research paper on augmented reality in education

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The Future of Quizzing: Augmented Reality in AR Test Exams

With the rapid advancement of technology, traditional methods of testing and quizzing are being revolutionized. One such innovation that is gaining traction is the use of augmented reality (AR) in exams, particularly in the popular AR Test system. This cutting-edge technology has the potential to transform the way students take quizzes, making it a more engaging and immersive experience. In this article, we will explore how augmented reality is shaping the future of quizzing and how AR Test exams are becoming a game-changer for both students and educators.

Enhancing Engagement and Interactivity

Augmented reality brings a new level of engagement and interactivity to quizzes and exams. Unlike traditional pen-and-paper tests or even online assessments, AR Test exams allow students to interact with digital content in real-time. By simply pointing their device’s camera at designated markers or objects, students can access additional information, 3D models, or multimedia resources related to the quiz questions.

This interactive element not only captures students’ attention but also promotes active learning. Rather than passively reading questions and selecting answers, students can explore concepts visually through AR overlays. This hands-on approach not only enhances understanding but also helps retain information more effectively.

Real-world Applications for Better Understanding

One of the key advantages of using augmented reality in quizzes is its ability to bridge the gap between theoretical knowledge and real-world applications. Many subjects often require practical understanding beyond textbook definitions. With AR Test exams, students can visualize complex concepts or scenarios that would otherwise be challenging to grasp through traditional methods alone.

For example, imagine studying physics equations without any practical application. With augmented reality, students can see these formulas come to life by overlaying virtual objects in their surroundings that demonstrate their relevance in real-world scenarios. This immersive experience enables a deeper understanding of concepts by providing tangible connections between theory and practice.

Personalized Learning Experience

AR Test exams offer a personalized learning experience that adapts to each student’s needs. By leveraging augmented reality technology, quizzes can be tailored to match the individual learning styles and preferences of students. This customization allows for a more effective and efficient assessment of knowledge.

In an AR Test exam, students can receive instant feedback on their answers, guiding them towards the correct solution or providing additional explanations when needed. This real-time feedback not only helps identify areas of improvement but also reinforces learning by addressing misconceptions promptly.

Furthermore, AR Test exams can adapt difficulty levels based on students’ performance. By analyzing their responses and progress, the system can generate questions that challenge students at an appropriate level, ensuring an optimal learning experience for each individual.

Remote Learning Possibilities

The COVID-19 pandemic has highlighted the importance of remote learning options. Augmented reality in AR Test exams offers a solution to bridge the gap between physical classrooms and virtual education platforms. With this technology, educators can create immersive quizzes that can be accessed remotely by students from anywhere in the world.

AR Test exams allow for flexibility in terms of time and location while maintaining the benefits of interactive assessments. Students no longer need to be constrained by physical classrooms or rigid schedules when taking quizzes. This innovation opens up new possibilities for distance education and lifelong learning opportunities.

In conclusion, augmented reality is revolutionizing quizzing with its ability to enhance engagement, promote interactivity, bridge theoretical knowledge with practical applications, offer personalized learning experiences, and provide remote learning possibilities. As technology continues to evolve rapidly, we can expect augmented reality to become an integral part of educational assessments like AR Test exams – paving the way for a more immersive and effective approach to testing in the future.

This text was generated using a large language model, and select text has been reviewed and moderated for purposes such as readability.

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Systematic review article, augmented reality in educational inclusion. a systematic review on the last decade.

• 1 GIDATI Research Group, Pontifical Bolivarian University, Medellín, Colombia
• 2 Escuela Superior de Ingeniería y Tecnología (ESIT), International University of La Rioja, Logroño, Spain
• 3 Department of Communication Sciences and Sociology, King Juan Carlos University, Madrid, Spain

The use of Augmented Reality (AR) to achieve educational inclusion has been not deeply explored. This systematic review describes the current state of using AR as an educational technology that takes into consideration the needs of all students including those with a disability. It is done through the analysis of factors, such as the advantages of AR, its limitations, uses, challenges, its scope in the educational field, the attended population and the positive or negative effects of its use in learning scenarios that involve students with diverse educational needs. A total of 50 studies between 2008 and 2018 were analyzed through searching in three interdisciplinary databases: Scopus, Web of Science, and Springer link. For this, the methodological stages considered were planning the review, search, analysis of literature and results report. After analyzing the results, it was possible to demonstrate that the use of AR for inclusive education in the field of sciences is where more studies have been conducted. In regard to the population with disabilities, among the most representative advantages reported were the motivation, interaction and generating interest on the part of the student. At the same time, an important methodological limitation identified was the size of the sample; some investigations were done with two or three subjects, some studies Single Subject Designs were found. In terms of the population attended, the studies generally included students with different impairments (hearing, visual, motor or cognitive), minorities (ethnic, vulnerable), leaving aside other groups excluded as exceptional talents and immigrants, which could be explored in the future. Despite different problems to be addressed, few frameworks to the diversity attention in education were reported, and there was no model and methodology in inclusive education considered in the studies. Finally, from this review we have identified open issues that could give rise to new research in the subject of using AR to favor the creation of inclusive learning scenarios.

Introduction

According to UNESCO (2017) : “the 2030 agenda for sustainable development, focused on ensuring that no one is left behind, provides a unique opportunity to create more inclusive and equitable societies. This should start with inclusive education systems” (p. 4).

In this regard, for more than two decades, the member countries of UNESCO have implemented policies of educational inclusion, in order to reduce the marginalization and exclusion of students with different learning preferences in the education system, accepting the calls for offering an education that is lifelong and that fits the needs of students ( Lindsay, 2018 ).

The processes of attending the diverse needs of individuals in regards to education, have evolved throughout history from a moralistic viewpoint ( Quiroga, 2010 ), followed by the concept of special education, such as that directed to subjects who, because of various issues: physical, psychological or emotional could not be adapted to traditional teaching ( Araque and Barrio, 2010 ), until now, when they have reached the concept of inclusive education, which is concerned with the right of each child to receive an education according to their individual learning needs ( Lindsay, 2018 ).

The advancement of information and communication technologies (ICT) has not only increased educational coverage by e-learning through the use of a variety of online platforms available today ( Lin et al., 2015 ), but also offers diverse learning experiences that have been shown to impact learning processes in different ways. Proof of this is ubiquitous learning (u-learning), AR (AR), virtual reality (VR), mobile learning (m-learning), games, gamification, or learning analytics ( Nincarean et al., 2013 ). Likewise, recent technological developments have led to mobile devices being used more frequently in education, mainly for children with disabilities or diverse educational needs ( Lin et al., 2016a ).

Specifically, AR allows combining and superimposing real objects with information and with virtual objects ( Azuma et al., 2011 ). At the same time, the augmented information may not be limited to the sense of sight but may also be applied to all senses, such as hearing, smell and touch ( Azuma et al., 2001 ). This makes AR a promising strategy to favor processes of educational inclusion ( Sheehy et al., 2014 ) since it favors multiple means of representation, of action and multiple ways of engaging students in the learning process ( Meyer et al., 2014 ). There is some scientific evidence to support this claim. For example, Hrishikesh and Nair (2016) , in their studies, indicate that AR makes possible for children with disabilities to understand concepts faster and better. Additionally, Mohd Yusof et al. (2014) have shown that AR offers exciting and fun teaching aids for students with special needs as it catches their attention.

Likewise, there is evidence that shows that AR positively impacts the educational experience of students, increases confidence, increases the level of commitment and interest ( Fombona et al., 2017 ), provides opportunities for self-learning ( Akçayir and Akçayir, 2017 ), enhances collaborative learning ( Phon et al., 2014 ), improves satisfaction and increases motivation in students ( Liu and Chu, 2010 ; Di Serio et al., 2013 ; Bacca et al., 2018 ).

Literature reviews on the use of AR in education analyze its development, as well as relevant aspects of use, however, as indicated by Gavilanes et al. (2018) when summarizing literature reviews on the use of AR in education until 2017, it is necessary to also analyze the potential of AR to support students with diverse needs, including those with disabilities.

This study presents a systematic review of literature, in which 50 studies that report a direct impact in attending students' diverse needs have been analyzed. The search source of the studies included in the review are databases: Web of Science, Scopus and Springer link. Different keywords were used in the searches in the three databases, the results were crossed to discard repeated documents, obtaining those that met the criteria of the review and following the steps described in the method used.

This document is organized as follows. The first section presents the works related to the present study, those that include AR in education and inclusion. The second section presents the information search process. The third section details the analysis of the literature found. The fourth section describes the results report and finally the fifth section presents the conclusions, challenges and future work.

Theoretical Framework

This section presents an analysis of existing studies in literature that address the use of AR for the creation of inclusive learning scenarios.

The study reported by Almutairi and Al-Megren (2017) describes the creation of an application with AR to teach Arabic to deaf primary school children, using the potential in combining video, images and audio with AR. The results of the research show that teachers and parents of deaf children prefer using multiple resources; Abas and Zaman (2011) made a storybook to motivate students toward reading. The book was aimed at students who had not reached basic reading skills and were in a recovery period. It consisted of three levels: easy, intermediate and advanced, and managed to provide greater motivation, commitment and a pleasant experience in the immersion of the educational process.

In the studies of Mirzaei et al. (2014) AR was combined with audio and video (AVSR Audio Visual Speech Recognition) in aiding deaf individuals. Through speech recognition techniques, facial expressions allowed capturing what the narrator said, without the need of knowing sign language. By just the use of a screen, the speech became readable text displayed with AR, allowing deaf people to read and better understand what was communicated.

Kerdvibulvech (2016) conducted an AR application study on children with hearing impairment and the goal of the research was helping them communicate both visually and receptively. It applied a portable communication jacket that is linked, called “T.Jacket,” it used sensor technology with AR, and it also extended its application to people with disabilities for its ease in expressing emotions. The result of this evaluation confirmed improvement in understanding and communication.

In contexts of professional training, Bacca et al. (2015) introduced the application called “Paint-cAR,” for students with diverse educational needs, especially for those students with low levels of basic skills and low motivation. The application supports the learning process of re-painting a car, in a vocational education program. This process facilitated students to follow long procedures, which due to their lower level of logical competences and process follow-up, were difficult for them to perform.

In their work, Tobar-Muñoz et al. (2014) designed a digital game with AR called Gremlings [sic] in my Mirror, focused on the development of logical skills in mathematics, which was evaluated with children with diverse learning needs such as: Attention Deficit Hyperactivity Disorder, Autism, Down Syndrome, among others.

The literature reviews on the use of AR in education reported so far have had various objectives. The review carried out by Bacca et al. (2014) , as well as that of Chen et al. (2017) highlight the analysis of the current state, reviewing the trends and uses of AR in education, likewise its advantages, limitations and effectiveness. On the other hand, Phon et al. (2014) , conducted a review on the use of AR and its potential in educational contexts focused on collaborative learning. Santos et al. (2016) reviewed learning experiences with AR to analyze its usefulness at primary and secondary levels. Espinosa (2015) , in her work, focused on projects about education with AR that had been carried out in Spain, as a state of art for that country. Diegmann et al. (2015) reported a systematic review on AR with five areas: discovery-based learning, skills training, training applications, games, and AR books in order to determine their benefits. Fombona et al. (2017) published a synthesis on the relationship between AR and m-learning. In another contribution, Akçayir and Akçayir (2017) presented the systematic review of using AR in educational contexts of formal and informal learning, as well as in trainings in the workplace. Ibáñez and Delgado-kloos (2018) presented a qualitative content analysis between 2010 and 2017 on the use of AR technology to support science, technology, engineering and mathematics (STEM) in learning.

The works reported in the literature reviews describe in detail the current state of use of AR in education, making interesting contributions in regard to the trends and challenges of this area of research. However, none of them reported the current state of knowledge about the use of the AR in education when it comes to aiding the processes of attention to students' diverse needs and for promoting a true educational inclusion. In this context, the research question that guides this study is: What is the current state of use of AR in education in order to support the creation of inclusive learning scenarios?

General Guidelines

In order to carry out the review of the literature object to this study, we considered the guidelines and steps proposed by Egger et al. (2001) in their book Systematic Reviews in Health Care, as well as those of Kitchenham (2004) . Specifically, the steps followed for the development of the literature review were the following:

A. Planning the review

1. Ask the question and sub-questions of the review

2. Definition of preliminary categories of analysis

3. Define the sources of literature search

4. Define the inclusion and exclusion criteria of the literature

5. Define the search criteria

6. Search of literature

7. Selection of literature

C. Analysis of literature

8. Reading of the selected literature

9. Data extraction and coding

D. Results report

10. Interpretation of results

11. Generation of the review report

With regard to the analysis of the literature, the recommendations of the Prisma declaration (for reports of systematic reviews and Meta-Analyzes) were followed ( Urrútia and Bonfill, 2010 ; Moher et al., 2015 ). The PRISMA statement is the international updated version of the QUORUM statement (Quality of meta-analysis reports). In the following sections, each of the steps followed for the review is described in detail.

Planning the Review

The main research question that this literature review addresses is:

What is the current state of use of AR in education in term of population, interventions, comparators, outcomes and study designs, considering studies between 2008 and 2018 included in three interdisciplinary databases: Scopus, Web of Science and Springer link, in order to support the creation of inclusive learning scenarios?

According to this main research question, a series of research sub-questions were defined:

RQ1: What are the advantages, limitations, effectiveness, uses, challenges, and scope of AR in inclusive education?

RQ2: What are the different types of AR that are the most promising in creating inclusion and why?

RQ3: What types of research designs have been considered when evaluating the use of AR in inclusive education processes?

RQ4: What types of population have been included in the learning scenarios supported by AR?

RQ5: What frameworks or models for attention to diversity have been used to support the creation of AR applications that facilitate processes of educational inclusion?

RQ6: What types of technology, including assistive ones, have been developed to favor the use of AR for educational inclusion?

RQ7: What author's platforms and tools consider the diverse needs of users in the process of creating learning experiences with AR?

RQ8: What is the effect of the AR experiences in terms of outcomes identified in this literature review?

Once the research questions were defined, preliminary analysis categories were established for each sub-question, which could be revisited during the execution of the review. Next, the defined categories are shown.

RQ1: What are the advantages, limitations, uses, challenges and scope of AR in inclusive education?

• Field of education: based on the International Standard Classification of education ( UNESCO, 2013 ).

