Next Article in Journal
Bidding Evaluation and Contractor Selection Using Balance Index Model and Comprehensive Input Efficiency Based on Data Envelopment Analysis
Next Article in Special Issue
Exploring the Potential of Mixed Reality in Enhancing Student Learning Experience and Academic Performance: An Empirical Study
Previous Article in Journal
Input Efficiency Measurement and Improvement Strategies of New Infrastructure under High-Quality Development
Previous Article in Special Issue
Advanced Dance Choreography System Using Bidirectional LSTMs
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Exploring the Benefits and Drawbacks of AR and VR Technologies for Learners of Mathematics: Recent Developments

1
Faculty of Education, University of Hamburg, Von-Melle-Park 8, 20146 Hamburg, Germany
2
Faculty of Education and Arts, Nord University, 8049 Bodø, Norway
*
Author to whom correspondence should be addressed.
Systems 2023, 11(5), 244; https://doi.org/10.3390/systems11050244
Submission received: 13 April 2023 / Revised: 5 May 2023 / Accepted: 11 May 2023 / Published: 14 May 2023

Abstract

:
Despite the growing interest in the field, the overall impact of augmented reality (AR) and virtual reality (VR) on mathematics learning remains unclear, with previous studies reporting mixed results. Moreover, to date, no systematic review has evaluated the potential of AR/VR in mathematics education, including its benefits and drawbacks for learners. To address this gap, the present systematic literature review aims to identify research trends, determine characteristics and methodologies, and explore the potential benefits and drawbacks of AR/VR technologies in mathematics learning based on existing empirical studies. In accordance with the PRISMA guidelines, we analyzed 59 peer-reviewed journal articles published in English that focused on AR/VR implementation in mathematics education. The review determined that geometry was the most widely studied topic of mathematics, with several studies focusing on the use of AR/VR to assist students with learning disabilities. The present review offers evidence for the potential of AR/VR potential in consolidating learners’ socio-emotional, cognitive/meta-cognitive, and pedagogical development in mathematics learning. Nevertheless, a few issues, including technological glitches, cost, start-up effort, health issues, and unfamiliarity with AR/VR, pose challenges to the successful application of AR/VR in the classroom. This systematic review contributes to the existing body of knowledge in the field and recommends avenues for future research.

1. Introduction

The use of new technologies in education has become increasingly popular in recent years with the rise of augmented reality (AR) and virtual reality (VR) technologies, which promise to enhance students’ learning process [1]. These nascent technologies can produce highly realistic representations as well as allowing subjects to interact with virtual objects. These effects are amplified when AR and VR are combined, offering multiple perspectives to learners [2]. VR technologies allow learners to access a virtual world, actively immerse themselves in it, and interact with objects, thereby enhancing their mathematical thinking skills and spatial abilities [3]. Moreover, AR technologies allow learners to work with objects in the real world, with the opportunity to explore their features and manipulate them without requiring them to become disconnected from reality [4,5].
AR/VR technologies have witnessed significant advancements in recent years and have the potential to revolutionize various fields, including engineering [6], medicine [7], tourism [8], industry [9], entertainment and gaming [10], and education [11]. Moreover, the use of AR and VR technologies in the educational landscape is expected to become more widespread in the near future [12,13,14,15]. In particular, the use of AR/VR in the field of mathematics education has attracted considerable attention in recent years as a useful tool to enhance learning motivation and student outcomes [16]. However, previous studies have yielded mixed results regarding the effects of AR/VR technologies on students’ mathematical learning processes [16,17]. On the one hand, the integration of AR and VR applications into mathematics education has the potential to consolidate students’ understanding of mathematical concepts and boost their learning motivation and spatial abilities [18,19,20,21,22]. On the other hand, negative attitudes toward AR and VR may generate unfavorable learning outcomes [23], and the mathematics learning process may be negatively impacted by the occurrence of negative side effects (e.g., headaches and eye strain) that may manifest after working in virtual environments [3]. Learning modes, curriculum design [24], culture, and learner characteristics [25] may influence the effectiveness of AR and VR technologies for students’ mathematics learning. To summarize, these findings indicate that the extent to which AR/VR technologies can enhance mathematics learning has yet to be conclusively determined, and, thus, a more thorough and systematic examination of the existing literature is warranted to help ensure that the recent developments and research trends, the role of AR/VR in mathematics education, and the successful implementation of these technologies are guided by empirical evidence rather than hype and speculation [26].
In light of the above-mentioned research gap, the present systematic literature review will focus on existing empirical studies—in particular, those pertaining to the overall role that AR/VR technology plays in students’ mathematics learning, including its benefits and drawbacks for learners. Moreover, research is included which explores the extent to which achievement outcomes are examined and which has identified ways to optimize the use of AR/VR, considering its benefits and drawbacks for users to support effective mathematics learning processes. The present literature review also reports research trends (e.g., publication years, geographical distributions, study contexts and domains, methodological bases of the studies, and distribution of the AR and VR studies) and the most popular digital tools used in the examined studies. Overall, this comprehensive systematic review will inform successful and sustainable design and practices in AR/VR-based mathematics education and help guide future research in this field by identifying key knowledge gaps.
The study is guided by the following research questions:
  • What are the research trends and overall characteristics of studies concerning the use of AR/VR technologies in mathematics learning?
    • How have the reviewed studies developed over time?
    • How are the authors of studies distributed geographically?
    • What are the study domains of the reviewed studies?
    • What are the methodological bases of the reviewed studies?
    • What research trends emerge in relation to the use of AR/VR in mathematics learning?
  • Which digital tools (software and hardware) are used in the reviewed studies on AR and VR research in mathematics education?
  • What potential benefits do AR and VR technologies offer for mathematics learning?
    • What are the potential benefits of AR and VR technologies for mathematics learners?
    • What are the potential drawbacks of AR and VR technologies for mathematics learners?

