225
Indonesian Journal of Science & Technology 9(1) (2024) 225-260

Indonesian Journal of Science & Technology
Journal homepage: http://ejournal.upi.edu/index.php/ijost/

Augmented Reality for Cultivating Computational
Thinking Skills in Mathematics Completed with
Literature Review, Bibliometrics, and Experiments for
Students
Lilis Marina Angraini1,*, Aay Susilawati2, Muchamad Subali Noto3, Reni Wahyuni1, Dedek Andrian1
1

Department of Mathematics Education, Universitas Islam Riau, Indonesia
Department of of Science Education, Universitas Pendidikan Indonesia, Indonesia
3
Department of Mathematics Education, Universitas Swadaya Gunung Djati, Indonesia
*
Correspondence: E-mail: lilismarina@edu.uir.ac.id
2

ABSTRACT
The research problem centered around the need to enhance
students' computational thinking (CT) ability, which is crucial
for their success in the present and future. This study aims to
examine the efficacy of Augmented Reality (AR) in improving
the CT abilities of seventh-grade junior high school students.
The study utilized a quasi-experimental design with a control
group and an experimental group to meet the research aims.
The control group was provided with conventional
mathematical instruction through established teaching
methods, while the experimental group was exposed to
mathematics learning enhanced by AR media. The study
involved 160 students from four junior high schools located
in one of the cities in Indonesia. A five-question CT ability test
was employed as the research instrument. The mean
difference test was used to analyze the data and compare the
performance of the control and experimental groups. The
research findings indicated that the effective application of
AR media significantly enhanced the CT skills of seventhgrade adolescents in middle school. The results aid in
creating new teaching approaches and emphasize the
possibilities of AR technology in math education.
© 2024 Tim Pengembang Jurnal UPI

ARTICLEINFO
Article History:
Submitted/Received 14 Des 2023
First Revised 30 Jan 2024
Accepted 19 Feb 2024
First Available online 21 Feb 2024
Publication Date 01 Apr 2024

____________________
Keyword:
Augmented reality,
Computational thinking,
Junior high school,
Learning media.

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1. INTRODUCTION
Technological advancements in the era of Digital Society 5.0 progress swiftly and have the
potential to enhance human lives. Many reports regarding this development for supporting
society 5.0. have been well-documented (Damayanti et al., 2022; Shaffiyah et al., 2022).
Technology has transformed education from being passive and reactive to participatory and
proactive. Education is crucial in an academic setting and is intended to stimulate students'
attention. Technology can help pupils understand and remember things more easily (Siregar,
2023). The use of technology, especially online educational resources, significantly influences
the field of education. The generation raised with internet access and technological progress
relies significantly on online resources for information and creating a virtual learning
environment. Students find many online instructional resources, including YouTube,
enjoyable and believe they help improve their skills. Although technology provides great help,
it is essential to highlight that the teacher's function as a mentor and companion for students
during the learning process remains crucial.
Moreover, the inherent drive, passion for acquiring knowledge, and self-assurance of
students are crucial elements that impact the effectiveness of learning using technology.
Integrating technology in school enhances learning quality, but requires instructors' active
participation for optimal outcomes (Adijaya, Armawan & Kristiantari, 2023; Yuliani, Kaur &
Jageer Singh, 2023; Pratiwi, Amumpuni, Fikria & Budiastuti, 2023; Hudriati, Yunus & Arham,
2023; Nur, Widodo & Putro, 2023). Regarding the significance of technology in education
today, technology holds an extremely significant educational role in schools and learning
today, particularly in mathematics learning (Valtonen et al., 2020).
Augmented reality (AR) is an innovative technology that combines digital information with
the physical world (Hsiao & Chang, 2016; Bangkerd and Sangsawang, 2021; Albar, 2021;
Castañeda et al., 2018). It incorporates virtual elements like photos, movies, and threedimensional (3D) objects into the physical environment. AR is a technology that enables the
interactive display of three-dimensional virtual objects in the real world (Dutta et al., 2022).
AR media can be applied in schools.
The implementation of AR into the learning process has great profits (Patzer et al., 2014;
Almenara & Vila, 2019): It can enhance students' willingness to learn and their ability to
comprehend material because of the varied and interactive visual representations it offers
(Iatsyshyn et al., 2020). Based on research by Chang & Hwang (2018), it incorporates virtual
elements like photos, movies, and three-dimensional (3D) objects into the physical
environment. AR is a technology that enables the interactive display of three-dimensional
virtual objects in the real world.
AR integrates additional elements into a physical environment to enrich the user's
perception of reality. It necessitates a setting and a suitable camera included in our gadgets
like cellphones, tablets, or PCs. AR contains three main characteristics outlined by Azuma
(1997):
(i) it merges the actual and virtual environments to offer users novel and distinct experiences
related to their actions;
(ii) it enables real-time interactivity, delivering an interactive experience, and
(iii) it is rendered in 3D.
AR should be integrated into all disciplines in schools, particularly those perceived as
challenging by pupils, rather than being limited to certain subjects. Mathematics is one of
those challenging courses. (Dinayusadewi & Agustika, 2020). AR technology in mathematics
education improves information visualization, with marker-based AR being more prevalent
than non-marker-based AR. The majority of AR applications are created using Unity 3D with
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the Vuforia software development kit (SDK) (Ahmad & Junaini, 2020). Unity is a software
application utilized for processing images, visuals, sound, input, and other elements to create
games or similar products like AR applications (Putra & Putra, 2021; Pramuditya et al., 2022).
Unity 3D is a sophisticated and completely integrated development platform that offers prebuilt tools for developing interactive 3D content. Vuforia is an SDK created for cellphones to
help develop AR experiences. The Vuforia AR Extension for Unity is a specialized extension of
the Vuforia SDK made expressly for use with Unity. Vuforia is a software development kit
(SDK) developed by Qualcomm for creating AR apps on iOS and Android mobile devices (Putra
& Putra, 2021). The Vuforia SDK serves as a central connection interface between the virtual
realm and the actual realm (X. Liu et al., 2018).
AR media can enhance students' engagement in learning mathematics and reduce
boredom (Syafril et al., 2021; Nurvitasari, & Sulisworo, 2023). Many have researched and
developed learning media based on AR in mathematics learning, as done by Dinayusadewi &
Agustika (2020), where it may be inferred AR technology can be used as a tool for learning
mathematics on geometric concepts in schools. Dinayusadewi & Agustika (2020) Outlined
challenges faced by teachers while creating AR-enhanced learning materials and methods,
such as difficulties in meeting essential hardware and software needs and having restricted
access to various sources of information, whether they be human, online, or in print. Teachers
have taken steps to address these issues by gradually upgrading laptops, seeking references
in foreign languages, and establishing a learning community.
Computational thinking (CT) is an essential skill needed in the 21st century (Curzon et al.,
2009). CT is a crucial talent for all students. (Vinayakumar et al., 2018; Deng et al., 2020;
Mohamed et al., 2019; Araujo et al., 2019; Y.-C. Liu et al., 2021; Repenning et al., 2016; Li
et al., 2020; Silva et al., 2018; Tofel-grehl & Richardson, 2018; Mitrayana and Nurlaelah,
2023; Valovičová et al., 2020; Voogt et al., 2015; Yang et al., 2020). CT is a demonstrated
skill that involves two main steps: abstracting the problem and automating the answer (Israel
et al., 2015; Park & Green, 2019). CT is a method of thinking that utilizes abstraction,
generalization, decomposition, algorithmic reasoning, and debugging (Kale et al., 2018; Lee
et al., 2023; Angeli et al., 2016). Critical thinking is the systematic process of examining,
evaluating information and evaluating information to solve complex problems using a
structured approach (Anderson, 2016; Barr et al., 2011).
CT skills are crucial for problem-solving and have particular relevance within the realms of
science, engineering, and mathematics (Taslibeyasz et al., 2020). CT has occurred likened to
mathematical reasoning involves beliefs, problem-solving, and justification (Rich et al., 2020;
Shute et al., 2017). Mathematics activities are closely connected to CT as they emphasize
skills and processes (Nordby et al., 2022; Mohaghegh & Mccauley, 2016). Mathematics
education focuses on three key parts of CT: problem-solving, cognitive processes, and
transposition (Kallia et al., 2021; Urhan, 2022).
Proficiency in mathematical critical thinking is essential since it provides students with
problem-solving skills, logical reasoning, and the capacity to analyze and interpret
mathematical topics. It enables students to approach complex mathematical problems
systematically and develop strategies to find solutions. Additionally, CT is crucial in multiple
disciplines like as mathematics, science, engineering, and computer programming. The
mathematical CT ability of students is low attributed to several factors. These factors can
include a lack of exposure to problem-solving tasks, limited opportunities to engage in critical
thinking activities, inadequate instructional approaches that focus solely on memorization
rather than understanding, and insufficient practice in applying CT strategies. Low
mathematical CT ability may manifest as students struggling to analyze problems, find
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multiple solution paths, make connections between different mathematical concepts, and
apply logical reasoning in their problem-solving process.
Current traditional learning methods may not adequately support the development of CT
skills. Traditional instruction often emphasizes rote memorization and procedural knowledge,
rather than promoting conceptual understanding and problem-solving strategies. As a result,
students may struggle to transfer their mathematical knowledge to real-life situations and
encounter difficulties in applying CT skills. Geometry content was chosen for this research
because it offers opportunities to develop and apply CT skills. Geometry involves spatial
reasoning, visualizing objects and relationships, and using logical reasoning to solve geometric
problems. These activities align well with the cognitive processes related to CT, like pattern
recognition, abstraction, and deconstruction, and algorithmic reasoning.
AR media was selected as a tool for enhancing mathematics learning because it provides
unique advantages. AR integrates digital information into reality, enabling students to engage
with virtual objects and visualize mathematical concepts more engagingly and interactively.
AR media can present three-dimensional representations, interactive visualizations, and
simulations, which can facilitate students' understanding, exploration, and problem-solving
in geometry. Compared to other media, AR provides a more engaging and participatory
educational experience, enabling students to connect abstract mathematical ideas with
practical real-world uses. While other media, such as textbooks or digital simulations, can also
support mathematics learning, utilizing AR media adds a layer of interactivity and realism. By
overlaying virtual objects in the real world, AR enhances students' spatial understanding,
visualization, and engagement. This makes AR a promising tool for promoting CT skills, as it
provides a unique and dynamic learning experience that enhances pupils' problem-solving
skills, critical thinking, and conceptual understanding in mathematics.
This research aims to examine how using AR media can improve the critical thinking (CT)
skills of junior high school pupils. The research data gathered pertains to the student's
mathematical CT skills, specifically in the context of geometry. We also added bibliometric
analysis since it can describe the current research situation. Detailed information regarding
previous research in bibliometrics is demonstrated in Table 1.
Table 1. Previous studies on bibliometric.
Author
Title
Shidiq et al., The
use
of
simple
(2021)
spectrophotometer in STEM
education:
A
bibliometric
analysis
Nordin,
Correlation between process
(2022)
engineering and special needs
from
bibliometric
analysis
perspectives.
Bilad,
Bibliometric
analysis
for
(2022)
understanding the correlation
between chemistry and special
needs
education
using
VOSviewer indexed by Google.
Riandi et al., Implementation
of
(2022)
Biotechnology in Education
towards
Green
Chemistry
Teaching: A Bibliometrics Study
and Research Trends