• Reported benefits of AR in inclusive education

• Reported limitations of AR in inclusive education

• What are the reported uses of AR in inclusive education?

• Reported challenges of AR in inclusive education

• Reported AR achievements in inclusive education

RQ2: What are the different types of AR that are the most promising to favor inclusion and why?

• Types of AR for inclusion

• Reasons to be used in the inclusion

• Research method

• Sample

• Method of data collection

• Types of groups with disabilities

• Types of groups excluded from society

• Purpose in the diverse population served

• Working frameworks developed with AR and educational inclusion

• Models with AR for educational inclusion

• AR applications in educational inclusion

• Reported technologies for educational inclusion

RQ7: What platforms and authoring tools consider the diverse needs of users in the process of creating AR-based learning experiences?

• SDK‘s

• Programming languages

• Authoring tools.

• Software for 3D modeling

• Other software

RQ8: What is the effect of the AR experiences identified in this literature review?

• Effect generated in inclusive education

As research sources, three (3) multidisciplinary databases were selected and recognized for their coverage and indexing, they were consulted and, subsequently, the results were cross-checked: Scopus, SpringerLink, and Web of Science. Scopus is “the largest database of citations and abstracts of refereed literature and high-quality sources on the web” ( Andalia et al., 2010 ), it covers scientific literature that is reviewed by experts, as well as Web of Science; these two are nowadays important sources of consultation ( Mongeon and Paul-hus, 2016 ). On the other hand, SpringerLink is also multidisciplinary, it offers access to more than 8.5 million documents.

Criteria for Literature Inclusion

General criteria:

1. Studies published between 2008 and 2018.

2. Studies that describe applications, models or education frameworks for diversity with AR.

Specific criteria in connection to research questions:

• SC.1) Studies that report advantages, limitations, effectiveness, uses, challenges, and the scope of AR in inclusive education.

• SC.2) Studies that describe which are the most promising types of AR to favor inclusion.

• SC.3) Studies that demonstrate the methods of educational evaluation that have been considered for applications of AR in inclusive education.

• SC.4) Studies that contain the types of research designs that they have considered to evaluate the use of AR in inclusive education processes.

• SC.5) Studies that indicate the types of population that have been included in the learning scenarios supported by AR.

• SC.6) Studies that describe frameworks, models or applications of AR that have been developed to support the processes of educational inclusion.

• SC.7) Studies that report what types of technology, including assistive, have been developed to favor the use of AR for educational inclusion.

• SC.8) Studies that indicate the effect of the AR experience.

Criteria for Literature Exclusion

The following exclusion criteria were defined and, therefore, the studies that had these issues were discarded:

• Studies or publications that didn't mention the term “AR.”

• Studies that claim to refer to AR but refer to mixed reality or virtual reality.

• Studies of AR that are not oriented in contexts of education for diversity or inclusive education.

• Studies that are not identified as articles, book chapters or conference articles, in the context of AR education and inclusive education.

Final Search Criteria

In order to start and have greater clarity, a preliminary search of documents was done, some results were analyzed and it was possible to verify that many studies between 2008 and 2018 have been published on different topics such as: diversity, inclusive education, special education, disability, and universal access in contexts of education with AR. All these were used as keywords and similar results arose when consulting the terms in Thesaurus of UNESCO. Therefore, the following query string was established for each term: “(including AND education and with AND augmented AND reality) AND PUBYEAR > 2007.” A total of six queries were made for each database, changing the keywords for each search and collecting the results.

Analysis of Literature

Performing the search according to the defined criteria, 363 documents were initially identified among scientific articles, book chapters and conference articles; the first search was made on April 22nd, 2018 and the last on May 3rd of the same year.

A first filter was applied to these 363 studies, evaluating the inclusion and exclusion criteria by considering the title and abstract of each literature, and cross-checking the results of the three databases to discard repeated documents. After this filter, 96 documents remained. Finally, when reading each of the 96 articles, a total of 50 studies met the criteria proposed and defined for the review: 26 journal articles, four book chapters and 20 conferences ( Tables 1 , 2 ).

Table 1 . AR studies in journals.

Table 2 . AR studies in conferences.

Once the literature to be reviewed was defined, it was read again in detail and the process of extracting and coding the data began, by taking into account the respective preset format for data systematization.

Results Report

This section describes the results obtained from coding, considering the categories and subcategories established in the planning section of the review with respect to each research sub-question. The list of categories is made according to the research questions (RQ).

Next the findings according to each research question are shown.

• F1: Advantages, limitations, uses, challenges, and scope of AR in inclusive education.

The main advantages reported in the studies analyzed are increasing motivation (24%) and facilitating interaction (18%). These two advantages that are the most frequent in the review coincide with the findings of other studies about AR in education ( Bacca et al., 2014 ; Diegmann et al., 2015 ; Chen et al., 2017 ; Fombona et al., 2017 ).

The third most frequently reported advantage refers to the fact that the AR catches the interest of students with disabilities or with special educational needs (SEN) (12%). This is considered an interesting finding because it is a key element when considering inclusive education. In this sense, several studies analyzed show the benefits of AR in working with students who have SEN, evidencing the work with the following populations: auditory limitation ( Carvalhoand Manzini, 2017 ), visual limitation (Lin et al., 2016), autism ( Tentori et al., 2015 ), attention deficit hyperactivity disorder ( Lin et al., 2016b ), dyslexia ( Persefoni et al., 2016 ).

The fourth advantage identified is the low cost of implementing this technology in the classroom (8%). Although some vision devices are expensive, “AR provides tools for rapid and low-cost presence” ( Zainuddin et al., 2010 ; Ab Aziz et al., 2012 ; Chen and Wang, 2015 ; Hsiao and Rashvand, 2015 ) and therefore it becomes a good tool to support processes in the classroom.

Helping with immediate memory has been identified as the fifth advantage most frequently stated in the studies, something that is also called short-term memory (6%) ( Vullamparthi et al., 2013 ; Cihak et al., 2016 ; Martín-Sabarís, 2017 ).

The order of the rest of advantages is as follows: efficiency in the learning process (6%) ( Fernandez et al., 2015 ; McMahon et al., 2015 ; Sytwu and Wang, 2016 ). Development of cognitive skills (4%) ( Benda et al., 2015 ; Bülbül et al., 2016 ). The student-centered nature of technology (4%) ( Tobar-Muñoz et al., 2014 ; Tentori et al., 2015 ). Reinforcement of student attention (4%) ( Vinumol et al., 2013 ; Escobedo and Tentori, 2014 ). Enjoyment in the training process (4%) ( Sheehy et al., 2014 ). The exploration and easy technological use by the student (4%) ( Lucrecia et al., 2013 ; Marín Díaz, 2016 ). The satisfaction generated for the student (4%) ( Chang et al., 2013 ; Sahin et al., 2018 ), and the most realistic perception provided (2%) ( Miundy et al., 2017 ).

These findings show that AR is a technology that favors inclusive education.

Most of the studies do not mention AR limitations for inclusion (54%), which is a high percentage that leaves open the possibility of expanding the research to know in detail what are the limitations in using AR in inclusive education and other contexts.

Among the most important limitations we can mention would be the limited number of subjects in the sample size (22%). The fact that these studies indicate problems in expanding the sample in the research. According to this literature review, most studies have had <10 participants, which is considered to be a very small size ( Zainuddin et al., 2010 ; McMahon et al., 2016 ; Cascales-Martínez, 2017 ). However, there are other issues that arise, for example, there are not many students in the same group or school institution with special educational needs and they are generally presented dispersed when applying the evaluation of the research. For this reason, these studies should be replicated in other similar populations ( McMahon et al., 2015 ).

In order of relevance, the following limitation identified is the need to connect to the internet (5%), the fact that the application of AR, in some cases, requires good internet connectivity ( McMahon et al., 2016 ). If that is not the case, this may hinder the application of AR technology.

Further limitations of the AR in supporting inclusive education identified with high frequency in the review are:

(1) technical problems at the time of using the application (4%), which according to the authors is important when the research focuses on students with disabilities, either physical or mental, because in those cases the levels of frustration must be controlled very well. In this sense, the preparation and planning of the experiences with AR and what are the internet requirements must be rigorous ( Sytwu and Wang, 2016 ).

(2) lack of research on using mobile AR (MAR) in education with SEN (4%). Despite the fact that using mobile devices in the educational field is not a very recent technological innovation, more research is still required on using it with diverse groups, in inclusive education) ( Sheehy et al., 2014 ).

(3) qualified staff is required (4%); especially teachers ( Colpani and Homem, 2016 ) and/or assistants are usually required to have basic digital knowledge for adopting ICT ( Marín Díaz, 2016 ). However, for the creation of augmented content the level of complexity may increase.

(4) it is not possible to replicate or repeat the study in another scenario (4%), as these are studies related to inclusion and special needs (SEN). They address problems of students with SEN, and therefore, these studies can hardly be repeated in other educational settings, although there may be exceptions ( Chen and Wang, 2015 ).

(5) the difficulty in recruiting participants for the study (4%), which explains the other limitation listed above, related to the size of the sample. Researchers report difficulty in finding students with SEN and acquiring the necessary documents to allow them to participate in the studies, including those needed from their parents ( Lee et al., 2018 ).

Other limitations with less frequency in the studies are:

(1) Luminosity difficulties (2%); luminosity is a requirement of AR technology, especially regarding markers, because good lighting must be available around markers.

(2) AR applications do not allow adding 3D images in application mode (2%), meaning it is generally not possible for the user to change or add images.

(3) Long-term results of the use of AR are needed to favor inclusion (2%). The use of AR in long-term educational inclusion should be analyzed and investigated in order to verify the time and the effects of this type learning for students.

(4) Requires training in digital competence for students (2%). In some cases, students with SEN do not know how to use the technology needed ( Cascales-Martínez, 2017 ), therefore, planning and prior training is recommended. This subcategory is related to the previous one, listed above, referring to qualified staff.

(5) The novelty effect could produce bias in the results of the research (2%) ( Cascales-Martínez, 2017 ). Which could be related to the student's fixation on technology and as a consequence, paying little attention to educational content. A good use of time and didactic methodologies are recommended in order to avoid distractions in this regard.

(6) The use of only one tool to collect information (2%). Some studies used only one information collection tool ( Zainuddin et al., 2010 ), usually surveys and/or interviews, however, in the case of children with different SEN it is recommendable to look for several sources of information collection in the same study.

(7) More research is needed to prove acceptability in school environments (2%). In the case of inclusion, research should always be expanded in looking for alternatives when using AR so as to avoid excluding or marginalizing any group, not only SEN students, but also other populations at risk of marginalization.

About the types of devices used to favor educational inclusion through AR we have that the most outstanding are handheld devices (68%). Which is a finding that confirms that using AR applications on mobile devices supports educational inclusion, tablets and smartphones being the most widely used ( Hsiao and Rashvand, 2015 ). PC and Web Cam (12%) come second, especially using them when caring for children with autism spectrum disorders (ASD) or intellectual disabilities which make using devices, such as desktop PCs necessary. Devices or screens mounted on the head occupy the third place (6%). These have been considered for cases of people with hearing and vision impairment, and autism ( Fernandez et al., 2015 ; Sandnes and Eika, 2017 ; Sahin et al., 2018 ). Glasses (4%) are used to improve deaf students' communication in ordinary schools ( Parton, 2017 ; Ioannou and Constantinou, 2018 ). Finally, large-screen projectors (2%), although very rare in the studies analyzed, have also been used for special cases in teaching primary school level mathematics ( Cascales-Martínez, 2017 ).

On the category of educational field of application, taken as reference UNESCO, 2013 international standard classification 2013 we found that more than half of the studies analyzed are focused on elementary school students (58%) with different SEN. Lower secondary education ranks second in AR (12%). These two fields of application cover 70% of the studies, which is revealing, and it confirms the global situation of favoring inclusiveness mostly in primary education ( Lindsay, 2018 ). In the third place is long-distance education (8%); here we can reference the study of Tesolin and Tsinakos (2018) which focused on developing three strategies for the elimination of systemic barriers in distance education in regard to inclusive education. Lastly, early childhood education, short cycle of tertiary education and undergraduate or equivalent studies are not reported in the literature reviewed; a possible explanation is the difficulty of having an adequate sample to carry out studies at these educational levels.

As the most relevant challenges, we can observe the long-term use of AR in different environments or contexts (10%). In this sense, the solutions found in trying to support inclusion make each study applicable to a specific context, but nevertheless, studies also indicate that solutions created to favor students with SEN can benefit all students ( Meyer et al., 2014 ). Therefore, the use of solutions developed in varied contexts should be promoted and applied for a longer time in order to verify their effectiveness. Secondly, lowering costs in some technologies for AR vision (8%) becomes an important need according to the authors of the studies linked to the review. While many devices for AR are inexpensive, which was considered an advantage, there are other devices of a higher cost, such as different types of glasses. This is considered another challenge because educational institutions usually have a low budget to implement solutions that favor educational inclusion. Thirdly, there is the need to improve the hardware of handheld devices and their configuration potential (4%), so as to ensure that mobile devices offer quality audio and video and ensure an improved AR experience.

Other challenges that arise are: (1) creating personalized learning activities (2%); (2) allowing to change the settings, such as controlling the sound (2%); (3). User connection limitations with the Kinnect device (2%), a tool that is used in some cases as a motion sensor combined with AR to address some issues for children with disabilities although when the number of participants exceeds 6 it is not possible to use it anymore; (4) creating strategies to avoid distraction in students (2%); (5) enabling the use of AR in the learning processes of students with visual limitations (2%). Although there are reported studies on the use of AR in students with vision impairments, the possibilities of use with students who are totally blind are very limited ( Marín Díaz, 2016 ). However, based on the contribution of Azuma et al. (2001) AR is not limited to the sense of sight, but also to others senses, such as hearing, smell and touch, generally used by students who are totally blind.

• F2: Different types of AR that are most promising in supporting inclusion.

When talking about inclusive education, researchers worked with markers mostly (84%), a result that is similar to that in other AR studies for education ( Bacca et al., 2014 ), a reason for this being that they are stable and allow a better follow-up and efficiency. Markers are graphic symbols that contain patterns that are easily recognized by the software of AR, through any camera, which allows to trigger objects superimposed in 3D, generally ( Wojciechowski and Cellary, 2013 ).

On the other hand, the second category in the table are those based on RA location (4%), something that requires the use of devices with accelerometer and compass as a main requirement and includes access to Internet with GPS. This type was especially used with students with intellectual disability and Down syndrome ( Smith et al., 2017 ).

