertaining 2.05

ARC AR used in computer science training can be credible 2.33

PAR My proﬁciency level of AR 1.90

ARA The use of AR is advisable in the study of computer science 2.58

Figure 2: Distribution of indexes.

man rank factor should be used. It is a statistical mea-

sure of the strength of a monotonic relationship be-

tween paired data. Correlation is the size of the ef-

fect. The coefﬁcient determines whether the quanti-

tative factor inﬂuences the quantitative response. Its

absolute value is usually interpreted according to the

following ranges:

• 0.00 – 0.19 – relationship is very weak;

• 0.20 – 0.39 – relationship is weak;

• 0.40 – 0.59 relationship is moderate;

• 0.60 – 0.79 relationship is strong;

• 0.80 – 1.00 relationship is very strong.

Its positive value shows the existence of a direct

relationship between factor and response. A negative

coefﬁcient indicates the reverse relationship.

We used the R-library “corrplot” to calculate and

display the rank correlation coefﬁcients. All corre-

lations are signiﬁcant at 0.05 level. We considered

indicators with a moderate and strong correlation. In

the ﬁgure 3, they are highlighted in red.

The ﬁrst line of the table indicates a strong rela-

tionship between teachers’ age and their experience

with AR use. That is, younger teachers are easier to

learn AR applications, they are more conﬁdent in their

ICT competencies. Therefore, they are more likely to

use AR in computer science training.

The study found a strong link between the fre-

quency of use of AR technology in teaching computer

science and the beliefs of teachers about the feasibil-

ity of its use. A positive strong relationship was also

found between teachers’ proﬁciency level and the fre-

quency of AR use.

The use of augmented reality by colleagues has a

positive moderate impact on the same activities of the

interviewed teachers. The Bring Your Own Device

(BYOD) approach also helps to incorporate AR into

learning. Teachers who are learning to work with AR

applications are more positive about the credible data

that this technology displays.

In addition, the survey found several indicators

that were poorly explained. First of all, there is no sig-

niﬁcant positive correlation of ARE (Entertainment of

Assessing Augmented Reality Possibilities in the Study of School Computer Science

Figure 3: Matrix of plots with a indicators data set.

AR) with other survey questions. This may mean that

teachers do not pay enough attention to the gaming

approach in teaching. A similar situation was found

with the RAR indicator. That is, despite some level

of AR using, teachers still do not consider themselves

ready for it.

We also found no signiﬁcant correlation between

the use of AR and the fact that these technologies are

interesting and motivating. Also surprising is the fact

that communication with colleagues has no effect on

the readiness of a computer science teacher. In our

opinion, these paradoxes are a result of the lack of ap-

propriate methodology. In general, we can say that

negative research results require rethinking and fur-

ther exploration.

Figure 4 contains a matrix of plots for indicators

with signiﬁcant correlation. These plots show the dis-

tributions of values for the indicators “PAR”, “MAR”,

“ARA”, “CAR”, the corresponding diagrams and the

correlation coefﬁcients between them.

4 EVALUATION OF SOME STEM

PROJECTS WITH

AUGMENTED REALITY

Today, STEM projects are becoming very popular in

schools. Their implementation allows you to integrate

knowledge from different subjects. Solving real prob-

lems determines the practical direction of tasks. At

the same time, students generate new ideas and de-

velop their own competencies, such as mathematical,

technological, social. Mobile applications with aug-

mented reality allow to increase the interest of modern

schoolchildren in the study of natural sciences. First

of all, this is possible thanks to advanced multimedia

technologies. These tools make it possible to “revive”

and clearly represent complex concepts.

We invited teachers to consider and evaluate

several STEM projects at the training. In these

projects, augmented reality mobile applications were

proposed. These applications are free and available

AET 2020 - Symposium on Advances in Educational Technology

Figure 4: Matrix of plots with signiﬁcant correlation values.

for download in Google Play and App Store.

Project 1. Skyscrapers. In this project, we

used the Skyscrapers AR mobile application to study

3D models of ﬁve famous high-rise buildings in the

world. Today, engineers use robust materials and in-

novative schemes to design buildings of this height.

So, it would be good for students to implement this

STEM project. In computer science lessons, they

study augmented reality technology, its capabilities

and terminology. In math lessons, children learn to

build diagrams. In language lessons, they discuss the

project in dialogues and prepare essays on construc-

tion technologies. In geography lessons, students can

explore the soil for building skyscrapers. In tech-

nology lessons, children create models of skyscrapers

and design a device to test their own buildings.

Students during the project should ﬁnd answers to

questions such as:

• How to choose a building material?

• How to check whether the manufactured materials

meet the advertised speciﬁcations?

• How long will the ﬁnished product last?

• Are the materials safe to design and use?

Finally, it is advisable to discuss with students

what career prospects they see after participating in

this STEM project.