Result
The study, which made use of the VOSviewer
program, found that modified spectrophotometers
are frequently used in chemistry and STEM teaching,
providing prospects for future research.
VOSviewer, a process engineering tool for mapping
analysis, experienced a decrease in publications on
"process engineering special demands" between
2017 and 2021.
An analysis of articles on chemistry and special
education using VOSviewer and Publish or Perish
showed a decline in publications in 2017 and a rise in
2021.
With journals being the most prevalent source, the
study bibliometric analysis of research trends on
biotechnology in education revealed four study
concept potentials, underscoring the significance of
teaching green chemistry in schools.

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Table 1 (Continue). Previous studies on bibliometric.
Author
Nordin,
(2022)

Title
A bibliometric analysis of
computational mapping on
publishing teaching science
engineering using VOSviewer
application and correlation.
Wirzal
& What is the correlation between
Putra,
chemical
engineering
and
(2022)
special needs education from
the perspective of bibliometric
analysis
using
VOSviewer
indexed by Google Scholar?
Nandiyanto A bibliometric analysis of
&
Al materials research in Indonesian
Husaeni,
journal using VOSviewer
(2021)
Maryanti et
al., (2022)

Sustainable development goals
(SDGs) in science education:
Definition, literature review, and
bibliometric analysis.
Nandiyanto A bibliometric analysis of
&
Al chemical engineering research
Husaeni,
using VOSviewer and its
(2021)
correlation
with
covid-19
pandemic condition.
Al Husaeni, Computational
bibliometric
(2022)
analysis of research on science
and Islam with VOSviewer:
Scopus database in 2012 to
2022.
Al Husaeni,
(2022)

Bibliometric analysis of briquette
research trends during the Covid19 pandemic.

Ragadhita & Computational
bibliometric
Nandiyanto, analysis on publication of
(2022)
techno-economic education.

Al Husaeni
&
Nandiyanto,
(2022)
Febriandi et
al., (2023)

Bibliometric
computational
mapping analysis of publications
on mechanical engineering
education using VOSviewer
Research on algebraic thinking
in elementary school is reduced:
a bibliometric analysis

Supriyadi et
al., (2023)

Global trend of ethnoscience
research: a bibliometric analysis
using Scopus database

Result
A study that examined teaching, science, and
engineering research using the VOSviewer and
Perish applications found a significant drop because
of pandemic conditions.
Utilizing the VOSviewer software, a research study
on the relationship between chemical engineering
and special needs examined 800 pertinent papers
between 2018 and 2022.

A bibliometric assessment of research on Indonesian
materials was conducted using VOSviewer, and the
results showed that "acid" received the most
attention from 2016 to 2021, with 43 publications
and 8 foreign linkages.
The bibliometric analysis, a vital instrument in
science education, offers a thorough grasp of the
subject, underscoring the important role it plays in
facilitating research on the SDGs.
Despite a decline in research since 2019, chemical
engineering uses VOSviewer software for
bibliometric analysis, which provides useful
information on research trends and themes.
In a study on science and Islamic research,
VOSviewer was used for bibliometric analysis, which
revealed a drop in research, particularly in Indonesia
and Malaysia. This study also provided excellent
reference materials for future research.
A review of 973 pertinent papers on briquettes was
analyzed using VOSviewer, bibliometric analysis, and
data mapping; the results showed a decline in
research over the previous three years as a result of
the COVID-19 pandemic.
A study on science and Islamic research that
employed data from the Scopus database from 2012
to 2022 and VOSviewer for bibliometric analysis
found a reduction in research, mainly in Indonesia
and Malaysia.
A study that used VOSviewer to chart the
development of nano propolis research over the last
ten years found a spike in research on nanoparticles
and propolis.
VOSviewer, a bibliometric approach, was used to
analyze 996 articles from 2012–2021, revealing a
decline in research on algebraic thinking skills and
providing valuable insights for future research.
An analysis of the Scopus database showed that
ethnoscience research has significantly increased
over the past 50 years.