• F3: Types of research designs considered to evaluate the use of AR in inclusive education processes.

The following table shows the research methods that were used: “qualitative-exploratory case study” (22%), “qualitative-descriptive” (24%), and “mixed methods” (16%). These were the most used methods evidenced in the documents analyzed, the others mentioned below have been less applied: “literature reviews or studies case” (6%), “Single Subject Designs” (12%), “quasi-experimental design” (8%), “literature reviews or case studies” (6%), “pre-experimental design” (2%), “quasi-experimental design” (8%), “pure experimental design” (2%), “transversal research” (8%). Findings on single subject designs are consistent with previous studies ( Horner et al., 2005 ; Gast, 2010 ) ( Table 3 ).

Table 3 . Research methods used to evaluate AR in inclusive education.

In relation to the samples, 48% of studies were found to have used samples of ten or fewer individuals, and 16% of the studies used between 11 and 30 participants. These results coincide with the limitation reported in the RQ1 on the difficulty to recruit participants. On the other hand, 10% of the studies report between 31 and 200 individuals. No studies with a sample size >200 (0%) were found, confirming the limitation exposed in RQ1. Finally, the methods of data collection used in the studies were questionnaires (24%), interviews (20%), case observation (12%), focus groups (10%), survey (8%), and case study (6%).

• F4: Types of population included in the learning scenarios supported by AR.

When speaking of inclusive education, the term is generally associated with learning scenarios where students with disabilities or special educational needs (SEN) participate ( Ab Aziz et al., 2012 ). In the context of the review carried out, inclusive education is understood as offering learning scenarios supported by AR in order to generate opportunities for all students, taking into account individuals with disabilities and also excluded groups, such as ethnic minorities, immigrants, among others ( Blanco, 2008 ).

Table 4 shows the population identified as target group in the studies reviewed, classifying them according to two categories: excluded groups and individuals with disabilities. With respect to the category of excluded groups, the largest number of studies were identified in the sub-category: Individual learning differences/different skills (16%). Only one study with ethnic minorities related to an indigenous population of Cauca in Colombia and their culture (2%) was identified in the review. Likewise, related to working with elderly populations, a study focused on training the elderly was identified (2%). No studies are recorded with the following target groups: victims of violence, religious minorities, immigrants, homeless people and/or population with exceptional talents. Working with these groups would be promising due to their great linguistic and cultural diversity. Researchers are encouraged to carry out research on the use of AR, since these groups have a high probability of being excluded from an educational system according to UNESCO. In particular, the exceptional talents of individuals can benefit from the use of AR methodologies or frameworks customized to their exceptional capabilities ( Jolly and Hughes, 2015 ).

Table 4 . Types of population in AR for inclusive education.

With respect to the Disability category, 20% of the studies were focused on individuals with hearing impairments (DHH), given that the AR allows the use of mobile devices and the visual channel is often preferred for perceiving information. The applications developed for this population combine videos with other visual tools or interactive multimedia ( Parton et al., 2010 ), also promoting the use of glasses for AR and QR codes ( Parton, 2017 ). On the other hand, 18% of the studies have also addressed the needs of individuals diagnosed with Autism Spectrum Disorder (ASD), since AR facilitates the creation of applications recognizing facial emotions, which represents a difficulty for individuals diagnosed with ASD ( Chen et al., 2015 ). This helps teachers reduce their workload and supports better concentration and motivation in children with Autism ( Escobedo and Tentori, 2014 ).

We found that 14% of the studies focus on individuals with intellectual disabilities. In this field AR has influenced the treatment due to its low cost and the use of gamification ( Colpani and Homem, 2016 ). Vinumol et al. (2013) created an interactive textbook for children with learning disabilities due to neurobiological disorder, using AR, video and images to enrich learning by interacting with the exhibits. McMahon et al. (2015) conducted a study with students with intellectual disability and autism measuring their ability to independently make decisions to navigate. The purpose was to help them travel to unknown places in a city, and students did so with more success using AR, compared to Google Maps and a paper map. Lin et al. (2016) also explored the use of AR in children with different intellectual disabilities to facilitate the learning of primary elementary geometry. They found that AR can increase motivation and tolerate frustration in children with this type of special needs. In another case, for teaching science vocabulary in post-secondary education, McMahon et al. (2016) conclude that the students managed to acquire the proposed definition and knowledge.

Other sub-categories of populations that were less addressed in the studies according to the review carried out were: visual limitations (8%), language deficiencies (6%), attention deficit hyperactive disorder (ADHD) (6%), physical or motor disability (4%), characteristic deficiencies (4%), cognitive deficits (4%), dyslexia (2%), down syndrome (2%), among others.

The main results of the purpose of the studies analyzed in this review have been: their application in inclusive education (20%), “improving the level of understanding in students with intellectual disabilities” (16%), and “eliminating or diminishing the hearing barrier, improving communication” (14%).

Other results were: eliminating or reducing visual barriers (8%), increasing the recognition of emotional expressions (8%), eliminating or reducing reading problems (6%), facilitating access to information (4%), eliminating or reducing motor barriers (4%). Improving vocabulary issues for people with disabilities (4%), employment for students with intellectual disability (ID) and autism (4%). Improving the level of attention and behavior (2%), detecting movements (2%), reducing the workload of teachers (2%), attending to student diversity (2%), improving navigation or displacement in students with disabilities (2%), conservation of cultural features (2%). All were focused and centered on inclusivity.

• F5: Frameworks or models for attention to diversity used to support the creation of AR applications that facilitate processes of educational inclusion.

Universal Design for Learning was identified as the most widely used framework in studies that support inclusive learning (12%). The reason is that this framework has been widely approved for inclusive education work around the world. Other frameworks identified were: “AR BACA Sind” (2%), an AR framework aimed at students with Down syndrome. “AR gamification” (4%) which proposes to help the learning process of children with intellectual disability in general and “FlarManager” (2%), an AR framework for Flash, used for the development of applications of students who are deaf. Another example is “co-CREARGBL” (2%), a learning methodology based on games which proposes three stages (training, iterative design and Class Evaluation). In this case, for the validation process the authors designed an application oriented to learning and increasing motivation in an indigenous community of Southwest Colombia. In total, five frames were found.

Although the previously mentioned frameworks were identified, 78% of the studies do not refer to the framework that was used to meet the diverse needs of the students. This shows that more research is needed in order to establish what are the theoretical bases of the solutions designed for attending diversity with the help of AR and also, how effective they are in achieving real educational inclusion.

Table 5 shows the applications for inclusive education: “Mobis,” “Tabletop system,” “SAM,” “AR-SiD,” “IVRALS,” “KanHan,” “Paint-cAR,” “Cuetaya,” “Gremlings in my mirror,” “ARCoach,” “Troyoculus.” In total, 11 reported applications. It is striking that 76% of the records do not mention the development of any application to attend these individuals, however, one reason may be the use of authoring tools, such as “Aurasma” or “Layar,” where it is possible to create and apply AR online easily.

Table 5 . AR applications for inclusive education.

Since there are different types of disability and of population at risk of exclusion in education, it is necessary to investigate and create more applications to meet these special needs.

• F6: Types of technology, including assistive ones, developed to support using AR for educational inclusion.

Technologies used with AR in inclusive education are mainly mobile AR (MAR) (44%). This result is easily explainable, it coincides with findings for RQ1, the use of handheld devices and with findings for RQ2, AR based on markers, which are the most used in inclusive contexts. The “based on vision” significance (16%) is another result that can be explained and confirms findings for RQ4, related to the population attended the most, groups with hearing deficiencies, through multimedia tools with AR.

The next subcategory in importance, based on sensors (6%), refers to those sensors used to search and record the movements of students with some physical or motor disability. Kinnect devices (6%) also help to control movements in combination with AR. Next, 3D (6%), may have been included by more studies in their applications, but only 3 studies mentioned it. The following entries are: “TextBook or Storybook” (4%), “ARVMS” (2%), “Oculus Rift (helmet)” (2%), “Tesseract OCR” (2%), “Face detection module” (2%), “ARCM” (2%), “SixthSense” (2%).

• F7: Platforms and authoring tools considering the diverse needs of users in the process of creating AR-based learning experiences.

Table 6 reports the platforms and software used to develop the applications of AR; considering that some studies used more than one tool, a classification of the category has been made as it follows. “SDK's or libraries”: “Vuforia” (8%), “ARToolkit” (6%), “FLARToolkit” (2%), “Vidinoti” (2%), “NyARToolkit” (2%), “ARTag” (0%), “ARToolkit for Unity” (0%). A possible explanation for the use of Vuforia is the fact that it is integrated into the new versions of Unity and has a free and commercial version and is “stable and efficient and offers several features, which allows the capacity of mobile applications and frees the developers of the technical limitations” ( Amin and Govilkar, 2015 ).

Table 6 . Software tools used with AR for inclusive education.

In the next category, “programming and developing languages” the following are reported: “Scratch” (4%), “Visual Studio” (4%), “C #” (2%), “UnityAR” (2%), “Java or JSP” (2%), “Flash” (2%). In this group the results don't make for big differences between them.

The registered authoring tools were: “Aurasma (HP Reveal)” (10%), “Layar” (4%), “AuthorAR” (2%), “Wikitude” (2%). The possible explanation is that Aurasma now HP Reveal, is one of the most used tools for browser in the world, easy to use, available for Android and iOS and free ( Delello et al., 2015 ).

Regarding software for 3D modeling, the following were reported: “Blender” (4%), “Irrlicht3D, OGRE3D” (2%). “Blender is a multiplatform computer program, dedicated especially to modeling, lighting, rendering, animation and creation of three-dimensional graphics, it is a free software” ( Rosales, 2015 ); in recent years this system has gained more followers ( Dovramadjiev, 2015 ).

In the category “Others,” only “The Joiner Algorithm” (2%) appears, and 52% of studies, more than half, curiously, do not mention the type of software tool used to create AR applications. More research is needed in order find more data and expand this information.

• F8: Effects of AR experiences identified in this systematic review.

Below, in Table 7 , are the registered and related effects, and the first one refers to improving communication in students with disabilities (24%). If we compared this result with findings for RQ4 in the disability category, where the highest percentage of studies had to do with “auditory deficiencies,” which in summary improves communication, we'll understand why this is the first entry, because it represents a fundamental reason for the effect analyzed here. The second entry, “it raises interest, attention, motivation and school performance in students with SEN” (22%), can be explained by findings in literature. Various studies have contributed to these effects in education ( Liu and Chu, 2010 ; Di Serio et al., 2013 ; Bacca et al., 2014 ; Chang et al., 2014 ; Akçayir and Akçayir, 2017 ), and the same can be said for children with special educational needs. Next, “the teacher can create personalized content for the child” (8%), refers to how experiences gave way to this possibility, something that increased the opportunities of an inclusive and personalized education. The entry: “increase of knowledge of the subject in students with SEN” (8%) has to do with results of different evaluations that highlighted the fact that students with different disabilities managed to acquire the knowledge proposed in the specific topic ( Cihak et al., 2016 ; McMahon et al., 2016 ; Cascales-Martínez, 2017 ). Then, “improve the teaching of work and employment skills” (6%) has to do with three documents that were inclined toward non-traditional teaching in people with disabilities who aimed to improve some skills needed to bring these individuals closer some type of employment. The entry: “motivates physical activity in students with disabilities” (4%) has to do with work aimed at children with mental problems ( Lin et al., 2016a , b ). The following: “to improve navigation through digital maps” (4%) refers to studies trying to make students able to move geographically on their own. The next entries are: “increases access to distance education” (2%), and “the burden of the teacher with the disabled child goes down” (2%), which has to do with the fact that, in some cases the teachers attending these types of students do not have the support needed or there are not enough teachers, and AR tools aim to reduce this burden in teaching ( Escobedo and Tentori, 2014 ). The following entry is “to improve the physical and mental health of the elderly” (2%) and the next one is “improves knowledge of indigenous culture and traditions” (2%); however, only one study was focused on preserving indigenous traditions ( Pinto et al., 2017 ), also considered herein as excluded groups.

Table 7 . AR effects on inclusive education.

In general, all studies ended with a minimum of positive effects on students with different needs, and, depending on the case, it improved their experience in the educational system taking advantage of the benefits of the AR.

Discussion and Challenges

The first challenge regarding the use of AR in the educational field and in particular in favoring processes of educational inclusion, refers to the educational levels linked to current studies. More research is needed in: early childhood education and the short cycle of tertiary education and degree or equivalent, all this taking into account the international standard classification of education (ISCED).

Another important future issue to consider is directing research toward educational fields where AR studies were not reported, such as engineering, agriculture, forestry, business, fishing, veterinary, among others, considering the diverse needs of students.

A third challenge has to do with the use of different types of AR to support educational inclusion. It is aimed at exploring the use of markerless AR, or AR without a marker. By taking advantage of the best technological conditions of current mobile devices, such as cameras and sensors (given that the most studies reported the use of markers and QR codes). Not needing markers could generate greater ease of use for students.

The fourth challenge is oriented toward the methods of data collection, going beyond questionnaires and interviews, which were reported as the most used methods. It is proposed to include other methods of data collection directly in the inclusive classroom, in order to avoid unreliable evaluations or giving desirable responses in the research ( Castells, 2016 ). Observation and case studies can help to a greater depth in the analysis of the investigation.

The fifth challenge is to further diversify the population served; most of the studies analyzed tended to address the educational needs of populations with hearing impairment and autism. It is necessary to expand and diversify the research to cover other needs, such as dyslexia, Down syndrome, attention deficit, hyperactivity, among others. Likewise, future research should include vulnerable groups such as: migrants, ethnic minorities, exceptional talents, which have not been addressed in research on the use of AR in education or have not been reported so far.

The sixth challenge identified is the need to expand research in developing models, frameworks and methodologies that use AR to favor educational inclusion, considering different populations that benefit from the relationship between technology and pedagogy. The development of these models, frameworks and methodologies should be done by multidisciplinary working groups that would not only focus on the technical characteristics, but have a strong didactic and psychological approach as well. We only found five frameworks oriented to a specific need of a disability, without considering wider contexts of diversity. No models and methodologies were reported. In this sense, frameworks supported by multimodal learning and AR ( Gilakjani et al., 2011 ) can be successful due to the multiplicity of channels and means of communication where the learning process is directed, guiding the creation of learning scenarios in contexts of diversity. Likewise, the consideration of the universal design for learning, a conceptual framework for attention to diversity that has been widely validated, could provide inputs from the conceptual standpoint of these models, frameworks and methodologies.