Project 2. Da Vinci Machines. In this project, we

used a mobile application with augmented reality to

study the models of the famous inventor Leonardo da

Vinci. This project is related to history, mathematics,

technology, art. Students will learn about the biogra-

phy of Leonardo da Vinci in history lessons. In com-

puter science lessons, they learn to search, collect,

process, present data from various sources. The AR

application is designed so that children have the op-

portunity to work with two layouts of pictures-labels:

horizontal (the picture is located on the desk) or verti-

cal (on the stand, interactive whiteboard, screen, etc.).

The teacher can offer students to study such models

as: Helicopter da Vinci, “Self-supporting” bridge da

Vinci, Tank da Vinci, Catapult da Vinci.

In technology lessons, it is advisable to organize

the practical manufacture and testing of these models.

For example, a self-supporting bridge can be made of

simple materials, such as ice cream sticks.

With their own catapults, students can explore the

mechanical motion of a body thrown at an angle to the

horizon, to check the law of conservation of mechan-

ical energy. It is important for the project that chil-

dren study 3D models in AR applications and com-

Assessing Augmented Reality Possibilities in the Study of School Computer Science

pare them with hand-made devices. Shooting distance

competitions should also evoke positive emotions in

children.

Project 3. Bridges. Today, bridges are built in

different shapes, sizes and materials. What makes a

bridge the strongest? Project participants learn about

this by building simple paper bridges. The children

can then measure the maximum allowable weight for

each such sample. Students also use the “Bridges

AR” application to explore some models.

In this project, important issues for research are

such as:

• identiﬁcation of the main types of bridge struc-

tures;

• explanation of the importance of bridges in human

life;

• study of the main characteristics of bridges and

parts for their

• construction (for example, the distribution of

compressive and tensile forces)

• building a model of your own bridge from simple

materials;

• experimentally check the maximum load that can

withstand the constructed structure.

As a development of this project, it is advisable for

the teacher to offer students additional practical tasks.

Here are some of them:

• Try to build bridges from other household mate-

rials, such as aluminium foil, wax paper or card-

board. Which material is the strongest?

• Experiment with different shapes. What happens

if I roll up a sheet of paper in the shape of a tube

or a triangle?

• Try making a longer bridge by gluing two sheets

of paper together. How long can you skate a

bridge before it collapses under its own weight?

• Is bridge design important?

• How safe are different bridges?

• Are there bridges on your way to school or near

your house? What type are they?

Such a project can be proposed for a science fair.

Children will probably also ﬁnd interesting stories

about professions related to objects of the project.

Project 4. Notable Women. It’s no secret that

there have always been women in science. They con-

ducted research in various sciences. Some of them

made important discoveries.

Studying such stories is important for girls to see

themselves as future scientists. With the “Notable

Women” mobile application, students will be able to

read about an outstanding female scientist, her ideas

and research. It is also advisable to create appropriate

presentation materials such as info-graphics, videos,

booklets, posters, etc.

As a result of presenting these materials, students

should see the inﬂuence of many women throughout

history and think about the thesis that “power is the

ability to inﬂuence”. The completion of the project

can be held as a discussion on the question “What is

the relationship between power and inﬂuence”?

Project 5. The universe. The content of the

project is to study the structure of the universe and

study astronomy using the Big Bang AR application.

This software is the result of a collaboration between

CERN and Google Arts & Culture. It will allow stu-

dents to see the shape of the universe in the palm of

their hand, to witness the formation of the ﬁrst stars,

our solar system and the planet Earth. Children will

be able to immerse themselves in the mystery of the

early universe and watch events unfold around them,

for example in their own classroom.

It is advisable for the teacher to ask students to

make a model of the solar system and calculate the

size of the planets. To see how much space there is

between different objects in the solar system, students

will have to practice with fractions.

The task of technology may involve the manufac-

ture of models of planets. Children should think about

whether it is possible to place “planets” so that their

model is proportional to real orbits.

Students can work in groups to solve problems

such as:

• search for scale factor;

• calculating the size of the planets;

• creation and processing of graphic 3D models.

Such tasks develop mathematical skills in scaling,

and allow a better understanding of space scales. With

the help of the Big Bang AR application, the project

participants should summarize the concepts and visu-

alize the basic concepts.

Unlike traditional classroom teaching, STEM

projects bring students closer to practice, bridging the

gap between theoretical problem solving and practical

implementation of acquired knowledge. Often in the

project the need to use knowledge from different dis-

ciplines contributes to the awareness of new material.

Career discussions can help students make important

connections between the lesson in the classroom and

the speciﬁcs of STEM professions in the real world.