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Table 1 (Continue). Previous studies on bibliometric.
Author
Supriyadi
et
al.,
(2023)

Nandiyant
o et al.,
(2023)

Suherman
et
al.,
(2023)

Al Husaeni
et
al.,
(2022)

Fauziah et
al.,
(2022)

Nandiyant
o et al.,
(2023)

Ruzmetov
&
Ibragimov,
(2023)

Title
Result
Didactical design research: a By identifying research topics, authors, sources,
bibliometric analysis
countries, affiliations, and most-cited papers in DDR
publications, Scopus offers bibliometric analysis. This
analysis showed a large growth in DDR initiatives from
2015 to 2022.
Particulate matter emission This study discusses the growth trend of scientific
from combustion and non- publications on the topic of particulate matter
combustion automotive engine identified based on several categories such as the
process:
review
and most cited, publisher, author, country, and affiliation.
computational
bibliometric
analysis on its source, sizes, and
health and lung impact
How to Improve Student This study intends to clarify research on the
Understanding in Learning advancement of language education to improve
Science by Regulating Strategy students' understanding of science education. This
in
Language
Education? study analyzes the definition of these methods,
Definition, Factors for Enhancing identifies components that improve students'
Students Comprehension, and understanding, and does a computational bibliometric
Computational
Bibliometric review analysis.
Review Analysis
How Language and Technology The project aims to investigate progress in language
Can Improve Student Learning and technology research to improve the efficiency of
Quality
in
Engineering? teaching and learning in engineering. An analysis of
Definition, Factors for Enhancing factors impacting the teaching and learning process is
Students Comprehension, and conducted using a bibliometric study utilizing the
Computational
Bibliometric keywords "Language" and "Engineering Learning" on
Analysis
Google Scholar from 2020 to 2022.
Strategies
in
Language This study aims to elucidate the progress of language
Education to Improve Science research in scientific education to enhance students'
Student Understanding during comprehension during laboratory practicums. This
Practicum in Laboratory: Review study investigates the characteristics that enhance
and Computational Bibliometric student comprehension and does a bibliometric
Analysis
analysis focusing on the terms "language",
"practicum", "laboratory", and "science" between
2015 and 2021.
Bibliometric data analysis of This work aims to thoroughly and methodically
research
on
resin-based examine bibliometric data using VOSViewer in a stepbrakepads from 2012 to 2021 by-step manner. Analyzed 88 documents from 2017using VOSviewer mapping 2021 on predetermined subjects based on the number
analysis computations
of publications collected.
Past, current and future trends Interest in salicylic acid and its derivatives has
of salicylic acid and its markedly increased over the last two decades, leading
derivatives: A bibliometric to a surge in academic research on this topic. Many
review of papers from the scientometric investigations have concentrated solely
Scopus database published from on a particular characteristic of the subject
2000 to 2021
substances. No discussions are held regarding the
origin and future potential of SA and its related
compounds. This study conducts a bibliometric
analysis of 2010 publications published between 2000
and 2021 that were included in Scopus in the subdiscipline of salicylic and salicylates.

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2. LITERATURE REVIEW
2.1. Augmented Reality
AR is a technology that combines the physical environment with the virtual world by
displaying two or three-dimensional virtual things, creating a seamless integration with
reality. Utilizing learning media through AR can stimulate critical thinking among learners,
encouraging problem-solving and aiding in visualizing abstract concepts for comprehension
and model structuring (Romalee et al., 2023; Urlings et al., 2022; Mahrou et al., 2021). AR
employs digital elements such as images, text, 3D models, or computer-generated videos to
deliver additional information or virtual objects. Integration of AR takes place in the realworld environment, encompassing classrooms, books, whiteboards, or other physical objects.
AR establishes a bridge between the tangible world and digital elements. Devices like
smartphones, tablets, or AR glasses serve to project digital elements into the real world. Users
observe their physical surroundings through the device screen, enriched with digital overlays.
An integral aspect of AR is the active interaction users have with digital elements, involving
touch screens, physical gestures, or voice commands for manipulation or accessing extra
information (Zafar & Zachar, 2020; Mladenovic et al., 2022).
The educational concept of AR aims to enrich students' understanding, engagement, and
interaction with learning materials. Digital elements presented can include illustrations,
animations, or supplementary information supporting the learning content. By delivering
additional content visually and interactively, AR enhances students' learning experiences,
making the material more captivating and easily comprehensible (Lima, Walton & Owen,
2022; Amantini et al., 2020). AR facilitates the presentation of information in a context
relevant to the surrounding environment. For instance, it can showcase a 3D model of human
body organs during a biology lesson. The AR concept is versatile and applicable across various
subjects like mathematics, science, history, and language, introducing a more dynamic
approach to learning. AR provides flexibility in accessing learning material, enabling students
to use AR devices at their convenience. Some AR applications even foster collaboration and
shared learning experiences, supporting team-based learning and social interaction (see
Figure 1) (Sharmin et al., 2022; Jeon, Oh & Son, 2021).
AR empowers students to directly visualize and manipulate 3D shapes. They can explore
the surface and volume of three-dimensional objects and correlate them with the concept of
unit area. AR devices allow students to interactively measure area, placing virtual measuring
tools on a surface as if measuring it right before their eyes. AR can simulate how the unit area
concept is applied in everyday scenarios, such as designing a garden or planning room layouts.
Students can compare areas between different geometric shapes in AR, understanding the
differences in a 3D visual context (Mladenovic et al., 2019; Mladenovic et al., 2020; Llena et
al., 2018). Table 2 shows the applications of AR in various fields.

Figure 1. Applications of AR.
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Table 2. Application of AR in various fields.
Fields
Education

Science and
Technology

Industry and
Engineering

Real Estate and
Interior Design

Gaming and
Entertainment

Commerce and
Marketing

Tourism and
Mapping

Health

Application of AR
AR can provide a simulated laboratory environment, enabling students to do
experiments without using actual equipment. This fosters an engaging and secure
learning environment.
Interactive Educational Maps: Utilizing AR in maps or educational materials can
supply supplementary information as students delve into the topography, history, or
culture of specific locations.
Physics Modeling Simulation: Within the realm of science, AR can be employed to
showcase simulations of intricate physical phenomena, such as the laws of motion,
gravity, or wave interference.
Medical Training and Anatomy: In the healthcare domain, AR is harnessed to deliver
interactive 3D anatomy simulations, enabling medical students or healthcare
professionals to gain a deeper understanding of the body's structure.
Assembly and Machine Maintenance: In manufacturing environments, AR can aid
workers in assembling or maintaining machinery by offering step-by-step guidance
on physical objects.
Design and Prototyping Simulation: Design and engineering teams can leverage AR
to create and test product prototypes in a virtual setting before moving to physical
production.
Virtual Property Tours: In the real estate sector, AR is employed to provide virtual
property tours, allowing potential buyers to virtually explore rooms.
Virtual Furniture Arrangement: AR enables users to position virtual furniture in their
space and visualize how the arrangement complements the interior design.
AR Games: AR games, such as Pokémon GO seamlessly Integrate real-world aspects
with virtual gaming features, resulting in a more immersive and interactive gaming
experience.
Concerts and Entertainment Events: Within the entertainment industry, AR can be
integrated to enhance visual effects during concerts or performances, creating
memorable experiences.
Virtual Product Try-On: AR empowers consumers to virtually "try on" products, such
as clothing or accessories, before making online purchases.
Interactive Advertising: Advertising campaigns leverage AR to offer interactive
experiences to consumers, including scanning ad images for additional information
or special offers.
Virtual Tour Guides: Within the tourism sector, AR serves as a virtual tour guide at
historical or tourist locations, providing additional information as tourists explore the
site.
Interactive Navigational Maps: AR map applications can assist users in navigating
new cities or environments by displaying information about surrounding objects.
Virtual Surgical Simulations: Doctors and surgeons can utilize AR for virtual surgical
simulations as a preparation step before actual procedures, contributing to
improved accuracy and skills.
Medical Training Enhancement: AR is incorporated into medical training to provide
supplementary information during medical procedures and to train clinical skills like
blood sampling or intravenous placement.