The seventh challenge is defining truly diverse samples, not oriented to isolated populations. Most of the studies analyzed state that they are oriented to specific types of people with disabilities, such as those who are deaf, blind, have Down syndrome, etc. Only a very small number of studies (3) define truly diverse samples.

The eighth identified challenge is the need to create and put into operation platforms or authoring tools that make use of AR and that are directly oriented to the attention of the diverse educational needs of students at different educational levels.

The ninth and last identified challenge refers to the evaluation of effects on medium and long term on the use of AR in different contexts; this would verify the real impact of this type of technology in learning scenarios that welcome diversity. Generally, the studies analyzed report a short-term evaluation through experimental studies carried out at a specific time. It is recommended to carry out experimental studies that allow verifying the impact of the use of AR over time.

Conclusions

A systematic review of literature on the topic of AR was carried out and applied in the context of educational inclusion; a total of 50 studies were analyzed, conference articles, book chapters and journal articles, applying the method of content analysis. The following factors were considered in the selected studies: field of education, advantages, limitations, uses, challenges and educational scope. In addition, we considered the purpose of the studies and research methods used, as well as the type of sample, and the population its effects.

Here is a brief summary of the main conclusions:

• The number of studies published on AR for educational inclusion between 2013 and 2018 has been maintained at an average of eight per year, with 2015 being the year when most articles were published, an average of 11.

• In the field of education sciences is where most studies have been applied, the least explored are in engineering, manufacturing and construction.

• Among the advantages reported were the motivation, interaction and catching the interest of the student with disability, all criteria that help inclusive education.

• The main limitations are small samples (often only a single subject is included) or the need for internet connectivity, considering this service is deficient or does not exist for certain populations.

• The most used devices are mobile or handheld devices, followed by the desktop computer or PC.

• Among the most reported challenges would be long-term focus and use in other environments or contexts. Most studies have not considered extending the time for testing and evaluating, nor extending to other scenarios outside those used initially.

• A high percentage of studies were applied to primary education, but education for secondary school, early childhood and short-term education should be explored in the future.

• The type of AR used most is based on markers, then geolocation; studies have not yet been explored without markers.

• Most studies used small samples, ten or less individuals, and some included between 11 and more participants.

• Information collection was mostly done through questionnaires and interviews.

• Regarding the population served, the studies were generally inclined toward students with disabilities, leaving aside another population or groups that are also excluded from the education system, something that could be explored in the future.

• Few frameworks for inclusive education were reported, despite the existence of various problems to be addressed.

• Some technologies have been used and combined in order to apply them in inclusive education, most of them in mobile devices, expanding the use of glasses and sensors.

• Vuforia is the library most used in the creation of AR applications, and authoring tools are Aurasma and Layar; however, it should be noted that most don't mention this aspect in their studies.

• The greatest effect is improving communication skills in students with disabilities, especially oriented to those with hearing problems, where more work has been done and therefore there are more studies on this topic.

The present work contributes to expanding the current state of research in the field of the application of AR in inclusive education, covering not only aspects of disabilities, but of other groups possibly excluded from the educational process, aiming at identifying the benefits and effects to be considered by future studies.

Data Availability

All datasets generated for this study are included in the manuscript and/or the supplementary files.

Author Contributions

JQ, SB, and RR: conceptualization. JQ and SB: formal analysis, investigation. JQ, SB, and RR: methodology. JQ, SB, RR, and GV: writing—original draft. JQ, SB, RR, and JC: writing—review and editing.

Social Justice Repair Kit Project ( https://www.sojustrepairit.org/ ), Doctorate in Engineering at Pontifical Bolivarian University and Scholarship from Colciencias Colombia. Call 754 of 2016: Formation of high-level human capital for the Department of Putumayo.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

GIDATI Research Group, Pontifical Bolivarian University, Medellín, Colombia, and VIRTUALAB Research Group, Technological Institute of Putumayo, Mocoa, Colombia.

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Keywords: augmented reality, educational inclusion, systematic review, educational technology, disability

Citation: Quintero J, Baldiris S, Rubira R, Cerón J and Velez G (2019) Augmented Reality in Educational Inclusion. A Systematic Review on the Last Decade. Front. Psychol. 10:1835. doi: 10.3389/fpsyg.2019.01835

Received: 23 April 2019; Accepted: 24 July 2019; Published: 13 August 2019.

Reviewed by:

Copyright © 2019 Quintero, Baldiris, Rubira, Cerón and Velez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Silvia Baldiris, silvia.baldiris@unir.net

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The effectiveness of using augmented reality (AR) to enhance student performance: using quick response (QR) codes in student textbooks in the Saudi education system

Sameer mosa alnajdi.

Education Technology Department, Faculty of Education and Arts, University of Tabuk, Tabuk, Saudi Arabia

Augmented reality (AR) is a new way to integrate virtual reality into the real world, and integrating AR into education offers opportunities for increasing student performance. The Saudi Ministry of Education integrated technology into its educational system by building an educational portal called iEN, which offers many technologies that support education, such as AR experiments, e-textbooks, learning games, video clips, and TV channels. This initiative made Saudi Arabia better prepared for the transition to remote education, which offered an easy and prompt shifting of the education system during the Coronavirus pandemic (COVID-19). The current study examined the effects of using QR codes as an AR to enhance student performance in Saudi education. The findings show that students who utilized QR codes in their education performed at higher levels than those who did not and demonstrated that students did not face any technical issues in integrating technology into their learning processes. However, that could be based on their generation of using technology (alpha generation), which became part of their lives.

Introduction

The place of education in the quest for sustainable development has served as an impetus for society. Such in Saudi Arabia, the goal has been invested in discussing how the capacity of education could enhance to meet the knowledge economy (Alnahdi, 2014 ). Education must be objectively restructured according to sustainability demands to achieve this goal. Various social factors should mediate this restructuring. The technological revolution represents a significant social factor for mediating this restructuring, as technology serves as a powerful social force for transforming the knowledge economy environment. However, this implies that the evolution of technology must be accompanied by a responsive curriculum reorganization aimed at meeting the demands of the knowledge economy.

The impact of technology on education is not new. Historically, the impact of technology begins with four industrial revolutions. Penprase ( 2018 ) notes that these technological revolutions shaped the future of education, gender, nature, and the form of work that calls upon hastening the re-skilling of the workforce, which all follow from the continued proliferation of technologies.

Reflection on the nature and form of this trend points to significant technological adjustments to education, such as augmented reality (AR) and the related quick response (QR) code strategies, which are gaining in popularity. However, the roles and contributions of the new technologies to learning have yet to be defined in diverse contexts. Specifically, how inclusive are AR strategies such as QR codes? How effective are they in diverse settings? What are their strengths and weaknesses? What actions are necessary to deliver the desired outcomes? This paper builds on a semi-experimental study to investigate the effectiveness of using QR codes in Saudi's educational process.

Research problem

The continued proliferation of technology in the world is influencing education in various ways, as integrating technology into education has become a required choice, offering a change in some learning processes to achieve desired outcomes (Alnahdi, 2014 ). AR is one of the new technologies trending globally, as organizations, companies, and institutes have started using AR to support their projects and products. Augmented reality has also been incorporated into educational processes; furthermore, QR codes as an AR technology offer an easy way to increase student performance. The Saudi Ministry of Education (MOE) adopted AR and QRs in student textbooks, a portal built as a co-environment. That opens to researchers a path to discover and discuss the adoption of this promising technological response that can support education. Therefore, the effectiveness of using AR in the Saudi education system constitutes the research problem investigated in this study to inform the practice.

Research aims and objectives

The proposed research aims to investigate the effectiveness of QR codes in supporting the educational process. The findings are intended to inform these practices of any existing weaknesses that need to be addressed. Several objectives have been considered to achieve this goal:

• Enhancing student learning outcomes
• Evaluating the effectiveness of AR integration in education
• Providing feedback on using QR in the Saudi educational system

Methodology

Research question.

This research focuses on one main research question: How effective is using augmented reality in education in enhancing student performance, using QR codes in students' textbooks in the Saudi educational system as the case study?

Literature review

Literature acknowledges the pivotal role of AR in education and its growing popularity. Karakus et al. ( 2019 ), in an explorative review on the nature and form of AR in education, reported that, in 437 publications between 1999 and 2018, AR research concerned itself with interactive learning environments, virtual reality, mobile learning, and e-learning environments. The collective findings indicate that AR plays a positive role in enhancing education in these contexts.

Khairuldin et al. ( 2019 ) described AR as technology-oriented learning that integrates virtual objects to natural learning scenes, filling in gaps of previously missing information in real-life education. In essence, AR supports the construction of knowledge through active, autonomous, and supportive practical learning. Moreover, the process of reconstructing knowledge from experiences should emerge from reflecting on the practices, recollecting, and making notes on the nature of the situation in education and attending to personal feelings, re-evaluating experiences, and integrating experiences gained with those that were pre-existing.

Indeed, according to Alnajdi et al. ( 2020 ), AR provided an opportunity to observe and learn from real action, and it can be extended to general education because it enables students to envision how theories apply. Even in e-learning, using AR can help make learning more exciting, interactive, and fun. In areas in which it has been applied, the approach has improved learners' scores, enhanced motivation, and fostered cooperative learning. AR provides the learning opportunity to observe and test theory and foster creative thinking and effective decision-making processes through integrating virtual reality with real life.

According to Huerta et al. ( 2019 ), AR could enhance the standards of technical education, fostering learners' engagement, skills, and competence, which is preferred over traditional methods. They explained that one could acknowledge theories as a source of basic knowledge that drives problem-based learning. The practice needs to be addressed by theories. Nevertheless, to be successful, one needs to observe beyond personal experiences and expectations systematically. It is this systematic observation that can help to build consistent knowledge and perspectives from experience.

In a systematic review of AR in education, Bacca et al. ( 2014 ) reported a growing interest in creating a unique setting in education. Their review focused on AR's uses, limitations, advantages, challenges, future, and effectiveness. They reported various findings; Firstly, AR is mainly applied in higher education, especially in science, humanities, and art faculties. Secondly, in the contexts in which they are applied, their focus has mainly been on motivating learners. Thirdly, marker-based AR works through scans and marking to bring up an augmented reality experience such as an object, text, video, or animation. This type of AR is the most common, followed by location-based AR, which stands for marker-less, position-based, and other technologies that rely on GPS. This trend is attributable to the availability of sensors embedded in mobile devices, such as the digital compass, GPS, accelerator, gyroscope, and digital compass, and the possibility of using global position systems. Fourthly, marker-less AR requires significant improvements in algorithms for accurate tracking. At the same time, the use of an add-on console, such as Microsoft Kinect in Xbox, allows users to interact without using a controller or other intermediary device, which becomes increasingly more popular. The main goal of applying AR is to expound on explanations on the main topics of interest, including providing additional information using platforms such as educational games and lab experiments (Bacca et al., 2014 ).

Also, Bacca et al. ( 2014 ) observed various strengths and limitations of AR, and the notable benefits include supporting learning gains, motivation, collaboration, and interaction. AR has been particularly effective in enhancing student engagement, fostering positive attitudes, and enhancing performance. On the other hand, the limitations include placing too much emphasis on virtual information, the intrusive nature of AR, and the inherent difficulties in maintaining superimposed information. Moreover, AR is not inclusive to diverse learners, especially those with disabilities. At the same time, they acknowledged that many of the studies reviewed used mainly samples ranging between 30 and 200 participants.

Overall, the insights presented in the literature laud the use of AR in education. Nevertheless, the limitations noted potentially overshadow AR's benefits to education. More importantly, the review opens the question as to whether the findings can be generalized to different types of AR and educational contexts. For instance, is Saudi Arabia any different? Are the strengths and weaknesses observed unique? How do they lend themselves to diverse cases and contexts of QR codes?

The relationship between augmented reality and quick response codes

The literature acknowledges the significant relationship between AR and QR code technology. In particular, QR codes effectively fit in AR because of their innovative nature. Law and So ( 2010 ) described QR codes as two-dimensional barcodes decoded by QR scanners and mobile phones. Data such as contact information, SMS messages, plain text, and URLs can be embedded in QR codes available for access. Indeed, this feature makes them part and parcel of AR learning.

Indeed, according to Law and So ( 2010 ), QR codes aim to fulfill three elements of AR learning: location independence, time independence, and meaningful content. In this case, location independence refers to learning that is not limited to specific locations, implying it can be carried out in formal and informal, indoor, and outdoor settings. On the other hand, time independence refers to learning that can take place outside of class time. Finally, meaningful content describes the content that is diverse and suitable for learners in different contexts. In this regard, at their best, QR codes are a means to AR learning.

According to Downer et al. ( 2016 ), AR learning embedded with QR codes can significantly benefit. One of its defining characteristics is goal-directed, enabling it to guide preparing instructions to accomplish defined goals and objectives. The second defining characteristic is the interdependence of the underlying steps. The arrangement primarily emphasizes a whole-system approach that aligns objectives, evaluation, and instructions. Thirdly, it is defined by a closed system. The standard system view spans significant training and education delivery processes, including conducting the needs assessment, specifying objectives, task analysis, selecting media, producing material, formative and summative evaluation, and developing assessment strategies. Overall, these approaches are linear in the sense that they lay out the generic procedural framework, including the steps for analysis, design, development, implementation, and evaluation of instructions. Secondly, its input and output structure and learning assessment, task analysis, and objectives effectively support the gradable learning forms.

However, a typical learning system needs to be created to fulfill various requirements, especially a research and synthesis theory. In one way, it needs to be aligned to how humans conceive and attribute stimuli in the environment. Secondly, it also needs to capture information and how it is derived and disseminated. Thirdly, it needs to mirror the system concepts and the interrelationships with the intervening factors that deter or promote the realization of the desired goals. Lastly, it needs to reflect the needs of the knowledge economy (Rabu et al., 2019 ). Discussions on and attempts to improve education by making it interactive for learners in Saudi Arabia have taken place. It is interesting whether the learning arrangement effectively fits this arrangement.