2. Background

2.1. Conceptualization of AR and VR Technology

While AR and VR technologies are closely related, they offer different approaches to interacting with reality and virtuality. While AR technologies overlay virtual information onto the real world and allow users to interact with both real and virtual content, VR technologies transport the user to a virtual environment with the aim of fully immersing them in that world [27,28]. Mixed reality (MR) blends both types of interaction within a single object. Milgram and Kishino [28] first proposed the reality–virtuality continuum—a central model for understanding AR/VR that introduced the MR construct. Their model proposed an approach to categorizing different MR display systems based on a taxonomy of key factors (see Figure 1). AR and VR may be viewed as lying at opposite ends of the reality–virtuality continuum [2]. For the user, the difference lies in the level of immersion [8]: in AR, the perspective of the user remains primarily that of the real world, while in VR, the user is wholly immersed in a virtual environment.
Researchers have highlighted several key features that characterize AR and VR technologies. According to Azuma [27], AR enhances the real-world view by overlaying or blending virtual objects with it, rather than replacing it entirely, with the aim of creating a seamless coexistence of real and virtual objects within the same space, giving the user the impression that the virtual objects are supplementing reality. Azuma et al. [29] describe the three main defining characteristics of AR systems as follows: (a) they generally involve the seamless integration of virtual and real-world elements; (b) they provide real-time interactivity; and (c) they accurately align and register 3D objects. Yung and Khoo-Lattimore [8] emphasized the three crucial constituents of VR as follows: first, visualization enables the user to explore the virtual environment by looking around, often facilitated by a head-mounted display; second, immersion involves the creation of a convincing virtual world that suspends the disbelief of users and provides realistic representations of objects; and third, interactivity measures the level of user engagement with the virtual environment and is often achieved through the use of sensors and input devices, such as joysticks or keyboards.