2.2. Computational Thinking
CT in the realm of mathematics and science education denotes an individual's capacity to
amalgamate components of problem-solving, logic, and algorithms, akin to the cognitive
processes of computers. It encompasses a comprehension of how information can be
structured, processed, and harnessed to formulate solutions or decisions. Regarding the
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study of mathematics and science, CT may encompass the proficiency to devise a methodical
approach to resolving mathematical or scientific quandaries. This involves delineating the
problem, arranging information coherently, and formulating systematic steps to attain
solutions (Acevedo-Borrega et al., 2022; Wang, Shen & Chao, 2022; Weintrop et al., 2016).
The relationship in diagram form (Huang et al., 2023) is presented in Figure 2.
CT encompasses the following aspects: (1) decomposition, i.e., the capacity to divide
(complicated) data, breaking down processes, problems, or tasks into smaller components or
manageable activities. Pattern recognition refers to the ability to identify similarities or
distinctions in patterns, trends, and consistencies within data which will subsequently be
employed in generating predictions and presenting data; (3) abstraction, i.e., generalizing and
recognizing the universal principles that produce patterns, trends, and regularities; and (4)
algorithm, which involves providing step-by-step troubleshooting instructions for others to
use in addressing the same issue (Harimurti et al., 2019; Huang et al., 2023). Furthermore,
these four aspects are presented in Figure 3.

Figure 2. The relationship diagram of CT.

Figure 3. The thought processes of CT.
In geometry education, CT plays a pivotal role by aiding students in honing critical thinking
skills, surmounting challenges in comprehending geometric principles, and augmenting their
grasp of the nexus between geometry and science. CT empowers students to visualize and
comprehend geometric concepts more interactively and visually, encompassing alterations in
object shapes and their interrelationships (Presser et al., 2023; Shin et al., 2022; McCormick
& Hall, 2021). Within the domain of geometry education, CT equips students to engage in
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critical deliberation and grapple with intricate geometric predicaments. Furthermore, CT in
geometry education facilitates students in discerning the interplay between geometry and
science, particularly in the dynamics of physical systems involving alterations in form and
structure. The process of learning geometry involves crafting algorithms and scrutinizing
computational data, which are fundamental for nurturing proficiencies in the realms of
technology and science.
2.3. Augmented Reality and Computational Thinking Research Trends
Analyzing research data on AR and Computer Tomography (CT) from 2013 to 2023 shows
clear patterns and trends (Figure 4). Comprehensive instructions for utilizing bibliometric data
are available in another location (Al Husaeni and Nandiyanto, 2022; Azizah et al., 2021). The
following is an overview and analysis of the data (97 documents in Scopus): In 2013, there
was one publication, indicating early interest or introduction to AR and CT in research. For
the years 2014-2015, there were no publications recorded, possibly due to various factors
such as a lack of attention or focus on the topic during that period.

Figure 4. AR and CT research trends.
Figure 4 shows that the emergence of one publication in 2016 signaled renewed interest,
potentially contributing to the reinitiation of research in the field. In 2017, the number of
publications increased to five, reflecting a growing interest and recognition of the significance
of AR and Computer Tomography (CT) in the study literature. The growth trend continued in
2018, with seven publications, underscoring the increasing attention to this topic as a crucial
research area. The year 2019 saw a significant spike with 19 publications, indicating
substantial exploration and heightened interest in the field of AR and CT. Although there was
a decrease in 2020 compared to the previous year, with 14 publications, the number
remained high, suggesting sustained interest and research in this field. In 2021, there were
13 publications, maintaining relative stability and indicating the ongoing relevance of AR and
CT as research focuses. Despite a slight decrease in 2022, with 12 publications, the number
remained considerable, signifying sustained interest among researchers. The peak was
observed in 2023 with 25 publications, highlighting the zenith of interest and research
activities in this field. The data indicates a substantial increase in research interest related to
AR and CT over the years. The surge in publications in 2019 may reflect advancements in
technology and an improved understanding of the potential applications of AR and CT.
Despite fluctuations in some years, the overall trend suggests a sustained rise in interest and
focus on this topic. The peak in 2023 may signify the ongoing growth of literature and the
exploration of new concepts in AR and CT.
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Figure 5 shows the description and analysis of AR and CT research data based on the
subject area. Chemical Engineering = 1 publication: Having only one publication, the field of
Chemical Engineering indicates a limited interest in implementing AR and CT in this domain.
Arts and Humanities = 1 publication: The solitary publication in Arts and Humanities implies
that the integration of AR and CT in this field is still constrained and may not have garnered
primary attention. Materials Science = 2 publications: Two publications in Materials Science
suggest a slightly increased interest but still depict a relatively restricted application of AR and
CT in this subject. Decision Sciences = 4 publications: The four publications in Decision
Sciences signify an interest in applying AR and CT to decision-making processes. Psychology =
5 publications: With five publications in Psychology, there is an endeavor to comprehend the
impact of AR and CT on psychological aspects. Physics and Astronomy = 6 publications: Having
six publications, Physics and Astronomy display significant interest in deploying this
technology in the realms of physics and astronomy. Mathematics = 24 publications: The
substantial number of publications in Mathematics underscores the profound impact of AR
and CT in the field of mathematics. Engineering = 24 publications: Matching the number of
publications in Mathematics, Engineering suggests that AR and CT are extensively utilized in
the engineering domain. Social Sciences = 38 publications: With 38 publications, Social
Sciences emphasize the critical role played by AR and CT in the context of social sciences.
Computer Sciences = 77 publications: The abundance of publications in Computer Sciences
highlights the dominance of AR and CT in the realms of computer science and information
technology.

Figure 5. AR and CT research trends by subject area.
The dominance of Computer Sciences in terms of the number of publications indicates the
substantial influence of AR and CT on the field of information technology. Mathematics and
Engineering also exhibit significant contributions, reflecting the successful application of this
technology in these fields. Certain areas, such as Chemical Engineering and Arts and
Humanities, exhibit limited contributions, suggesting that the acceptance or adoption of AR
and CT may not be widespread in those domains.
Figure 6 shows that the keywords "augmented reality" and "computational thinking"
highlight the central theme of this research. The largest circle emphasizes that both these
concepts are pivotal to the research article. This underscores that the central topic of
discussion revolves around the application of AR within the realm of CT. The inclusion of the
keyword "student" specifically underscores a focus on students' learning experiences and
their responses to the integration of AR to enhance CT skills. This indicates that the research
doesn't solely concentrate on technical aspects but also delves into its impact on student
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learning. The incorporation of these primary keywords in the largest circle underscores a
distinct and unified emphasis on AR and CT. The presence of the keyword "student" signifies
a comprehensive approach, taking into account various facets of students' learning
experiences. This mirrors the research's recognition of technology's influence on student
understanding and responses, encompassing not only technical dimensions but also
educational and learning perspectives.

Figure 6. AR and CT research trends by VOSviewer.
2.4. The Relation Between Augmented Reality, Geometry and Science
Utilizing AR in geometry education can assist students in visualizing abstract concepts and
gaining a deeper understanding. AR allows students to grasp geometric concepts, such as
changes in object shapes, from diverse perspectives, enhancing their understanding of spatial
concepts and spatial perception. AR can visualize geometry concepts, including points, lines,
planes, and their relationships, aiding students in comprehending the structure and
connections between geometric concepts. AR implemented on Android devices can serve as
a three-dimensional learning tool for mathematics, enabling students to observe and
understand geometric objects in three dimensions (Zhang et al., 2014). The integration of AR
into learning media development, merging the real and virtual worlds, helps students grasp
geometry concepts more visually and interactively. Consequently, AR enhances students'
visual and interactive comprehension of geometry, fostering increased interest and
engagement in learning (Peng & Ou, 2014; González, 2015; Gargrish, Mantri & Kaur 2020).