The importance of the use of quick response codes in education

The relevant literature acknowledges the crucial role of QR codes in revolutionizing the learning process. It also highlights various areas of concern that invite debate on its effectiveness. For instance, in exploring the concept of QR codes and their benefits to digital education, one article noted that the two concepts are intertwined in that "the digital education system is nothing but education using gadgets" (Goyal et al., 2016 , p. 452). The influx of technologies, security, legitimacy, and the process of accessing digital information has presented significant challenges, as information technology holds numerous benefits for education. The use of a digital information system can now be likened to automating education by making it easy to access academic content. QR codes represent overcoming the underlying challenges and constitute a cryptographic approach for securing information, such as learning content, video clips, documents, exams, and certificates.

The use of QR codes is reported to touch on various facets of education, such as problem-based learning. Santoso et al. ( 2019 ) stated various benefits in their study on the use of QR in a teacher education program. Firstly, students assisted by QR demonstrated significantly improved outcomes compared to their counterparts who relied solely on direct instruction learning. Secondly, students subjected to problem-based learning who were assisted with QR codes had the mathematical problem-solving ability to improve their post scores compared to their counterparts. Considering these gains, Santoso et al. ( 2019 ) recommended that instructors invest in QR codes to develop engaging learning environments and enthusiastic students. Leone ( 2015 ) explained that these gains attributed them to the QR code being a tool for personalized, inclusive, and interdisciplinary learning experiences.

Moreover, Chicioreanu et al. ( 2015 ) acknowledged the challenges students face in accessing learning resources, further applauding the significance of QR codes in addressing these weaknesses. They particularly noted that colleges have been bombarding learners with hundreds of pages of information online that are so useful that the students must access them. Links can easily be clicked on a web page to direct users to the content sought. However, these links are difficult to pass on to learners in the classroom setting because of their long and complex combined string of characters. QR codes were created to enable quick access to information, and they can now be even more easily accessed because of the ubiquity of technologies such as tablets and smartphones that can scan the square QR. QR codes are popular technologies because of their relatively large capacity for quick decoding and their capacity to hold large amounts and multiple kinds of information. In questioning whether learning how to use QR codes is appropriate training, Chicioreanu et al. ( 2015 ) explained that QR technology enables various functions that support education, including transferring data such as teacher contact information, sharing additional resources, posting tutorials, interacting with course handouts, experiencing virtual tours, playing educational games, and completing interactive polls.

The technological merits of QR codes are best discussed in detail by Law and So ( 2010 ), who singled out their versatile nature. For instance, they reported that QR codes could carry much information, such as a long multilingual text, automated messages, business cards, linked URLs, and any other type of information that can be incorporated into the conventional two-dimensional barcode. They further noted that a QR code could typically hold up to 7,089 numeric characters, 1,817 Kanji characters, 4,296 alphanumeric characters, and 2,953 binary bytes. This memory capacity makes them preferable to Data Matrix, Maxi Code, and other 2D codes. Powered by mobile devices, it is easy for users to connect and access information with relative ease.

Some merits and demerits inherent to QR code-embedded learning are also mentioned in the literature. For instance, Chung et al. ( 2019 ), in their report on their inquiry into the use of QR codes in children's classrooms, noted that the codes are exciting for children who participated in their study. In their further examination of experiences with the use of QR codes, Law and So ( 2010 ) reported that many learners in junior schools found QR code-embedded learning to be engaging. However, many learners in this group were not well prepared for mobile learning. They reasoned that the education system could certainly not expect junior students to carry mobile devices to school. Other cases of using the QR in the math trial activity were expensive and unsuitable for significant learners.

Moreover, while it is pretty easy to use mobile devices to scan QR codes, students in junior classes often tilt their mobile devices while snapping codes, reflecting a lack of adequate knowledge on the use of mobile devices. Lastly, the reliance on 2G and 3G networks provided by mobile carriers is expensive and potentially overshadows the benefits of QR codes. Moreover, Abdul Rabu et al. ( 2019 ) acknowledged that the users' motivation mediates the use and acceptance of QR codes. This motivation is not always guaranteed. So ( 2011 ), in questioning why the academic world has been slow to adopt QR codes, hypothesized that instructors are lagging because they have not mastered the use of the technology. It then seems that the benefits of QR to education may not be straightforward because various factors mediate it.

iEN: national education portal in Saudi Arabia

The Ministry of Education (MOE) in Saudi Arabia created a portal for education called the "iEN," an Arabic word that means eye, which can be found at https://ien.edu.sa/ which was designed to provide co-environments to support the learning process, see Appendix A , has three sub-portals: (1) books and lessons, (2) iEN revisions, and (3) additional resources. The portal provides more than 100 AR experiments, video clips, exercises, whole textbooks, learning games, and general information. Users can access all this information using the QR codes provided in their textbooks, see Appendix B . The three sub-portals of the iEN are separated into four levels according to the target audience: students, teachers, principals, and parents. Users can sign up to create an account and sign to their accounts to access the portal's functions and tools, to use the portal's list to find new resources and to review the users' guide based on their character, see Appendix C (iEN, 2020 ; MOE, 2020). Also, users can access the Q&A section to find answers, contact the help center, and make suggestions. The intelligent portal corresponds with both Android and iOS smartphones and tablets.

Four main access points are available to parents: eBooks, iEN reviews, additional resources, and "my children," which enables them to create exams for their children and follow their children's progress in courses, see Appendix D . Teacher accounts contain two main sections: information board, which has 11 access points, and teacher services, which has five access points. The access points make a quantity of information and services available to teachers, such as contacting their students through the students' community, creating question banks, and issuing worksheets to the virtual learning community. A feature called "my students," which is a learning community, allows teachers to exchange knowledge and discuss educational issues with their students and provides support and complete follow-up to students using a variety of strategies, see Appendix E . Student accounts also contain two sections: information board, which has eight access points, and student services, with five access points. These 13 access points offer free learning features, including a library of educational and targeted videos related to extracurricular activities and self-evaluation services, which enable students to evaluate their performance and send their results to their teacher, see Appendix F (iEN, 2018 ).

The iEN portal enabled the Saudi MOE to shift quickly from traditional education to distance education during the coronavirus (COVID-19) pandemic. Use of the iEN portal was an additional option in semesters before the lockdowns associated with the COVID-19 pandemic, but after schools closed on March 9, 2020, the MOE linked the iEN with Future Gate (FG), a virtual school created and established by the MOE offered free to all public schools across the country to support the traditional school. However, due to the pandemic, the MOE combined the iEN and FG under the Unified Education System (UES) and made the iEN more effective by developing the portal and adding more functions in each sub-portal to support parents, teachers, and students.

Design of experiment

A semi-experimental method was employed, for this study, in one of the middle schools in Tabuk, in the northern region of Saudi Arabia, which has a population of 667,000. According to the Tabuk Education Administration (TEA) ( 2019 ), the region has 1459 schools, 352 of these schools are middle schools and have 47,078 students (TEA, 2019). Two classes were chosen randomly to include control and experimental groups in this study. Each class contained 33 students; both had completed the last unit in the traditional classroom setting. The control group in the experiment was taught the lesson traditionally without using the QR or iEN functions.

In contrast, the experimental group was taught to enhance learning using the enrichment content available through the QR and iEN. Before the lesson began, the students completed an exam for the unit, see Appendix G , as a pre-test, and then students started learning through traditional ways and using QR codes to transfer to the iEN portal. QR codes were provided at the beginning of each lesson see Fig.  1 . These codes transfer the individual scanning the code to the AR environment, which contained seven enriching video clips that enhanced knowledge; two of these clips provided experimental explaining, and the other five clips explained the lesson in an avatar video, see Appendix H . Two video clips provided asynchronous teaching, a clip summarizing the lesson in a knowledge map, and an e-book. In the experimental group, students learned the lesson through traditional teaching methods, watching the video clips in class, and completing other exercises provided on the iEN after school (e.g., activity practice, self-evaluation). After the experiment, students completed a post-test to determine the QR codes' effects on student learning. On pages 60–61 of the textbook, a post-test is given as a revision test at the end of the course. Only traditional teaching methods were used.

QR code of lesson in student textbook (MOE, 2020)

Students, in the beginning, took the pre-test to measure their knowledge. The results of the pre-tests showed a minimal difference of 0.12 (Mean Difference: 5.65–5.55 = 0.12) between the two groups' performance, which indicated no statistically significant difference existed between the two groups at α  ≤ 0.05, reflecting their homogeneity (Table ​ (Table1 1 ).

Pre-test results

However, following the experiment, the post-test was taken, and the results indicated a difference of 3.27 between the two groups, as shown in Table ​ Table2, 2 , which was statistically significant at α  ≤ 0.05 (Mean Difference: 13.21–9.94 = 3.27), with the experimental group students outperforming the control group students. Based on these results, this study agreed with the findings from Ozcelik and Acarturk (2011) of the benefits of using the QRs provided in the students' textbooks, which supported the use of QR in student textbooks make learning more accessible and more effective. The current study's findings also agreed with many other studies, such as Liu et al. ( 2007 ) and Rivers ( 2010 ). Students showed higher results and scientific improvement because they enjoyed and benefited from using the QRs and the iEN portal.

Post-test results

Furthermore, students in the experimental group had been advised to use the portal by completing assignments provided on the iEN, including the practice activity creating exams through the "evaluate yourself" function. The assignments through the iEN were completed by 91% of the participated students, and only three students failed to do the practice activity due to Internet access issues, and only one failed to access the self-evaluation. Those assignments offered direct feedback, so students could redo them multiple times until they obtained the correct answers. More details are provided in Table ​ Table3 3 .

Evaluation results of iEN assignments

Results showing significant differences between both control and experimental groups attributable to the experimental group, this finding agreed with (Sahin and Yilmaz, 2020; Tait et al., 2020 ), which reported that students who were in the experimental group were delighted and found it helpful and easy to use, and they prefer to use AR in their future learning. In addition, they deal with using the AR technology easily and reach a higher level of performance and achievement than students in the control group.

Also, results proved that using AR in education can offer positive opportunities and impacts to develop the education and support students, as Tsiavos and Sofos ( 2019 ) stated that, (1) learning benefits, (2) offering a motivating environment, (3) engaging students, (4) help students to focus on the lesson, (5) changing students' attitudes positively about the lesson, (6) students' excitement, (7) increasing students' eagerness, (8) increasing students' knowledge, (9) integrating virtual reality in the real-world to enhance locative perception, and (10) developing students' observation.

A review of the literature indicated that the impact of technology on the education curriculum is inevitable and significant. This inevitability follows from the fact that education and technology are intertwined. Indeed, education cannot exist as an island; it must exist to fulfill the needs of society. Since social needs are dynamic, especially those influenced by technology, education must respond through curriculum change. Augmented learning and the use of related technologies such as QR codes lend themselves to the discussion to enhance the potential of education. These technologies offer various advantages to education and learning processes.

In this current study, students showed their interactivity by using the QR codes in engaging, inclusive, and personalized ways, which motivated and steered them to perform better in different subjects and contexts. After the experiment, students were asked for their perceptions of using the QRs. Also, they stated that they started using QRs in other textbooks to understand lessons better and prepare for the new lessons through the AR clips. These comments agreed with feedback reported in many study results (Hwang et al., 2011 ; Liu et al., 2007 ; McCabe & Tedesco, 2012 ; Rikala & Kankaanranta, 2012 ; Rivers, 2010 ). Students in those studies reported an improvement in their performances and achievement. They were motivated and enthusiastic during using the QRs in the learning process, which made them more comfortable dealing with the lessons and decreased their stress. A few students in this study reported their limited ability to use the QRs at home based on limited ownership of smart devices and access to the Internet, but that did not affect their class activities.

As the benefits of QR codes in educational contexts such as in Saudi Arabia were under debate, AR did not apply in the Saudi education system until the MOE established the iEN. As an additional note, due to the pandemic, use of the iEN increased, with more than 7 million accounts created, and the number of QR scanning passed 100 million (MOE, 2020 ).

This study was conducted during the first semester of the 2019/2020 academic year and highlighted the benefits of using AR to make the learning process more effective. After the science teacher shared the differences and the positive results with his students, he started to apply the experiment with all his classes. However, before finishing the article to report the funding, the world experienced Coronavirus (COVID-19) pandemic. Based on the pandemic, all education switched to a distance learning context, and schools in the whole world have been closed. In Saudi Arabia, the readiness of the digital environment due to the integration of technology before the pandemic helped the MOE more easily shift the education process from the traditional classroom setting to the distance education format; students were able to use the AR lessons provided on the iEN and using the virtual school (FG). Utilizing AR in Saudi education started before the pandemic been occurred, which helped students transition easily and allowed teachers to expand the process and possibilities of making education more effective. QR codes in schools have increased over the years, and their role became more effective by offering teaching clips, e-textbooks, AR experiments, and learning games and developing a following from teachers, parents, and principals. Lastly, in this study, the findings agree with those of other studies about the effectiveness of AR and QR in education and how it contributes to enhancing and improving student performance. The integration of AR and QR in education can be attributed to many factors, including those provided in the studies reviewed, such as connecting knowledge with actual exercises.

One of these factors is students' characteristics, as today's students are considered the alpha generation for their skilled use of technology. Alpha generation is the last generation of using technology, this generation was born in 2010, and years after, they were born with the new technologies and live-in digital entertainment. Technology became part of their lives, and they could not imagine their lives without it (Tootell et al., 2014 ). They deal with technologies in many contexts, such as the games they play that are built on AR, so the technologies have become part of their daily lives.

Offering the iEN portal allowed the Saudi Ministry to shift education quickly from traditional education to distance education during Coronavirus (COVID-19) pandemic. Using iEN was an additional option in the previous semesters, but after schools closed on March 09, 2020, the Ministry of Education linked iEN with Future Gate (FG), a virtual school created and established by the Saudi Education Ministry which offers free to all public schools all over the country to support the traditional school system. However, during the pandemic, MOE combined iEN and FG under one system called Unified Education System (UES). Also, MOE developed and added more functions into the iEN portal to make it more effective, such as offering for parents examing their children. Also, for students offers a free learning feature, which has a library of educational and targeted videos that can be invested in curricular and extracurricular activities. In addition, teachers have the ability through a feature called "my students" to create a learning community that allows teachers to exchange knowledge and discuss educational issues with their students and provides supporting and full following-up to students with various strategies.

So ( 2011 ) found some teachers revising or trying not to use QR and AR because they lack the skills to use technology, so I recommend searching more studies to review the constraints and obstacles of adopting AR and QR in education and finding solutions. In addition, researchers could start to design environments to merge virtual reality (VR) in education to build AR environments based on instructional design models. Finally, researchers could study how the AR environment affects MOOCs' massive open online courses.