We conducted some research to understand the

attitude of practicing teachers to the STEM projects

outlined above. Expert evaluation was chosen as the

main method of the experiment. Experience shows

AET 2020 - Symposium on Advances in Educational Technology

that it is effective for assessing the qualitative charac-

teristics of educational methods in various scientiﬁc

studies (Kuzminska et al., 2019). Decision-making by

experts is based on a reliable presentation of the cur-

rent situation, a correct understanding of the essence

of the methodology and the completeness of the char-

acteristics of its components.

We selected 64 computer science teachers as

experts. They attended TMPIRE teacher training

courses in 2020. To estimate the desired sample size,

we used the results of (May and Looney, 2020). To

ensure the quality and uniformity of expert assess-

ments, we selected teachers according to criteria such

as:

• Work experience more than 10 years;

• 80–90% success rate of learning in TMPIRE;

• The highest national professional category;

• Experience in using augmented reality technolo-

gies.

We asked these teachers to evaluate the projects

described above according to the following criteria.

Cr1. Relevance of the project as the importance of

the project for students. Here we understood the

integrated indicator of the project. It determines

the possibility of student development through

a combination of cognitive, research interdisci-

plinary activities of students.

Cr2. Realism of the project tasks and availability of

execution. The criterion evaluates the possibil-

ity of project implementation by students of a

certain age group, the compliance of its tasks

with the level of preparation of students.

Cr3. Possibility of project development. The inte-

grated indicator involves assessing the prospects

of the project through the expansion of re-

search objects, participation in afﬁliate pro-

grams, proﬁt The content of the project is an

information component.

Cr4. The criterion should assess the possibility of de-

veloping ICT competencies, in particular their

skills for the use of augmented reality applica-

tions.

The experts ranked each of the projects according

to these criteria. The evaluation was performed on an

ordinal scale from 1 to 5. One point was awarded

to the least signiﬁcant indicator and ﬁve points to

the highest signiﬁcant one. We summarized the re-

sults of the survey in the table. To transform evalu-

ation into ranking, we asked experts to evaluate all

projects according to the ﬁrst criteria, then accord-

ing to the second, third, and fourth. The table is

available by the link https://drive.google.com/ﬁle/d/

1xkuiKZUF33nMYNwnCaQaOSkuErLJXqxb.

The most obvious value of the criterion is its over-

all rating (average rating), which is determined by all

experts. This statement is also true for projects. How-

ever, it is necessary to check whether this rating is

not accidental. This means that we need to check the

consistency of expert assessments. Since the distri-

butions of estimates by all criteria and by all projects

are not normal (p-value < 2.2× 10

−16

), we should use

non-parametric criteria to process these statistics. As

is known, the Kendall rank correlation coefﬁcient is

used to determine the relationship between only two

variables. To assess the agreement of more than two

evaluators, it is advisable to use Kendall’s coefﬁcient

of concordance (W).

Statistical processing of ranking results was car-

ried out using the R language. In particular, we used

its libraries such as: nortest, irr, Kendall, DescTools,

ggplot2.

To calculate the coefﬁcient W, we used the func-

tion:

KendallW ( t c r 1 , c o r r e c t = FALSE ,

t e s t = TRUE, na . rm = FALSE)

where

• tcr1 is a transposed dataframe of evaluations of all

projects according to the 1st criterion;

• correct is a parameter that determines the need to

use the emission correction when calculating W;

• test is a logical indicating whether the test statistic

and p-value should be reported;

• na.rm is a parameter to skip empty score values.

The results of the calculation of W for criteria 1-4

are presented in table 4.

Table 4: Generalized data for calculating the concordance

coefﬁcient W for criteria.

Kendall chi-squared P-value W

Cr1 152.79 < 2.2 × 10

−16

0.60

Cr2 138.70 < 2.2 × 10

−16

0.54

Cr3 157.82 < 2.2 × 10

−16

0.62

Cr4 130.93 < 2.2 × 10

−16

0.51

To interpret the obtained results, we used the fol-

lowing ranges of values of the coefﬁcient W (May and

Looney, 2020):

• 0.01– 0.20 – poor agreement;

• 0.21– 0.40 – fair agreement;

• 0.41 – 0.60 – moderate agreement;

• 0.61 – 0.80 – good agreement;

Assessing Augmented Reality Possibilities in the Study of School Computer Science

• 0.81 – 1.00 – very good agreement.

From these data we can reject the zero and accept

the alternative hypothesis of the existence of agree-

ment between experts. Unfortunately, we have to state

that the assessments of experts on the criteria of re-

alism and development of ICT competencies are less

consistent. This indicates a difference in the estimates

of this criterion for almost all projects.

We additionally performed the calculation of the

coefﬁcient W for projects (table 5). We took into ac-

count that the same project received the same points

from the experts. Therefore, the “correct” parameter

was used in the KendallW function. It corrects the

calculation of W if there are related ranks.