Figure 7. Relation between AR, geometry, and science.
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The close connection between geometry and science is evident, with geometry being a
branch of mathematics studying relationships within space, allowing an understanding of
space through its fundamental characteristics. Modern geometry has strong links to physics,
such as the relationship between pseudo-Riemannian geometry and physics. Geometry finds
applications in various scientific fields, including mechanics, astronomy, crystallography,
geodesy, aerodynamics, and navigation. In education, geometry serves as a tool to visualize
scientific concepts like molecular structures and planets, and it is employed in developing
science teaching materials using simple geometric media for middle school students. Thus,
geometry and science are closely intertwined, with geometry acting as a tool to visualize
scientific concepts and being utilized across diverse scientific fields (Liou et al., 2016; Yeh &
Liao, 2014).
Geometry's application in physics, especially in mathematical physics, is multifaceted.
Geometry aids in solving problems related to area, length, and volume measurement, crucial
for depicting and understanding the behavior of physical systems. It is employed to measure
physical bodies and discern the dominating properties when representing surrounding
objects. Hyperbolic geometry, utilizing Euclidean geometry's theorems and axioms but
substituting Euclidean parallelism postulates with hyperbolic parallelism postulates, finds
applications in theoretical physics, notably in general relativity. Differential geometry applies
calculus and linear algebra methods to analyze physics-related issues, such as the behavior of
physical systems, econometrics, and bioinformatics. Algebraic geometry involves
constructing mathematical objects and examining their relationships with known structures,
with applications in physics, particularly in understanding the behavior of physical systems
involving changes in shape and structure. Thus, geometry is an essential tool in physics for
comprehending and predicting the behavior of physical systems and developing theories and
methods in theoretical physics (Loizeau et al., 2011).
2.5. Benefits of Geometry in Science
The utilization of geometric techniques can be employed for reducing dimensionality with
shape supervision when analyzing physical features through geometric moments. Geometry
facilitates the extraction of visual information associated with the shape and structure of
objects (Kumar & Taber, 2020; Thiagarajan & Shapiro, 2018). In the scientific realm, this may
involve recognizing and scrutinizing geometric patterns linked to physical phenomena.
Dimensionality reduction serves as a method to simplify data while retaining crucial
information. In this context, the incorporation of geometry aids in condensing the dimensions
of intricate physical data into a more straightforward and easily understandable
representation. Geometry allows for the identification of pertinent physical features within a
system or object. The analysis of physical features might encompass the measurement and
modeling of geometric properties that reflect specific physical characteristics. Geometric
moments can offer profound insights into the distribution of mass or other physical properties
within an object. This comprehension can serve as a foundation for subsequent analyses
related to dynamics, kinematics, or other physical properties. Through the lens of geometry,
a visual understanding of intricate physical phenomena can be amplified. Visualizing
geometric shapes, distributions, and interactions supports scientists and researchers in
envisioning and detailing complex physical processes (Jin, Xie & Xiao, 2019; Atrevi et al.,
2017). Figure 8 show the benefits of geometry in science.
The application of geometry in dimensionality reduction can bolster the efficient
optimization and modeling of physical data. This aids in crafting simpler yet still informationrich mathematical models for scientific analysis. Geometry emerges as an essential tool for
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delineating, analyzing, and comprehending the shapes and physical features involving
distributions in a given space (Taber et al., 2018; Khan et al., 2022; Khan et al., 2022).
Geometry aids in comprehending the concepts of kinetics and dynamics. Applying
geometry concerning the motion and positioning of objects facilitates the construction of
detailed models depicting how these objects interact and move within space. The application
of geometry aids in visualizing physics concepts, assisting in planning and analyzing the
outcomes of physics experiments, thereby bringing a systematic approach to data collection
and interpretation (Marshall, 2013).

Figure 8. Benefits of geometry in science.
3. METHODS
3.1. Research Design
The study utilized a quasi-experimental methodology to examine the effectiveness of
implementing learning using AR media compared to traditional teaching methods using
PowerPoint media in enhancing students' CT abilities in the context of learning triangles and
quadrilaterals. The study aimed to determine the success rate of applying AR media in
enhancing CT skills. The research flow in Figure 9 describes the initial steps before researching
until conclusions are obtained.
Figure 9 shows that the research process comprises the subsequent stages: Problem
Identification, Problem Formulation, and Literature Review: In the initial stage, researchers
pinpoint and articulate the research issue. They craft research inquiries and explicit
hypotheses, followed by an exhaustive review of literature pertinent to the research domain.
Preparation of Research Instruments and Validation: This phase involves devising research
tools. These tools then undergo a validation process to guarantee their dependability and
validity in gauging the intended variables. Sample Selection: Researchers opt for a
representative sample for the study. The selection procedure may encompass particular
criteria to ensure that the chosen sample is apt for addressing the research questions.
Research Implementation: This stage involves executing the prepared research plan. The
formulated methodology and protocols are put into action, and experiments or interventions
are carried out based on the designs of the experimental and control groups. Pretest-Posttest
conducted on experimental and control classes with participants in both groups undergoing
pretests to set up a baseline. Following the intervention or experiment, posttests are
administered to gauge the alterations or effects stemming from the applied treatment or
intervention.
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Figure 9. Research procedure.
Data Collection: Throughout and after the execution of the research, data is systematically
collected. This may encompass diverse methods such as documentation, experiments, and
interviews. Data Processing and Analysis, and Conclusions: The collected data undergoes
processing and analysis using parametric statistical methods. The outcomes are elucidated,
and conclusions are drawn based on the findings. This phase also encompasses a discourse
on the ramifications of the results, the constraints of the study, and suggestions for future
research. In summary, these stages furnish a methodical and systematic approach to
executing research, ensuring lucidity in defining the problem, methodological precision, and
the generation of meaningful conclusions.
3.2. Data collection and Participants
The research involved a total of 160 seventh-grade students randomly selected from four
junior high schools in the Marpoyan Damai sub-district during the academic year 2022-2023.
The students were split into two groups: one received AR-based learning, while the other
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received conventional Power Point-based instruction. The selection of students and schools
was done randomly to ensure a representative sample. Before the treatment, All students
participated in a pre-test to evaluate their first CT skills. This enabled us to set a standard for
comparison. After the treatment, both groups took a post-test to assess their final cognitive
performance following the therapies.
The subjects in the study were 12-13 years old, taught by the same teachers, and provided
with the same learning materials and practice questions. They had equal learning
opportunities from the teacher. The experimental group received instruction using AR media,
while the comparison group used PowerPoint media. Both interventions aimed to enhance
students' CT skills. The study consisted of six sessions, with each session lasting 2 x 45 minutes,
including the pretest and posttest. The CT ability test was utilized instrument for data
collection. The test was validated by experts and lecturers to ensure its validity and reliability
in measuring CT skills. The validation process involved reviewing the test items for relevance,
clarity, and alignment with the intended learning outcomes. Table 3 shows
questions/problems included in the instrument used to measure students' CT abilities.
Overall, the study used a quasi-experimental design with pre-test and post-test
measurements. The devices utilized were the CT ability test, which was validated by
specialists, to evaluate pupils' talents. The research process included carrying out
interventions throughout six sessions and assessing the data using t-test values to assess the
impact of AR media on improving CT skills. Comprehensive instructions for utilizing the t-test
are provided at another location (Afifah et al., 2022; Fiandini et al., 2024).
Table 3. Description of the problems.
No.
1

Problems

Question: ABCD and EFGH are squares. Point
D is the center of the EFGH square. The area
of the shaded region is…

2

Take a look at the rectangles KLMN and
PQRS. If the area of the shaded region is
40 cm2, determine the area of the
unshaded area.