In addition, to make the AR more effective, it should build based on instructional design models to ensure it matches learners' needs characters and motivates them. According to Iqbal et al. ( 2019 ), using the ARCS model (Attention, Relevance, Confidence, and Satisfaction) helps to evaluate the system and AR to make it fit and appropriate for learners, for that, a study could review and analyze the whole website iEN through instructional design models. Alalwan et al. ( 2020 ) mentioned that teachers participating in their study reported that a lack of their skills in instructional design adversely affects the willingness to use AR properly. Also, the stalemate of the content material in AR systems and the hardness of requesting modify limit teachers from making any modifications based on students' needs in line with the curriculum.

This study pointed out the necessity of researching future studies to review and analyze ARs environments for checking the design through instructional design models to ensure their fitting and occasioning to education and students' needs and characteristics.

Limitations

This study has some limitations. The first limitation was grade level. The study was conducted on second grade in middle schools (contains grades from seventh through ninth grade; first, second, and third grades) in Saudi Arabia. Also, it applied during the first academic semester of 2019 at TEA. Another limitation was the study's focus on a science course. Specifically, a lesson about alkaline liquid and acidic liquid, all materials were available by scanning the QR code provided in students’ textbooks.

Acknowledgements

I would like to thank the Education Administration in Tabuk for their support, and the Scientific Research Deanship in University of Tabuk for their granting of this study under grant number S-1440-0036.

Associate professor of Education Technology at University of Tabuk. Hold a Ph.D. in Curriculum and Instruction from Indiana State University in 2014, in the track of Educational Technology, and had Instructional Design Certificate from Indiana State University, USA, 2014. Chairperson of Education Technology Department. Former chairperson of Curriculum and Study Plans Unit at Education and Arts College, Former Dean of Deanship of Development and Quality, Former official spokesman, and former member of the university’s board in University of Tabuk.

Appendix A: iEN main page

Appendix b: ar experiments, appendix c: roles and characters to join ien, appendix d: parent account services, appendix e: teacher account services, appendix f: student account services, appendix g: revision test, appendix h: lesson pages.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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• Published: 26 June 2023

The impact of augmented reality on student attitudes, motivation, and learning achievements—a meta-analysis (2016–2023)

• Wenwen Cao 1 &
• Zhonggen Yu   ORCID: orcid.org/0000-0002-3873-980X 2  

Humanities and Social Sciences Communications volume  10 , Article number:  352 ( 2023 ) Cite this article

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• Science, technology and society

In light of the COVID-19 pandemic, a significant number of students have been compelled to remain at home while receiving education supported by augmented reality (AR) technologies. To determine the impact of AR technologies on educational outcomes, the present study undertook a meta-analysis utilizing Stata/MP 14.0. The study found that the attitudes of learners towards AR-assisted education were more positive, and their learning achievements were significantly higher compared to those who did not use AR technologies. However, there was no significant difference in motivation levels between the AR-assisted and non-AR-assisted educational models. The researchers explored several reasons for this result, but they could not identify any clear explanation. Future studies could take into account other factors that might affect education outcomes such as learning styles and learner personality. Doing so could shed more light on the impact of AR technologies on education.

Introduction

Since the emergence of the COVID-19 pandemic, many students have been compelled to receive education from home with the assistance of augmented reality (AR) technologies (Saleem et al., 2021 ). Given the rising popularity of AR technologies in the field of education (Tezer et al., 2019 ), a multitude of studies have conducted meta-analyses to investigate their effectiveness, particularly under the COVID-19 pandemic context (e.g., Selek and Kiymaz, 2020 ; Bork et al., 2020 ; Gargrish et al., 2021 ; Gonzalez et al., 2020 ). One recent meta-analysis found that AR technologies could have a positive impact on learning outcomes when users’ spatial abilities were taken into account (Bölek et al., 2021 ). While medium-sized effects were often observed in terms of learning gains resulting from the use of AR (Garzón and Acevedo, 2019 ), the results may have been influenced by the exclusion of studies with insufficient data. Additionally, when applied in collaborative learning, AR technologies could have a major influence on learning outcomes, although the results were limited to the pedagogical methods utilized in the included sample (Garzón et al., 2020 ).

The field of education has witnessed a rapid surge in the popularity of augmented reality (AR), which has the potential to greatly enhance learning experiences (Garzón et al., 2019 ). However, the study conducted by Garzón et al. ( 2019 ) neglected to define the specific features of AR that can conveniently assist and improve learning achievements. When compared to traditional learning methods, AR-assisted learning has demonstrated a considerable improvement in learning achievements, and the efficacy of various AR applications in education has shown no significant differences (Ozdemir et al., 2018 ). It is important to note, however, that the sample size in Ozdemir et al.’s study was restricted to only 16 participants and was limited to the Social Sciences Citation Index, resulting in a possible sample bias that could impede the reliability of their results. Learner attitudes toward and learning achievements in AR-assisted education may need further examination since both variables have not received enough exploration.

A meta-analysis of AR-assisted education offers several advantages (Cao and Hsu, 2022 ). Combining the results of multiple studies increases the sample size and statistical power, enabling more accurate and dependable conclusions in AR-assisted education. By analyzing multiple studies together, meta-analysis can identify patterns and trends that may not be apparent in individual studies, indicating the consistency of results across different studies and enhancing the generalizability of findings. Meta-analysis mitigates the impact of bias in individual studies by examining a larger pool of data and reduces the need for replication studies, thereby saving valuable time and resources. It also helps integrate findings with existing theoretical frameworks, providing a more comprehensive understanding of the topic in AR-assisted education. Overall, meta-analysis provides a more robust evidence base for decision-making in policy and practice in AR-assisted education.

The purpose of this meta-analysis is to investigate the impact of Augmented Reality (AR) on educational outcomes while minimizing the aforementioned limitations. We intend to achieve this by incorporating a larger sample size from diverse databases. Our study aims to address the issue of sample bias by expanding the sample size and examining the role of AR features in education. We will include all available studies related to AR, and in cases where adequate information is unavailable, we will reach out to the authors for clarification. Our analysis will also encompass various pedagogical approaches facilitated by AR technologies, with the goal of arriving at comprehensive conclusions regarding attitudes, learning achievements, and motivation.

Literature review

Attitudes toward ar used for education.

The utilization of augmented reality (AR) has been suggested as a means to enhance attitudes towards and satisfaction with education. As reported by Weng et al. ( 2020 ), AR has the potential to induce positive attitudes toward education. Alqarni ( 2021 ) suggests that AR may facilitate positive learning experiences, including academic achievements for students with disabilities. The integration of AR into problem-based learning has also been noted as a promising approach to improving students’ attitudes toward specific subjects (Fidana and Tuncel, 2019 ). Recent research conducted by Sahin and Yilmaz ( 2020 ) found that students who utilized an AR-enhanced science course, specifically “Solar System and Beyond,” exhibited more favorable attitudes toward learning than their non-AR-using peers. Additionally, they reported higher levels of satisfaction and lower levels of anxiety. Delello ( 2014 ) also posits that AR technologies may play a crucial role in improving attitudes toward AR-assisted education.

Despite the potential benefits of AR technology in enhancing attitudes toward education, it is important to acknowledge that some studies have reported negative attitudes toward its use. For instance, Basoglu et al. ( 2018 ) suggest that the use of AR smart glasses (ARSGs) may pose privacy concerns and reduce the perceived ease of use, which can lead to negative attitudes toward AR. Similarly, Akçayır et al. ( 2016 ) assert that students’ lack of familiarity with AR technology can result in frustration and generate negative attitudes toward AR-assisted education. Given the contradictory findings surrounding the impact of AR on attitudes toward education, we propose an alternative hypothesis for further investigation.

H1: The attitudes of learners towards AR-assisted education are significantly more positive compared to those without the aid of AR technologies.

Learning achievements

The majority of studies have reported positive learning outcomes associated with the use of AR technologies. Akçayır and Akçayır ( 2017 ) suggested that utilizing AR technology could enhance learning achievements, foster student engagement, and boost confidence in academic activities. Fidana and Tuncel ( 2019 ) found that integrating AR technologies into problem-based learning approaches resulted in improved learning achievements. Similarly, Sahin and Yilmaz ( 2020 ) reported that students who used AR technologies achieved significantly higher learning outcomes than those who did not. Lee and Hsu ( 2021 ) also demonstrated the efficacy of AR-assisted learning through the “Makeup AR” approach, which enhanced learning achievements, self-efficacy, and reduced cognitive loads. Wu et al. ( 2018 ) further supported the effectiveness of AR-based learning systems, reporting significantly better learning achievements compared to traditional learning methods.

Several studies have reported negative learning outcomes associated with augmented reality (AR) technologies. For instance, Kuhn and Lukowicz ( 2016 ) found that incorporating AR technologies, such as Google Glass, into intelligent classes did not result in significantly higher learning achievements compared to those without AR technologies. Conversely, students who learned using a serious game with AR technologies called Lost in Space demonstrated significantly greater improvements in learning achievements than those who used traditional learning tools, but no significant differences were observed during gameplay (Hou et al., 2021 ). Additionally, AR technologies could potentially have adverse effects on mobile learning achievements, as improper mobile design with AR technologies may lead to frustrating learning outcomes and reduced learning efficiency (Chu, 2014 ; Hwang et al., 2016 ). Given these contradictory results, we propose an alternative hypothesis.

H2. Learning achievements in AR-assisted education exhibit significantly higher results compared to those achieved through non-AR-assisted education.

Motivation of AR technology-assisted learning

Numerous studies have demonstrated that augmented reality (AR) technologies can enhance learning motivation. For example, Cavallo and Laubach ( 2001 ) found that AR technologies could improve learning motivation. Akçayır and Akçayır ( 2017 ) reported that AR technologies motivated students to participate in learning activities. Yildirim ( 2016 ) discovered that students who used computer-based AR technologies were significantly more motivated than the control group who did not use AR technologies. Moreover, Tian et al. ( 2014 ) and Zhang et al. ( 2014 ) indicated that the use of AR technologies in education effectively enhanced students’ motivation. Cen et al. ( 2020 ) observed that a mobile AR-based learning system significantly improved the motivation of secondary chemistry learners. Demitriadou et al. ( 2020 ) suggested that AR technologies were effective in increasing learning motivation.

Despite the positive effects of augmented reality (AR) technologies on learning motivation, some previous studies have shown differing results. For instance, Gómez-García et al. ( 2021 ) found that students who used AR technologies did not exhibit significantly higher learning motivation than those who did not use them. Additionally, Lee and Hsu ( 2021 ) reported that the application of AR in vocational certification courses failed to significantly enhance learning motivation. Furthermore, teachers who resist changing their traditional pedagogical approaches may feel less motivated by AR technologies, which could also dampen students’ motivation for using AR technologies in learning. Similarly, students who are accustomed to traditional learning styles may also exhibit resistance toward AR-assisted learning. Given these implications and inconsistent findings, we propose an alternative hypothesis.

H3. Learning motivation in AR-assisted education shows a substantial increase compared to non-AR-assisted education.

Research methods

This meta-analysis adhered strictly to the protocols outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, as detailed by Page et al. ( 2021 ). PRISMA outlined 27 items that served as a guide throughout the meta-analysis process and provides specific recommendations for conducting a thorough and valid meta-analysis. The ethical committee overseeing this study has granted a waiver for registration, as the study does not involve any human participants and does not violate any ethical criteria.

Eligibility criteria

Following the PRISMA protocol, we established explicit inclusion and exclusion criteria for selecting relevant studies. Inclusion criteria were as follows: (1) large randomized controlled trials that involved AR technology-assisted education and conducted comparative studies; (2) written in English language; and (3) formally and openly published, and peer-reviewed. We excluded studies that (1) focused solely on AR technology without any reference to education; (2) lacked sufficient information for meta-analyses; (3) belonged to the category of review studies; (4) had no relevance to the study topic; (5) were of overall lower quality based on Standards for Reporting on Empirical Social Science Research in AERA Publications; (6) contained insufficient data; (7) had small sample sizes; or (8) yielded unconvincing results.

Search strategy and selection process

The study involved conducting a systematic search of online databases, including Web of Science, Scopus, Wiley, Taylor & Francis, ScienceDirect Elsevier, and SpringerNature, using specific syntactic rules to enter keywords such as “AR, augmented reality, education, control group, experimental group, learning, and teaching”. Prior to the screening, duplicates, records deemed ineligible by automation tools, and those with missing information, small sample sizes, lower quality, lack of sufficient data, or unconvincing conclusions were removed. The selection process was reviewed independently by two researchers, achieving satisfactory inter-rater consistency ( k  = 0.87). In cases of disagreement, a third reviewer was consulted. Ultimately, 28 relevant results were included after screening and excluding ineligible literature (see Fig. 1 ).

A flowchart of the literature inclusion procedure.

Characteristics of the included studies

The present review encompasses studies that showcase the recent accomplishments in AR-assisted education, with publications ranging from 2016 to 2023. The cumulative number of participants in the control group is 1509, while the experimental group consists of 1417 individuals. These studies investigate the comparative effectiveness of AR-assisted and traditional educational approaches in terms of learning achievements, learners’ attitudes, and motivation. All included research articles are published in distinguished journals such as Advances in Physiology Education, Australasian Journal of Educational Technology, Behaviour & Information Technology, British Journal of Educational Technology, Computer Application Engineering Education, Computers & Education, Computers in Human Behavior, Education Sciences, IEEE Transactions on Learning Technologies, Innovation in Language Learning and Teaching, Interactive Learning Environments, International Journal of Human–Computer Interaction, Journal of Baltic Science Education, Journal of Computer Assisted Learning, Journal of Science Education and Technology, and Universal Access in the Information Society (refer to Table 1 ).

Data synthesis

In order to ensure the reliability of our findings, we employed two methods: publication bias testing and sensitivity analyses. Publication bias is a common issue in research, as journals tend to prioritize publishing positive results over negative ones. To detect potential publication bias, we utilized Begg’s (Begg and Mazumdar, 1994 ) and Egger’s tests (Egger et al., 1997 ). We also examined the distribution of individual studies to identify any presence or absence of publication bias. Additionally, we performed sensitivity analyses using Stata/MP 14.0 software to further validate our results.