2.2. Previous Reviews of AR/VR in Mathematics Education

Previous literature reviews pertaining to AR/VR in education have primarily focused on either the use of AR in STEM education (e.g., [30]) or in general educational sciences (e.g., [12,31]), with few systematic reviews assessing the combined effectiveness of AR and VR for mathematics education. While several reviews have focused solely on the use of AR in mathematics education, to the best of our knowledge, no systematic review to date has evaluated the combined impact of AR and VR technologies in mathematics learning processes. Our search of the literature revealed several systematic review studies that were exclusively on the use of AR in mathematics education [16,17]. Ahmad and Junaini [16] used SCOPUS as a database and recruited 19 journal articles published between 2015 and 2019. Palanci and Turan [17] focused on the methodological trends of studies using AR in mathematics education, reviewing 86 studies (i.e., conference proceedings and journal articles) sourced from the Web of Science (WoS) database. These reviews focused exclusively on AR technology (omitting VR) and offered no comprehensive analysis or discussion of the effectiveness of both AR and VR technologies on mathematics learning from various perspectives (e.g., cognitive, affective, socio-emotional, psychological, and attitudinal outcomes). However, they reported several common benefits and difficulties associated with the use of AR in mathematics education. Accordingly, the most frequently mentioned opportunities offered by AR for students include improvements in learning motivation and confidence as well as enhanced learning through visualization, spatial abilities, and interactive engagement. The reviews also revealed that the use of AR technology is associated with problems in mathematics learning, such as difficulties in creating visualizations and understanding mathematics concepts visually, as well as technical problems and cost.
A recent scoping review [32] referred to AR and VR collectively as “extended reality” (XR). The study aimed to explore the existing research on XR, with a particular focus on the pedagogical implications of immersive extended realities in the context of teaching and learning engineering mathematics. Although Lai and Cheong [32] presented a framework for implementation of the XR technology, the available evidence in support of the impact of AR/VR in mathematics learning is limited.
Consequently, the discernible lack of research in the realm of mathematics education regarding the collective influence of AR/VR accentuates the burgeoning demand for comprehensive systematic reviews on this topic. The present study is well-equipped to address this requirement and provide a timely exploration of the potential benefits and drawbacks of both AR and VR technologies in mathematics education.

3. Materials and Methods

The present systematic review aims to understand the value of AR/VR technology, focusing on its benefits and drawbacks in the context of mathematics learning. The review promises to generate broad conclusions regarding the merit of focused conceptualizations, approaches, and applications in the field of AR/VR by identifying research trends and presenting interpretable patterns [33,34]. We adhere to the “referred reporting items for systematic reviews and meta-analyses” (PRISMA) guidelines [26] to enhance the trustworthiness and transparency of the review with respect to the selection of the studies and report synthesis. In light of the rapid development of technology, we have aimed to explore the most recent research on learning mathematics with AR/VR with a focus on empirical research articles. The literature search was conducted in August 2022 using two well-known electronic databases (i.e., WoS and SCOPUS), and we applied the following search strings with Boolean logic: “Title (augmented reality OR virtual reality) AND Abstract (math*).”
The electronic search yielded 740 records at the identification stage. MS Excel and EndNote X9 software were employed to organize and manage the identified records, and 60 duplicated records were discarded through EndNote X9. At the screening stage, we followed five manuscript selection criteria: (a) document type: the study was published in a peer-reviewed journal and presented empirical data; (b) language: the study was written in English; (c) publication year: the study is quite recent and incorporates most recent technological developments—we therefore restricted the publication interval to the last five years (2018–2022); (d) domain: the study was carried out in the field of mathematics education; and (e) research focus: the study provided empirical results on the benefits or drawbacks of AR/VR technology for mathematics learners. Based on these criteria, we screened the titles, abstracts, and keywords of 680 studies, and then examined the full texts of 151 papers. In the final step, the eligibility check ensured the inclusion of 59 papers in the present systematic review (see Figure 2).
Analyses of the 59 papers (see Table 6 in Section 5) were conducted separately by the first two authors, and the main focus was particularly on the role of AR/VR technologies and answering the developed research questions. We screened the eligible papers several times to ensure familiarity with the empirical data and evidence relating to the research questions. Two scholars conducted an independent coding of the papers in accordance with the principles of qualitative content analysis [35]. To establish intercoder reliability, all codes were compared, and a high reliability rate (0.91) above the recommended threshold (0.80) was obtained [35,36].

4. Results and Discussion

In this literature review, we have organized the synthesis of the results and discussion into three main categories, which are oriented by the research questions: (a) overall research trends, (b) digital tools used in the studies (software and hardware), and (c) the potential of AR/VR technologies for mathematics learning.

4.1. Research Trends on Learning Mathematics with AR/VR Technology

4.1.1. Publication Years

The analyses revealed a notable increase in the number of empirical studies on the use of AR/VR in mathematics education published in peer-reviewed journals after 2018 (see Figure 3). This finding highlights the considerable interest of mathematics education researchers in this topic and the fact that applications of AR/VR technologies in the educational landscape have proliferated in recent years [12,13,14,15,22]. The fact that the tools/devices required for AR/VR implication are becoming more affordable and accessible [10,15,37] may have contributed to this result. Forecasts regarding the increased adoption of AR/VR technologies in education, reported in the 2019 and 2020 Horizon Reports by the New Media Consortium [38] and Educause [39], are in line with our results.