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3.3. Data Analysis
Data processing was performed using the post-test scores and t-test results. The
researchers examined the data to assess the influence of the AR intervention on students' CT
skills, in comparison to traditional PowerPoint-based teaching. A t-test was utilized to
evaluate the statistical significance of the disparities in the post-test results between the two
groups.
4. RESULTS AND DISCUSSION
This study intends to determine the efficacy of utilizing AR media to improve the CT skills
of seventh-grade students, especially on flat shapes (triangles and quadrilaterals). Before this
research was carried out, we gave pre-test questions to 160 students to find out their initial
abilities concerning triangles and quadrilaterals (see Table 3).
Table 3 describes the statistical parameters of two student groups, the experimental and
the control groups before any interventions or treatments are applied. There were 80 pupils
in each group. The average pretest score for the experimental group was 21.67, while for the
control group it was 20.26. The average pretest scores reflect the students' baseline level of
understanding before receiving any treatment. Standard deviation measures the dispersion
of data points from the mean. The experimental group had a standard deviation of 6.45,
whereas the control group had a standard deviation of 6.04. Increased standard deviation
indicates more variability in the data. Both the experimental and control groups reached a
maximum score of 35.
The information provides an initial insight into the students' characteristics before the
research began, forming a basis for assessing the changes or impacts caused by a therapy or
intervention during the study. Table 3 Indicates that there was no significant difference
between the students who used AR media for studying (experimental group) and those who
used conventional methods (control group). The minimum score in the experimental group
was 15, surpassing the score in the control class of 10. Statistical tests were conducted to
verify that both groups originated from regularly distributed populations, assessing normality,
homogeneity, and t-test outcomes.
Table 3. Pre-test data.
Descriptive Statistics
N
Means
Sd
Max
Min

Control
80
20.26
6.04
35
10

Experiment (AR)
80
21.67
6.45
35
15

Table 4 shows the results of normality and homogeneity tests for two groups: the
experimental class and the control class. The experimental class's normality test shows a
significance value of 0.25, whereas the control class's normality test shows a significance
value of 0.28. The findings indicate that the data distribution in both groups is not remarkable
and does not deviate significantly from a normal distribution. In other words, the data in both
groups can be seen as originating from a population that follows a normal distribution. The
homogeneity test between the experimental and control classes has a significance value of
0.33. A significance value of 0.33 suggests that the difference in variances between the
experimental and control classes is not statistically significant. Put simply, it can be assumed
that the variations in both groups are similar or homogeneous.
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Table 4 The significance values of the two groups were greater than 5%, suggesting that
the populations from which the groups were sampled had a normal distribution. A
homogeneity test was performed, and the significance level exceeded 5%. This suggests that
the two groups were similar. The average similarity between the two groups was assessed.
The t-test yielded a significance value of 0.23, which is greater than 5%, suggesting that there
was no significant difference in the averages of the two groups. This corroborates the
previously mentioned descriptive data, indicating that there was no notable disparity in the
early capabilities of the two groups. The researcher assessed the impact of using AR media
on improving students' CT skills by conducting a final test following four consecutive sessions
on triangles and quadrilaterals.
Table 4. Pre-test normality, homogeneity, and t-test results.
Kolmogorov-Smirnov Test
Levene Test T-test
Criteria
Control Experiment (AR)
N
80
80
160
160
H0 accepted
Sig.
0.28
0.25
0.33
0.23

Table 5 depicts the results of the posttest given to two separate groups: the experimental
group and the control group. The mean score of the experimental group is 81.67, while the
control group has an average score of 60.26. The standard deviation of posttest scores is 5.94
in the experimental group and 5.24 in the control group. The experimental group achieved a
maximum score of 100, whereas the control group's best score was 70. In contrast, the
experimental group's lowest score is 62, and the control group's lowest score is 15. The
posttest results show that the experimental group had a higher average score, a smaller
standard deviation, and a wider range of values compared to the control group. This suggests
that the intervention or treatment given to the experimental group positively impacted their
posttest results more than the control group. Table 5 shows that the experimental group
exhibited considerably enhanced CT abilities compared to the control group post-therapy,
despite both groups having identical abilities at the beginning. The highest score in the
experimental group was significantly higher than that of the control group, while the lowest
score in the experimental group was only slightly lower than the highest score in the control
group. Assumption and average difference tests were conducted to ensure the effectiveness
of incorporating AR media in learning.
Table 5. Post-test data.
Descriptive Statistics Control Experiment (AR)
N
80
80
Means
60.26
81.67
Sd
5.24
5.94
Max
70
100
Min
15
62

Table 6 reports the results of normality and homogeneity tests for the experimental group
and the control group. The normality test indicates a significant result of 0.27 for the
experimental group and 0.17 for the control group. The findings indicate that the data
distribution in both classes is not significant or does not significantly vary from a normal
distribution. Put simply, the data in both classes can be considered to come from a population
that follows a normal distribution. The homogeneity test between the experimental and
control classes indicates a statistically significant difference with a reported value of 0.42. A
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significance value of 0.42 indicates that the difference in variances between the experimental
group and the control group is not statistically significant. Therefore, it can be deduced that
the differences in variances across both classes are very similar or homogeneous. Table 6 the
significant values of the two groups were larger than 5%, suggesting that the two groups
originated from populations with a normal distribution. A homogeneity test was run, and the
significance value was more than 5%, suggesting that the two groups were homogeneous.
The average similarity of the two groups was then calculated. The data demonstrates that the
significance value of the t-test was less than 5%, suggesting a significant difference in the
means of the two groups. The use of AR media effectively improved the seventh graders' CT
skills, particularly in the areas of triangles and quadrilaterals.
Table 7 displays samples of students' responses to the CT abilities test. The findings from
responses and interviews highlight the importance of recognizing the interrelatedness
between grasping geometric concepts, CT, and mental representations when solving
mathematical problems. Within mathematical ideas, students demonstrate their
understanding of CT by grasping the mathematical connection among the shaded area,
square, and rectangle. The initial mistake was promptly corrected with precision,
demonstrating pupils' adeptness in applying algebra to solve mathematical difficulties.
Table 6. Post-test normality, homogeneity, and t-test results.
Kolmogorov-Smirnov Test
Levene Test T-test
Criteria
Control Experiment (AR)
N
80
80
160
160
H0 rejected
Sig.
0.17
0.27
0.42
0.00

Table 7. Students’ answers to the CT abilities test.
No.
1.

Students’ Answers

Translate: The area of the shaded region is 16 cm
Data Interview
Below are the outcomes of interviews conducted by researchers (R) with students (S)
regarding student test responses:
R: What information can you find out from the questions above?
S: Based on the above problem, it is known that the length of the side of the square EFGH is 8
cm and the length of the side of the square ABCD is 24 cm. Then you are asked to determine
the area of the shaded region.
R: How do you determine the area of the shaded region?
S: I first determined the area of square EFGH as 64 cm2, and then divided it by 4. The area of
the darkened zone is 16 cm2.
R: Why do you have to divide the area of the EFGH square by 4?
S: I'm trying to imagine that if the EFGH square is rotated a bit then the points of the shaded
area will be exactly 1/4 of the area of the EFGH square.
R: Very good.
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Table 7 (Continue). Students’ answers to the CT abilities test.
No.

2.