Begg’s and Egger’s tests are two commonly used statistical methods to assess publication bias in meta-analyses. Begg’s test is a rank correlation test that examines the association between effect sizes and their variances or standard errors. A non-significant p -value (e.g., p  > 0.05) suggests that there is no evidence of publication bias. However, a significant p -value (e.g., p  < 0.05) may indicate the presence of publication bias, but it can also mean that the sample size is too small or the number of studies included in the analysis is too few. Egger’s test is a linear regression test that examines the association between the effect sizes and their precision (the reciprocal of variance). A non-significant p -value (e.g., p  > 0.05) indicates that there is no evidence of publication bias. However, a significant p -value (e.g., p  < 0.05) suggests the presence of publication bias, but it can also mean that the sample size is too small, or there is substantial heterogeneity among the included studies.

The present meta-analysis was conducted using Stata/MP 14.0 software. Firstly, we extracted data pertaining to mean values, standard deviations, and participant numbers across both experimental and control groups. Additionally, subgroups such as learning achievements, attitudes, and motivation in AR-assisted education were also extracted. Effect sizes were then calculated using Cohen’s d formula: d  = Me−Mc/Sp, where Me represents the means of the experimental group, Mc represents the means of the control group, and Sp signifies the pooled standard deviation of both groups (Sedgwick and Marston, 2013 ). We will classify effect size values as very small if they are around 0.1, small if approximately 0.2, medium if roughly 0.5, large if about 0.8, very large if near 1.2, and huge if approaching 2 (Sawilowsky, 2009 ).

The heterogeneity of estimates was assessed by the researchers using I 2 , Q , z , and p values. The degree of heterogeneity was categorized as unimportant if I 2 was <40%, moderate if I 2 was between 30% and 60%, substantial if I 2 was between 50% and 90%, and considerable if it ranged from 75% to 100% (Higgins and Green, 2021 ). We employed a random-effect model for meta-analysis if I 2 was >50%, and a fixed-effect model if I 2 was <50%. In addition to I 2 , Q , z , and p values were also considered in determining the level of heterogeneity.

In cases where a single study produced multiple results, we utilized the Statistics Toolkit (STATTOOLS) to merge participant numbers, means, and standard deviations into a single group (Altman et al., 2000 ). We combined various subgroups such as attitudes (Alqarni, 2021 ; Fidana and Tuncel, 2019 ; Sahin and Yilmaz, 2020 ), attractiveness (Albrecht et al., 2013 ), learning interest (Chin and Wang, 2021 ), satisfaction (Huang et al., 2021 ; Ucar et al., 2017 ; Wu et al., 2018 ), and self-efficacy (Lee and Hsu, 2021 ) under the “attitudes” category. The “learning achievements” subgroup included test scores (e.g. Gonzalez et al., 2020 ), academic achievement, academic averages (Selek and Kiymaz, 2020 ), evaluation scores (Gargrish et al., 2021 ), final exam scores (Gonzalez et al., 2020 ), grades of work, financial knowledge (Candra Sari et al., 2021 ), learning outcomes (Stojanović et al., 2020 ), learning performance (Hanafi et al., 2016 ), the mathematical calculation (Ruiz-Ariza et al., 2018 ), operational effectiveness (Mao and Chen, 2021 ), spatial perception skills (Carbonell Carrera and Bermejo Asensio, 2017 ), test and quiz scores (Christopoulos et al., 2021 ), visualization skills (Omar et al., 2019 ), and writing skills (Wang, 2017a ). The “motivation” subgroup focused on learning motivation (Chang et al., 2016 ; Chu et al., 2019 ; Gómez-García et al., 2021 ; Lee and Hsu, 2021 ; Christopoulos et al., 2021 ). The included studies utilized AR technologies in education as the treatment.

If multiple experimental groups were used, preference would be given to the group that was most closely associated with the use of augmented reality (AR). Among the experimental groups that utilized AR, priority would be given to the group that had the most stringent design and provided the most compelling results. When selecting a control group, the one that could provide the most informative comparative results with the experimental group would be selected. In studies where pre- and post-tests were conducted to compare control and experimental groups, data from the post-tests that underwent the treatment would be retrieved.

The sample size, methodological quality, and age of participants can all contribute to the variability of effects observed in a meta-analysis. Larger sample sizes generally lead to more precise estimates of effect size with less variance. Small samples may have greater variability due to sampling error. Studies that are well-designed and implemented with appropriate controls tend to produce more reliable and valid results. Poorly designed studies with bias or confounding factors can produce less trustworthy outcomes and introduce heterogeneity in the meta-analysis. Studies that include participants from different age groups may lead to variations in treatment effects. For example, an intervention may work better for younger individuals but not as well for older populations. Therefore, in this meta-analysis, differences in sample size, methodological quality, and age of participants across studies may have negatively influenced the generalizability of the results.

Testing for hypotheses

H1. The attitudes of learners towards AR-assisted education are significantly more positive compared to those without the aid of AR technologies .

In a random-effect model, the variance is assumed to consist of two components: within-group variation and between-group variation. The group-specific effects are considered random variables that follow a normal distribution with a mean zero and a certain variance. In contrast, a fixed-effect model assumes that each group has its own fixed effect, which is not normally distributed. The interpretation of results from a random-effect model is usually more generalizable than from a fixed-effect model since it accounts for both within-group and between-group variation. However, a random-effect model may have less statistical power than a fixed-effect model when there are only a few groups or when the within-group variability is small. Therefore, the choice between the two models depends on the research question and the specific data characteristics.

The effect model used for conducting the meta-analysis was determined based on the level of heterogeneity. The observed variances in study outcomes across studies were attributed to heterogeneity rather than random errors, specifically in relation to attitudes towards AR-assisted education (indicated by Q  = 171.78, I 2  = 94.2, p  < 0.01 in Table 2 ). As a result, random-effect models were employed to analyze attitudes within the context of AR-assisted education using meta-analytic techniques.

A forest plot was generated using Stata/MP 14.0 software to test the alternative hypotheses (Fig. 2 ). The plot included 11 effect sizes, with individual studies represented by dots in the middle column and the horizontal line indicating 95% confidence intervals. The no-effect line was represented by the middle line, while the diamond at the bottom indicated the pooled result. If the horizontal line or diamond crossed the no-effect line, it suggested non-significant differences. The diamond was located to the right of the middle line, indicating a significantly more favorable attitude in the experimental group compared to the control ( d  = 1.08, 95% CI = 0.44–1.72, z  = 3.32, p  = 0.001 in Table 2 ).

A forest plot of differences in attitudes between control and experimental groups.

To test for publication bias, a funnel plot was created using the same software. Figure 3 shows symmetrically distributed dots along both sides of the middle line, suggesting the absence of publication bias ( z  = 1.63, p  = 0.102 through Begg’s test in Table 3 ). Therefore, researchers accept the first alternative hypotheses.

A funnel plot of publication bias in attitudes.

H2. Learning achievements in AR-assisted education exhibit significantly higher results compared to those achieved through non-AR-assisted education .

In terms of learning achievements, the estimations yielded significant heterogeneity ( Q  = 281.66, p  < 0.01, I 2  = 92.5 in Table 2 ), prompting the researchers to employ a random-effect model for the meta-analysis. The results indicated a significant difference between the experimental and control groups, with the former achieving significantly higher learning outcomes ( d  = 0.85, 95% CI = 0.47–1.22, z  = 4.37, p  < 0.01 in Table 2 and Fig. 4 ). Additionally, there was no indication of publication bias in the data according to the funnel plot analysis (Fig. 5 ) and Begg’s test ( z  = 1.75, p  = 0.08 in Table 3 ), thus leading the researchers to accept the second alternative hypothesis.

A forest plot of differences in learning achievements between control and experimental groups.

A funnel plot of publication bias in learning achievements.

H3. Learning motivation in AR-assisted education shows a substantial increase compared to non-AR-assisted education .

In order to test the alternate hypothesis, researchers utilized a random-effects model for conducting meta-analysis due to significant heterogeneity in estimates ( Q  = 12.52, p  = 0.028, I 2  = 60.1). A forest plot (Fig. 6 ) was created which showed that the pooled estimate of motivation, represented by the diamond, intersected with the no-effect line, indicating no significant difference in motivation between the two groups ( d  = 0.85, 95% CI = 0.47–1.22, z  = 4.37, p  < 0.01 in Table 2 and Fig. 6 ). Additionally, results from Begg’s test ( z  = 1.13, p  = 0.26) and Egger’s test ( z  = 1.18, p  = 0.302 in Table 3 ) depicted symmetric distribution of dots on either side of the middle line in Fig. 7 , thereby indicating no presence of publication bias. Consequently, the third alternative hypothesis was rejected by the researchers.

A forest plot of differences in motivation between control and experimental groups.

A funnel plot of publication bias in motivation.

In order to verify the reliability of our estimate results, we performed sensitivity analyses using the Stata/MP 14.0 program by entering the command “metaninf N M SD N0 M0 SD0, random cohen”. The results are presented in Fig. 8 , where each dot represents an individual study, while the middle line displays the effect size and the lines on both sides represent the upper and lower confidence interval limits. All of the dots fall within the given confidence interval limits when a particular study is excluded. We conducted separate sensitivity analyses for attitudes, learning achievements, and motivation, and obtained the same results, indicating that the overall and separate estimates of our study are reliable and robust. The final results are summarized in Table 4 .

Results of the sensitivity analysis.

Attitudes toward AR for educational purposes

It can be concluded that students exhibit more favorable attitudes towards AR-assisted education than traditional education. Implementing AR technologies in education has the potential to generate excitement and interest among learners, leading to positive attitudes toward AR-assisted learning. This is especially true for those who experience AR technologies for the first time, as they may find the technology curious and even magical (Sahin and Yilmaz, 2020 ; Akram et al., 2021 ). AR technologies have three dimensions that provide students with a more tangible and authentic learning experience, ultimately enhancing learning effectiveness (Wojciechowski and Cellary, 2013 ). AR technologies capture students’ attention, increase their engagement, and immerse them in educational activities, leading to positive attitudes toward AR-assisted education (Perez-Lopez and Contero, 2013 ). Positive attitudes towards AR-assisted education are closely linked to learning achievements in AR contexts (Sahin and Yilmaz, 2020 ). This positive correlation may further reinforce positive attitudes as students’ learning achievements significantly improve when compared to those achieved through traditional learning.

It is reasonable to expect that AR-assisted education can result in significantly higher learning achievements compared to traditional education. The multi-dimensional scaffolding functions of AR technologies may offer novel experiences and stimulate students to participate in the learning process, thereby enhancing their learning achievements (Gilliam et al., 2017 ). AR-assisted learning may also foster students’ curiosity, which can increase their cognitive effort and improve their learning achievements (Kuhn and Lukowicz, 2016 ). Strong curiosity may help students focus on learning content and reduce distractions, leading to improved learning outcomes. In AR-assisted contexts, students typically experience lower cognitive loads than those without the use of AR technologies and also report higher levels of satisfaction (Wu et al., 2018 ). This may further contribute to improved learning achievements facilitated by AR technologies.

Although this study did not find a significant difference in motivation levels between AR-assisted education and traditional methods, it is reasonable to expect such a difference based on the potential benefits of AR technologies. The remarkable functions of AR technologies may encourage students to engage in simulated learning activities and associate virtual with real learning environments (Abdullah, 2022 ), leading to increased learning motivation and the development of positive attitudes towards learning (Tian et al., 2014 ). Students tend to enjoy using AR technologies in their learning, finding them easy and convenient to use, and they report high satisfaction with their AR-assisted learning experiences (Ozarslan, 2013 ), which can reduce their learning anxiety compared to traditional learning (Tomi and Rambli, 2013 ; Al-Ansi, 2021 ). Thus, students are motivated to continue using AR technologies to enhance their learning experiences. Lee and Hsu’s ( 2021 ) failure to detect significant differences in motivation levels might be due to the short duration of their experiment, poor Internet connection, or the use of small smartphones that could hinder students’ ability to effectively utilize AR technologies.

Major findings

The results of this study are in line with previous research (e.g. Christopoulos et al., 2021 ; Carbonell Carrera and Bermejo Asensio, 2017 ), indicating that AR-assisted education generates more positive attitudes among learners and leads to higher learning achievements compared to traditional methods. However, the study did not observe any significant differences in motivation levels between AR-assisted education and non-AR-assisted education. The study authors explored several explanations for this unexpected finding.

Limitations

This study has several limitations. Firstly, due to constraints in the availability of library resources, it was not possible to access all relevant literature. Secondly, Begg’s and Egger’s tests indicate that publication bias exists regarding learning achievements in AR-assisted education, which may reduce the reliability of the findings. Additionally, the variability of research contexts makes it challenging to fully summarize the effects of AR technologies on educational outcomes.

Future research directions

Other factors, such as learning styles and learner personality, may also significantly impact the effects of AR technologies on educational outcomes. Future research could incorporate a more comprehensive range of influencing factors. Additionally, future studies could explore the differences between the application of mobile and static AR technologies in educational contexts (Lee and Hsu, 2021 ). Researchers should also consider the impact of technostress, interaction, affection, cognition, and telepresence on AR-assisted learning experiences and achievements (Baabdullah et al., 2022 ). Furthermore, studies could focus on the effects of AR on learners’ spatial ability (Di and Zheng, 2022 ).

Data availability

The datasets generated during and/or analyzed during the current study are openly at https://osf.io/jfwb2/?view_only=872843fa65cf4d35b35afb7214b793b9 .

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The authors extend gratitude for funding support from the following: Shan Dong Humanities and Social Sciences Project in 2022 (Grant No: 2022-JCJY-09): A Study on English College Instructors' Leadership in China, funded by Shandong Federation of Social Sciences; 2019 MOOC of Beijing Language and Culture University (MOOC201902) (Important) “Introduction to Linguistics”; “Introduction to Linguistics” of online and offline mixed courses in Beijing Language and Culture University in 2020; Special fund of Beijing Co-construction Project-Research and reform of the “Undergraduate Teaching Reform and Innovation Project” of Beijing higher education in 2020-innovative “multilingual +” excellent talent training system (202010032003); the research project of Graduate Students of Beijing Language and Culture University “Xi Jinping: The Governance of China” (SJTS202108).