As can be seen from the table, the Bridges project

was ranked by experts on fair agreement. Instead,

DaVinci and Woman received good values of W coef-

ﬁciente.

Therefore, the sums or averages of expert esti-

mates for almost all projects can be objective indi-

cators of the experiment. Summary table6 contains

systematized data of average values of evaluations for

criteria and projects.

Figure 5 contains a graphical representation of the

results obtained. It demonstrates the distribution of

total ratings by all criteria.

The DaVinci project received the highest aver-

age value of expert estimates. Teachers consider it

relevant, realistic and effective for the development

of ICT competencies. According to the survey, the

SkyScrapers project turned out to be relevant and

promising. The Bridges project also received a high

rating for the development of ICT competencies. De-

spite the overall low score, experts consider the “No-

table Women” project to be promising. This may be

due to the fact that most of the teachers surveyed were

women.

In general, STEM augmented reality projects are

an effective tool for organizing students’ search ac-

tivities. The objectives of such projects demonstrate

the integration between mathematics, computer sci-

ence, engineering, history, art. The STEM concept is

a source of interdisciplinary innovation in school ed-

ucation. As our experiment showed, the organization

of STEM projects with augmented reality aroused the

interest of computer science teachers. They found the

projects relevant and useful for the development of

ICT competencies. We can predict that the use of aug-

mented reality technologies will also interest students

and will have a positive impact on their choice of fu-

ture profession.

We recommend scientists, lecturers, teachers to

create more STEM projects. This should help to in-

volve students in interdisciplinary learning to gain

real practical experience, the development of lifelong

learning skills.

5 CONCLUSIONS

Therefore, innovative ICTs should be used in com-

puter science lessons, as they are necessary and cru-

cial for living in the modern world. Augmented re-

ality is one of the most up-to-date teaching content

visualization technologies. Currently, the use of AR

in education has been a success. In our opinion, the

introduction of this technology will increase the mo-

tivation to learn, increase the level of mastering the

material. This is also possible due to the variety, inter-

activity of visual presentation of educational objects,

migration of part of students’ research work into the

virtual environment.

Our analysis of publications on the problem of re-

search has shown that the experience of using aug-

mented reality applications is mostly fragmentarily

described in scientiﬁc articles and blogs of enthusi-

asts. Appropriate implementation of AR means in the

practice of educational institutions will be done step

by step.

It is clear that successful implementation of this

technology requires special attention to the system of

teacher training and retraining, curriculum develop-

ment and next-generation textbooks. However, such

fragmented use of augmented reality is already facil-

itating the process of its implementation. Our expe-

rience has shown that the developed training courses

are in demand in advanced training courses. They are

of interest to teachers. The results of this study show

that IT teachers have access to computers and mobile

devices and have a high level of interest in augmented

reality technology.

The study found difﬁculties in implementing AR

such as:

• increasing the time of teacher’s preparation for

augmented reality classes;

• AR tools are usually application-speciﬁc, so

learning about different topics requires installing

and sometimes integrating multiple applications;

• sometimes AR is perceived by students and teach-

ers as an entertainment game, not as a learning

environment;

• development of high-quality AR applications

clearly requires the work of professional program-

mers.

This study has several limitations. The question-

naire was based on self-assessment. Therefore, the

AET 2020 - Symposium on Advances in Educational Technology

Table 5: Generalized data for calculating the concordance coefﬁcient W for projects 1-5.

Kendall chi-squared P-value W

DaVinci 153.1 < 2.2 × 10

−16

0.80

Universe 80.94 < 2.2 × 10

−16

0.42

Bridges 70.72 < 2.2 × 10

−16

0.37

SkyScrapers 111.74 < 2.2 × 10

−16

0.58

Notable Women 132.19 < 2.2 × 10

−16

0.69

Table 6: Final table of expert evaluation.

DaVinci Universe Bridges SkyScrapers Women

Cr1 3.27 3.59 2.22 4.53 1.39

Cr2 4.58 3.70 2.92 1.91 1.89

Cr3 1.61 1.86 3.17 3.94 4.42

Cr4 4.27 2.27 4.11 2.63 1.73

ProjectSum 13.73 11.42 12.42 13.01 9.43

Figure 5: Diagram of distribution of expert assessments according to criteria 1-4.

level of ICT competence and teacher readiness was

not sufﬁciently objectively determined. Also, the de-

gree of use of AR applications has not been measured

in practice. In addition, the number of teachers was

limited. As a consequence, it is likely that teachers

with advanced digital competence participated in the

experiment. Expert assessments can be only one of

the methods for determining the complexity of the

STEM project, and therefore have a recommendatory

nature.

There is a need for future research on technical

and methodological issues of using augmented reality

technologies in school STEM projects. For example,

the development of repositories of educational AR-

applications to support computer science is currently

in demand.

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