Students’ Answers
Description
The responses and interviews with students reveal a strong understanding of geometric
problems and CT. In the initial response, the student adeptly identified key information from
the problem, specifically the side length of square EFGH being 8 cm and the side length of
square ABCD being 24 cm. The objective was to calculate the area of the shaded zone. The
student's method of determining the area of the shaded zone showcases a strong
understanding of geometric fundamentals. By initially calculating the area of square EFGH (64
cm²) and then dividing it by 4, the student successfully arrived at the area of the shaded region
as 16 cm². When asked about the rationale for dividing the area of square EFGH by 4, the
student provided a clear explanation. Visualizing the potential rotation of square EFGH, the
student correctly deduced that the points of the shaded area would precisely cover 1/4 of the
total area of square EFGH. The student's explanation reflects well-integrated CT, where the
student endeavors to visualize and model the solution visually. The concept of rotating square
EFGH to comprehend the area of the shaded region exemplifies CT, as the student utilizes
mental representations to simplify geometric problems. Commendation from the researcher
indicates recognition for the student's thoughtful and accurate solution, reinforcing the
understanding of concepts and their application in the realm of computational geometry.
Students’ Answer:

Translate: The area of the unshaded region is 216 cm
Data interview:
The following are the results of interviews between researchers (R) and students (S) regarding
student test answers:
R: What information can you find out from the questions above?
S: The square PQRS has a side length of 8 cm, while the rectangle KLMN has a side length of
16 cm and a width of 12 cm. Next, they are required to calculate the area of the zone that is
not shaded.
R: How can the area of the unshaded zone be calculated?
S: I first determined the area of square PQRS as 64 cm2, and then computed the area of
rectangle KLMN as 192 cm2. The overall area is calculated as 192 + 64, which is 256.
Subtracting 40 from 256 gives a final area of 216 cm2.
Are you confident in the accuracy of your response?
S: I am confident that my answer is accurate.
R: Is the shaded area a subset of the square's area, the rectangle's area, or both?S: The area
of the shaded region is both the area of the square and the area of the rectangle
R: Then are you sure your answer is correct?
S: I think I was wrong, I should have subtracted 256 - 40 - 40 = 176, so the area of the unshaded
region is 176 cm2
R: Very good.
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Table 7 (Continue). Students’ answers to the CT abilities test.
No.

Students’ Answers
Description:
The outcomes of responses and interviews elucidate the cognitive steps taken by students in
solving mathematical problems by leveraging mathematical concepts and CT. Initially, students
adeptly identified key information from the problem, such as the side length of square PQRS being
8 cm and the length and width of rectangle KLMN being 16 cm and 12 cm, respectively. They were
assigned the duty of calculating the area of the zone that was not shaded. Subsequently, the
students accurately calculated the area of square PQRS and rectangle KLMN. However, in the
subsequent step, students made an error in subtracting the total area. This reflects the students'
comprehension of mathematical concepts, specifically the use of algebra to resolve mathematical
problems. When questioned about the certainty of their answer, students were initially confident,
but upon further inquiry regarding the relationship between the shaded area, square, and
rectangle, students acknowledged their mistake. This indicates students' ability to reflect and
reassess their answers, highlighting facets of CT where students employ evaluative skills to gauge
the accuracy of their solutions. The researcher's questions on the relationship between the
darkened area and the square and rectangle helped pupils strengthen their comprehension.
Consequently, students accurately rectified their answers by performing the appropriate
subtraction.

The AR media utilized in this study includes several menus, namely, a) the Introductory
menu, b) the Competency menu, c) the Material menu, d) the Evaluation menu, and e) the
Profile menu. The media design, along with a manual on how to operate it, was available for
the students’ access in the form of a file. The content on the material menu was to be
delivered in four meetings. In each meeting, the students were given example questions in
the order from the easiest to the most difficult. Following the example questions, the
students were also given practice and evaluation questions in the same order. This was done
to form students' CT patterns so that they became accustomed to solving problems from
simpler to more complex problems.
The AR media displayed, first, the packaging of the material and, later, example questions,
practice questions, and evaluation questions to the teacher who operated the media to
achieve the CT indicators expressed by Harimurti et al. (2019): (1) decomposition was
successful for almost half of the students in the experimental group, enabling them to analyze
a problem by breaking it down into smaller components to solve it; (2) the students developed
the ability to identify parallels, distinctions, and regularities in the patterns given, through
pattern recognition; (3) abstraction allowed students to recognize the fundamental principles
behind these patterns, trends, and regularities.; and (4) algorithm, in which students created
detailed issue-solving instructions for others to utilize in addressing the same problem.
Ultimately, utilizing AR media to improve the critical thinking skills of middle school pupils
was successful. Figure 10 shows some screenshots of the display of the AR media used in this
study.
Figure 10a demonstrates how the AR application exhibits sample problems related to
triangle materials. These problems are classified as high difficulty, suggesting a more intricate
or advanced level, possibly aimed at addressing deeper learning challenges. Figure 10b
illustrates how the AR application supports practice exercises on quadrilateral materials.
Problems categorized as low difficulty imply that these exercises are designed with a simpler
or fundamental level, suitable for basic concept understanding. Figure 10c showcases a
second sample problem on triangle materials within the AR application. The problems in this
image are designated as high difficulty, signifying a greater level of complexity compared to
the sample problem in image 10a. In summary, these images convey information about the
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range of difficulty levels in problems accessible through the AR application, enabling users to
access sample problems with diverse difficulty levels based on their preferences and
individual understanding levels.