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Cao, W., Yu, Z. The impact of augmented reality on student attitudes, motivation, and learning achievements—a meta-analysis (2016–2023). Humanit Soc Sci Commun 10 , 352 (2023). https://doi.org/10.1057/s41599-023-01852-2

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Home > Books > Augmented Reality and Its Application

Augmented Reality Research and Applications in Education

Submitted: 08 July 2021 Reviewed: 09 July 2021 Published: 24 August 2021

DOI: 10.5772/intechopen.99356

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Augmented reality is defined as the technology in which virtual objects are blended with the real world and also interact with each other. Although augmented reality applications are used in many areas, the most important of these areas is the field of education. AR technology allows the combination of real objects and virtual information in order to increase students’ interaction with physical environments and facilitate their learning. Developing technology enables students to learn complex topics in a fun and easy way through virtual reality devices. Students interact with objects in the virtual environment and can learn more about it. For example; by organizing digital tours to a museum or zoo in a completely different country, lessons can be taught in the company of a teacher as if they were there at that moment. In the light of all these, this study is a compilation study. In this context, augmented reality technologies were introduced and attention was drawn to their use in different fields of education with their examples. As a suggestion at the end of the study, it was emphasized that the prepared sections should be carefully read by the educators and put into practice in their lessons. In addition it was also pointed out that it should be preferred in order to communicate effectively with students by interacting in real time, especially during the pandemic process.

• augmented reality research and applications
• field of education
• pandemic process
• digital transformation
• virtual environment

Author Information

Ezgi pelin yildiz *.

• Department of Computer Programming, Kazim Karabekir Vocational School of Technical Sciences, Kafkas University, Kars, Turkey

*Address all correspondence to: [email protected]

1. Introduction

Today, rapid changes and advances in science and technology affect and change the lifestyle of individuals. Apart from individuals, it is not possible for the education process and educational environments not to be affected by this change [ 1 ]. When the technologies used in educational environments from the past to the present are examined, it is seen that there is a transformation from blackboard and chalk to the computer and internet world, even to smart technologies with artificial intelligence. Especially in recent years, computer and internet technologies have had such a wide area of use in our lives that it was unthinkable for education services to be left out of the field [ 2 ].

The definition of today’s learners as Z generation and/or digital generation and their characteristics require educators to follow technological developments and use the most appropriate technological tools in learning environments. One of these new technologies is augmented reality applications in education. When the literature is examined, there are many definitions of the concept of augmented reality made by researchers. Some of these definitions:

Augmented reality according to Milgram and Kishino [ 3 ]; “it is a reality environment where digital media products are used instead of real world objects” appears to be the most general definition. According to Azuma [ 4 ], augmented reality is a derivative of virtual reality. According to this definition, augmented reality is virtual environments in which existing reality is supported, not created from scratch. In this context virtual and real objects in augmented reality environments offered to users in harmony. Augmented reality creates the interactive environment between the virtual and real world. Augmented reality is used to achieve this [ 5 , 6 ]. When the definitions in the literature are examined, as a common definition; augmented reality can be defined as real worlds enriched using virtual objects.

Game and Video

Art and Museums

Device Maintenance/Support

With the rapid development of Augmented Reality applications day by day, usage areas in many sectors are starting to increase. Major brands have started to give importance to providing a more realistic and embodied experience to their customers by using Augmented Reality (AR). This technology, which appears in many fields such as cosmetics, automobiles, construction, food, combines the virtual world with real life. Identifying target audiences, tracking and using technology in brand awareness and sustainable marketing is now vital for companies. The most importantly, companies from the public or private sector invest on enhanced technology in order to better promote or market their services/products and need talented people/firms in this field. In this context, augmented reality applications offer these services to businesses with technology support.

to provide students with more flexible and interesting learning environments,

to experience an excitement they have never experienced before,

to increase their willingness and motivation to learn,

to help students make active observations during their learning processes and to form hypotheses as a result of these observations,

to increasing students’ learning performance and helping them establish social interactions within the group,

to bridging formal and informal learning and encouraging students to learn collaboratively,

AR technology; it gives a feeling of independence from the place, freedom and personal,

to creating new opportunities in education by promoting learning.

it is possible to rank as.

When the augmented reality technologies, which are frequently used in the field of education, are examined, wearable technologies draw attention. Wearables are loaded with smart sensors that track body movements. Usually these products use bluetooth, Wi-Fi and mobile internet connection to sync with smartphone wirelessly. Users are connected to wearable devices with the help of sensors. Wearable technology products that are always with the user; it provides important services in many areas, especially in entertainment, health, work, information, education, socialization and security.

Wearable technologies in the field of education are used in learning-teaching environments. Modern visualization techniques help students explore existing educational resources and new knowledge ( Figure 1 ) [ 12 ].

Wearable technologies the past and present and future.

Internet of things

Smart watches

Google – Glass Project

HoloLens – Microsoft:

Oculus Rift – Facebook

Bracelets, Rings and Necklaces

Smart Clothing and Tattoos

These tools, which can also be named as wearable computers in the literature, reveal a commensalistic relationship between human and computer however, the daily life of the individual has a structure that enriches their experience [ 13 ]. From smart watches to wristbands, sensor accessories such as rings and necklaces, virtual reality glasses, Google Glass project and derivative smart glasses, as well as smart optical lenses and headphones, many things can be shown among wearable technologies [ 14 ].

Augment – 3B

Google Translate

LifePrint Photos

In the light of all this information, the purpose of this chapter; the use of augmented reality environments and applications in the field of education, the programs and technologies used in this context, and the researches are discussed in detail.

The new normal situation, especially with the pandemic process, also creates an opportunity for more educators to try new generation technologies (VR and AR technologies) beyond video and teleconferencing applications. It is predicted that such research studies will be important so that educators realize the benefits of these technologies and use them actively in learning environments.

2. Conceptual framework

Augmented reality (AR) has been slowly but surely following its predecessor virtual reality in changing the education sector—digitizing classroom learning, and making training more diverse and interactive. In this section, current studies in the literature in recent years on the integration of augmented reality applications into education are given. When these studies are examined;

Çetin [ 15 ], investigated the effect of augmented reality-based stories on reading skills in his research. In the research, augmented reality based story text samples were presented to primary school 3rd grade students ( Figure 2 ).

Augmented reality based story text samples.

A scoring key was developed for the answers given to the questions prepared by the researcher to measure the skills of expressing what they read in writing. As a result of the research, it was observed that the augmented reality-based stories did not have a significant effect on the reading motivation and reading comprehension skill levels of the students, but they created a positive significant difference on their ability to tell what they read in written and verbal form. In addition, as a result of the research, it was observed that the reactions of the students towards the texts increased.

As a similar study Baysan and Uluyol [ 16 ], the effect of the use of augmented reality books (AR-books) on the academic success of the students and the students’ opinions about the environment were investigated in his study. The AR-based teaching material developed by the HITLibHZ-BuildAR program was used in the laboratory environment for the experimental group of 22 people and the course was taught by the researcher. As a result; according to the qualitative data obtained from the students, AR is a promising technology. Educational AR applications should be used in areas that require 3D spatial visualization such as Geometry and Geography rather than technology education. Participants support the use of AR in Computer Hardware training, with better developed platforms and more professional designs ( Figure 3 ).

Augmented reality application book sample.

Almusawi et al. [ 17 ], in their study, they discussed innovation in physical education: teachers’ perspectives on readiness for wearable technology integration. The study is a case study and includes semi-structured interviews with 38 public school physical education teachers. The following scheme was used in the study ( Figure 4 ).

The findings show that physical education teachers have concerns about the design aspects of wearable technologies in terms of material design and device suitability for physical education. To eliminate these concerns, it is proposed to provide innovative learning environments that impact technology through collaborative, competitive, engaging and evidence-based learning experiences through wearable technologies that provide comfort, enhanced wearability and injury prevention in physical education.

It is understood from the existence of studies in the literature that augmented reality technologies have been used frequently in medical education recently. When the relevant studies in the literature are examined ( Figure 5 ).

Use of augmented reality technologies in medical education.

Kucuk et al. [ 18 ], a new perspective in medical education multimedia applications: augmented reality has been studied in their research. As a result, it is difficult to understand the subjects including the structure of the brain and vessels such as neuroanatomy in medical courses, in this direction, it was emphasized that AR applications could be developed to facilitate the learning processes of students in such subjects. Considering the characteristics of today’s students in the digital citizen group, it has been suggested in the study that students should be supported with various technological solutions in this process, at this point, the dissemination of medical augmented reality applications that are based on the learning approach anytime and anywhere and support individual learning.

3. Augmented reality applications used in education

Augmented reality, a concept that has been frequently encountered recently, promises a future where we can get away from the world we live in, create a new worlds and enter ‘inside’ our imagination. By adding this technology with which we can ‘beautify’ the world we live in, make brand new additions to our world and bring our imagination to the place we live in, we started to manipulate our real world at the same time, while constructing mixed reality virtual worlds that we use together. It has become compulsory to benefit from these privileges and advantages that augmented reality offers to our lives, especially in terms of education, on behalf of the Z generation youth.

It is now possible to use these technologies in learning and teaching environments by making use of the ready-made programs of augmented reality. When the literature is examined, the frequently used programs and application areas are below:

3.1 Augment: 3B

Augment is an ARCore-based mobile app to visualize 3D models in Augmented Reality, integrated in real time in their actual size and environment. Balak and Kısa [ 19 ] investigated the effects of this application on technical drawing education in their studies. The data obtained as a result of the use of Augmented Reality technology in the technical drawing course of the 2015–2016 period were examined. As a result; the result of the survey made with the pre- and post-tests applied; it has been determined that the students understand and adopt the Augmented Reality technology, which is a modern education tool, and this technology increases their interest in the lesson ( Figure 6 ).

Technical drawing with 3D modeling with AR technologies.

3.2 Google translate

According to Google, the Translate app currently supports text translations between 103 languages, offline translations for 52 languages and Word Lens-based augmented reality translations for 30 languages. Aiming to make life easier for users with its mobile translation application, Google offers Instant camera translation; It started to support a total of 88 languages with the addition of 60 new languages such as Arabic, Hindi, Malaysian, Thai and Vietnamese etc. ( Figure 7 ).

Augmented reality-based Google translate app.

3.3 SketchAR

SketchAR, which is an application that combines augmented reality and drawing, is among the applications frequently preferred by artists recently. SketchAR, which is basically a drawing application made available to artists, confirms that digital works created by artists are unique and original, making them accepted as NFT (data unit). SketchAR, an initiative founded in 2017 by Aleksandr Danilin, Alexander Danilin and Andrey Drobitko in Lithuania, offers its users a different drawing experience by combining augmented reality technology with drawing, together with artificial intelligence support ( Figure 8 ).

Drawing courses with SketchAR.

3.4 Wikitude

Wikitude initially focused on providing location-based augmented reality experiences through the Wikitude World Browser App. In 2012, the company restructured its proposition by launching the Wikitude SDK, a development framework utilizing image recognition and tracking, and geolocation technologies. Wikitude initially entered the market with its geo location AR app. The Wikitude app was the first publicly available application that used a location-based approach to augmented reality ( Figure 9 ).

Wikitude world browser app.

It is supported by studies in the literature that this application is also used in geography education. Wikitude; it is a complete AR development platform used by major brands, travel catalogs, retailers and publishers to deliver a variety of engaging solutions.

3.5 LifePrint photos

Life Print is an Android and iPhone photo and video printer. The Life Print program uses augmented reality to magically bring photos to life ( Figure 10 ).

Augmented reality app: LifePrint photos.

3.6 Smartify

The application starts with permission from users to access camera and location. With camera access, the artwork is scanned, and according to the location, it provides the opportunity to get information about which museums are and how far, how many artworks of art they are, open and closed hours, and to see some of the artworks in the museum. The application has three basic directions; scan , profile and explore ( Figure 11 ).

Augmented reality app: Smartify.

3.7 Spyglass

Spyglass app is a program that allows users to turn their smartphones into a compass, gyroscope, star tracker and more ( Figure 12 ).

Locating with spyglass technologies.

3.8 Blippar

Blippar uses augmented reality, artificial intelligence and computer vision to provide you with information about what you find around you. It is quite successful with its advanced image recognition algorithms that find out what the objects are and bring the relevant information. Blippar will introduce the feature that will allow its users to create their own profiles very soon, but it will be possible to get detailed information about a person with the innovation called Augmented Reality Face Profiles ( Figure 13 ).

Unlock augmented reality of everyday objects and places with the Blippar app.

3.9 Aurasma

by creating animated and interactive boards

prepare interactive lecture notes or handouts

interactive presentation of albums or details about activities such as observation projects, experiments ( Figure 14 ).

Educational use of Aurasma app.

According to Onder [ 21 ], the Aurasma application draws attention with its ability to provide AR environments and opportunities to teachers and students, ease of use, support for distance education, creating individualized learning environments and being used as an evaluation tool.

This research is an example of a literature review. A literature review is a search and evaluation of the available literature in your given subject or chosen topic area [ 22 ]. At the end of the study, it was emphasized that the prepared sections should be carefully read by the educators and put into practice in their lessons. In addition it was also pointed out that it should be preferred in order to communicate effectively with students by interacting in real time, especially during the pandemic process.

5. Conclusion and suggestions

In this research, a detailed analysis of the augmented reality environments and applications that are frequently used in the design of learning and teaching environments in the education sector with the digitalization process is included. As the general results of the research; today, with the introduction of technologies into educational environments, different tools and materials have begun to be used in teaching methods. In this context, it is seen that the inclusion of mobile tools and mobile applications in learning environments has become widespread recently. With this rapid development in mobile technologies, new media environments, in which interactivity increases, offer an increasing number of services to the user. One of the environments where this interaction is provided and which can integrate objects in virtual environments with real objects is technologies that offer “Augmented Reality (AR)”. These technologies allow virtual objects to be superimposed on real images. AR tools consist of camera, computer infrastructure, a marker and tangible objects.

One of the most important sectors in which augmented reality technologies are used is the education area. Augmented reality applications help students understand abstract concepts in the learning and teaching process; it provides environments where students can share information within the group. In addition, it has been supported by studies in the literature that these environments significantly increase students’ learning. In addition, it was emphasized that augmented reality increases the interests, motivations and experiences of students in the field of education and plays a role in transferring the knowledge and skills gained in the virtual environment to real environments.

In all this context; increasing the use of learning environments of augmented reality environments and applications, where the effectiveness of its use in education has been determined to this degree, in different levels and course contents is the most important suggestions of this research.

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