Figure 10. Display of the AR media.
The results of this study support previous studies (Dinayusadewi & Agustika, 2020; Liu,
Sohn & Park, 2018; Liu, Huang & Sung, 2021; Silva et al., 2018; Syafril et al., 2021). AR
technology can be utilized in educational settings, offering numerous advantages. This study
found that incorporating AR media into instruction can improve the CT skills of seventh-grade
junior high school pupils. Learning systems that utilize AR have a beneficial effect on the
development of students' cognitive processes (Chang & Hwang, 2018).
However, several points in this research are worth consideration. First, on several devices
used by the students, the pictures on the AR media moved on their own without the students
pressing the play button. Second, some students perceived the color combination used in the
media as unattractive. Despite these two drawbacks, the students in general opined that the
AR media was interesting and that it brought novelty to mathematics learning at their schools,
helped them recall the formulas for flat shapes and work on the example, practice, and even
evaluation questions, except for a few difficult questions for which they still needed help from
the teacher and discussed with their peers. Other studies corroborate these findings.
Students are very enthusiastic about learning using AR (Volioti et al., 2023). Overall, the
students were interested in the AR media and thought that it was helpful for them in learning
mathematics on triangles and quadrilaterals and enhancing their CT skills.
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During the research process, specific and important findings were presented regarding the
effectiveness of implementing AR media in enhancing the CT skills of seventh graders,
specifically concerning triangles and quadrilaterals. The t-test analysis revealed that the
significance value was less than 5%. This shows a statistically significant difference in the
means of two groups: the group that got CT instruction with AR and the control group. The
statistical significance confirms the integration of AR material significantly improved CT skills.
These results are consistent with other research (Angraini et al., 2023; Huang et al., 2023;
Hanid et al., 2022). The use of AR can improve CT skills. The research demonstrated that the
utilization of AR media resulted in a notable improvement in the critical thinking abilities of
seventh graders. Students who were exposed to the AR instructional approach displayed
enhanced abilities in analyzing, problem-solving, and applying CT strategies specifically
related to triangles and quadrilaterals.
The findings indicated that AR media helped students develop a deeper understanding of
geometric concepts, particularly those related to triangles and quadrilaterals. AR's interactive
features enabled students to see and control virtual items, leading to a more comprehensive
grasp of geometric properties and relationships. The integration of AR in CT instruction
fostered increased student engagement and motivation. This follows previous research
results (Cetintav & Yilmaz, 2023; Smith et al., 2023). Technology such as AR plays a role for
students in the construction and reflection of knowledge. The immersive and interactive
nature of AR experiences captured students' interest and encouraged active participation in
the learning process. This heightened engagement positively influenced their CT skills
development.
The research revealed that AR provided students with opportunities to apply CT skills in
real-world contexts related to triangles and quadrilaterals. This follows other research
(Toquero, 2021). Students' experiences using interesting AR are very important in terms of
exploring a concept and utilizing representations in real-life contexts. This experience trains
students' CT skills. Students were able to explore and solve authentic problems using AR
simulations, bridging the disparity between theoretical conceptions and practical
implementations. The results showed that the execution of AR media positively influenced
students' attitudes toward learning CT and geometry. The use of innovative technology
created a positive and enjoyable learning environment, resulting in increased motivation and
enthusiasm for the subject matter (Asril et al., 2023).
The findings emphasize the efficacy of AR media in improving seventh graders' CT skills,
namely in the realm of triangles and quadrilaterals. Triangles and quadrilaterals are abstract
objects in geometry. Geometry plays a role in understanding spatial structures and physical
entities. Employing geometry helps in mathematically describing and elucidating the motion
of physical objects, enabling improved modeling and analysis of physical phenomena.
Geometry is instrumental in formulating the laws of physics, particularly those about motion.
Galileo utilized geometric principles to formulate the laws governing the motion of falling
bodies and projectile motion. This contributes to detailing and predicting the behavior of
objects in space (Marshall, 2013).
The utilization of AR technology has significant potential to enhance science education by
integrating visual and interactive elements into the learning process (Lytridis, Tsinakos, &
Kazanidis, 2018). AR empowers students to visualize intricate scientific concepts that might
be challenging to comprehend in an abstract form. By presenting three-dimensional models,
simulations, or interactive graphics within the real-world environment, students can perceive
and grasp these concepts more tangibly. AR allows students to directly interact with virtual
aspects in the actual world, such as manipulating molecular models, seeing natural events,
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and conducting virtual experiments. This enhances active involvement and promotes a
deeper understanding of subjects. AR allows students to examine items or phenomena in
three-dimensional space, enhancing their comprehension of the structure and connections
between objects in a scientific setting. Students can investigate the solar system, ecosystems,
or human anatomy.
AR can deliver realistic simulations of scientific experiments or natural processes. Students
can observe the consequences of their actions in the virtual environment without the
associated physical risks or costs of real-world experiments. Certain AR applications facilitate
collaboration among students in a virtual learning environment, enabling group discussions
and exploration, thereby supporting social learning and group engagement. AR aids students
in understanding how scientists work by presenting real-life simulations of scientific activities,
offering insights into the research process and scientific methods. The integration of AR
technology can enhance motivation and engagement in science learning. Innovative and
captivating learning experiences can stimulate students' interest in science. AR allows
students worldwide to access the same educational resources irrespective of geographical
location, thereby improving the accessibility of science education (Uriel et al., 2020).
The application of AR in science education can create dynamic, immersive, and motivating
learning experiences, assisting students in constructing a more robust understanding of
scientific concepts (Sung, Ma, Choi & Hong, 2019; Chen et al., 2019). AR empowers students
to observe and manipulate three-dimensional physical objects such as molecules, atomic
structures, or item forms. This representation helps students understand intricate physics
issues that may be difficult to grasp using conventional visuals or models. AR enables students
to conduct physics experiments in a virtual environment without the need for physical
equipment. They can observe the effects of various experimental parameters and directly
comprehend physics principles (Nincarean Eh Phon et al., 2019; Stolzenberger, Wolf &
Trefzger, 2021).
AR can simulate motion concepts, including Newton's laws of motion or principles of
projectile motion (Ferdimana et al., 2023; Lytridis, Tsinakos & Kazanidis, 2018). Students can
gain a deeper understanding of the behavior of moving objects, by interacting with threedimensional models of physics concepts like planets in the solar system, magnetic fields, or
electrical circuits. This fosters a more profound understanding of the structure and
relationships between objects in physics. AR enhances learning by incorporating physics
components into the physical environment, allowing students to directly sense physics
concepts through comprehensive visual and audio experiences. Abstract physics concepts,
such as those in relativity theory or quantum mechanics, can be simplified through visual and
interactive representations in AR, enabling students to explore these concepts more
concretely. By incorporating AR technology into physics science education, teachers can craft
more enjoyable, effective, and profound learning experiences for complex physics concepts
(Huang et al., 2021; Nadeem et al., 2020).
The research demonstrates that the integration of AR led to statistically significant
enhancements, increased engagement, a deeper understanding of geometric concepts, realworld application of skills, and positive attitudes toward learning. This study gave new
information for strategy during the educational process (Al Husaeni et al., 2021; Fauziah et
al., 2021; Suherman et al., 2023). Specifically, it has been reported previously in mathematics
(Ajenikoko, and Ogunwuyi, 2022; Akinoso, 2023; Radiamoda, 2024; Husnah et al., 2021;
Lathifah and Maryanti, 2021; Putri et al., 2022; Marasabessy, 2021; Dallyono et al., 2020;
Hashim et al., 2021; Maryati et al., 2021; Ogunjimi and Gbadeyanka, 2023; Obafemi et al.,
2023; Mitrayana, and Nurlaelah, 2023; Camenda et al., 2021; Omolafe, 2021; Serra et al.,
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2021; Wijaya et al., 2022; Mirzabek, 2023; Awofala, 2023; Awofala et al., 2023; Obafemi et
al., 2023; Awofala et al., 2024; Obafemi, 2024; Maryanti, 2021; Jose, 2022; Dermawan et al.,
2022; Lagcao et al., 2023; Awofala and Olaniyi, 2023; Obafemi et al., 2024; Awofala and
Agbolade, 2024; Padmore and Ali, 2024; Lasisi et al., 2024).
4. CONCLUSION
Some aspects of the AR media application still require improvement, as discussed above.
Ensure that the photos are static and increase the color combination for a more beautiful
display. Since the two groups had similar abilities in the pre-test but showed significant
differences in the posttest, it can be inferred that the use of AR media in learning effectively
improved students' CT skills. The study revealed that the majority of subjects were female,
with 60 female students in the experimental group and fewer male students in the selected
classes. Therefore, future research is suggested to have more balanced samples, given that,
based on previous research, male students tend to be far more interested in operating
learning media than female students.
Several recommendations, suggestions, and limitations can be identified concerning the
research on enhancing students' CT skills through AR media. These are as follows:
(i) Recommendations: (a) Image Stability: It is recommended to enhance the stability of
images in AR media applications. Ensuring that the images do not move on their own can
enhance the overall user experience and prevent any distractions or disruptions during
the learning process. (b) Attractive Color Combination: Consider enhancing the
attractiveness of the color combination used for display in AR media. A visually appealing
interface can further engage students and enhance their motivation and interest in using
AR for learning.
(ii) Suggestions: Balanced Gender Representation: Since the subjects in the study were
predominantly female, it is suggested to have more balanced samples in future research.
This will enhance the study of how AR affects CT skills in various genders. Previous
research suggests that male students may have a higher interest in operating learning
media, and including a more balanced representation can provide insights into any
potential gender differences in learning outcomes.
(iii) Limitations: (a) Sample Size and Generalizability: The research acknowledged the
limitation of a predominantly female sample in the study. This could impact the
applicability of the results to a wider demographic. Future research should be conducted
using larger and more diverse samples to enhance the study's external validity. The
research specifically concentrated on improving CT skills relating to triangles and
quadrilaterals. Although this approach facilitated a targeted inquiry, it constrains the
applicability of the results to different domains within CT or mathematical principles.
Future studies could investigate how AR can improve a wider variety of critical thinking
skills. b. Duration of the Study: The research did not specify the length of the intervention
and the follow-up period. Examining the study's chronology can aid in assessing the
durability and lasting influence of AR on Critical Thinking skills.
It is advisable to improve visual stability and color coordination in AR media applications.
Future study should strive for gender parity and greater sample numbers to enhance the
generalizability of the results. Furthermore, examining a wider array of critical thinking
abilities and taking into account the length and post-study period can offer a more thorough
insight into the efficacy of AR in improving critical thinking skills.

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5. AUTHORS’ NOTE
The authors assert that there are no conflicts of interest related to the publishing of this
work. The authors verified that the paper was plagiarism-free.
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