4.1.2. Geographical Distribution

An analysis was conducted on the country affiliations of all authors (n = 202) to determine the global outlook on the researchers’ contributions to the implementation of AR/VR in mathematics education. Our analysis observed a diverse set of contributors to this research area, with 25 different countries being represented (see Figure 4). The numbers/figures displayed on the world map in Figure 4 represent the quantity of researchers from each country who are making contributions to the field. Researchers from Asia (45%, n = 90) and Europe (33%, n = 66) are the dominant contributors to the field. North America is the third largest contributor (20%, n = 40), followed by South America (1%, n = 3) and Australia (1%, n = 3).
The heterogeneous geographical distribution of researchers may be attributable to the varying levels of funding, research priorities, and educational policies across different regions worldwide. Furthermore, the prevalence of technology and digital devices in education may be higher in certain regions, leading to greater interest in the use of AR/VR in mathematics education. It is also worth noting that these results may reflect the biases of the research community or the authors themselves, such as language barriers, access to information and resources, and cultural factors that may influence the decision to pursue research in this area [40]. Overall, the reported results attest to considerable scholarly interest and investment in researching the use of AR/VR in mathematics education and demonstrate that researchers from a diverse set of countries are contributing to this important area of research.

4.1.3. Study Domains

The analysis demonstrated that research on the use of AR/VR in mathematics learning is heavily focused on geometry. Algebra is the second most studied area, followed by a mixture of a few domains (e.g., geometry, algebra, and calculus), then calculus, probability and other branches, such as financial mathematics and school mathematics (see Table 1).
It is unsurprising that geometry emerged as the most popular subject domain, given that it lends itself well to visualization and AR/VR technology can visualize geometric objects in the real sense [19]. According to our analysis, however, the effectiveness of AR/VR technologies for learning subjects in various foundational areas of mathematics, including calculus, analysis, arithmetic, logic, probability, and statistics, has not been sufficiently researched.
Lai and Cheong [32] argued that XR, including AR and VR, cannot be universally applied across all areas of mathematics given that the benefits derived from visualization are variable. However, we adopt a different perspective, asserting that visualization plays a significant role in the learning of different mathematics subjects and has the potential to enhance students’ understanding across multiple mathematical fields [41,42]. While we recognize that the potential utilization of AR and VR in mathematics education may involve different levels of difficulty depending on the constraints of the subjects, we contend that the primary constraint may be closely tied to the ingenuity and proficiency of the developer as well as the technological infrastructure [37].
To summarize, AR/VR technologies can be useful for users in learning various fields of mathematics. For instance, AR/VR can be used to visualize geometrical objects and structures in a more immersive, realistic, and interactive way, allowing individuals to explore, render, and manipulate shapes and figures in three dimensions. This opportunity may especially help learners to improve their spatial reasoning skills and deepen their understanding of geometrical concepts. Concerning algebra, AR/VR can be used to create visual representations of abstract algebraic concepts (e.g., equations and functions). This can make these concepts more tangible and accessible for learners, particularly for those who struggle with abstract reasoning. Moreover, AR/VR can be used to visualize complex concepts of calculus, for example complex mathematical functions and important constructs and methods, such as derivatives and integrals. This may help learners to develop a more intuitive understanding of concepts from calculus and may facilitate mathematical problem-solving skills. In probability, as another important field of mathematics, AR/VR can be used to simulate probabilistic scenarios, such as coin tosses or dice rolls, and visually represent the outcomes. This technological support may help learners to develop a conceptual understanding of probability and to figure out how to calculate probabilities in different contexts.
In each of these domains, AR and VR can function as an important tool to provide learners with more immersive and interactive learning experiences. The significance of AR/VR in mathematics education lies in its potential to engage and motivate learners, enhance their conceptual understanding, and facilitate problem-solving and critical thinking skills [3,16,17,18,19,20,21,22,43,44]. However, further empirical data are needed to substantiate the potential benefits of AR/VR technologies.
In conclusion, while there is a significant focus on using AR/VR for teaching geometry and partly algebra, the potential benefits and drawbacks of these technologies in other areas of mathematics are yet to be fully explored.

4.1.4. Methodological Bases of the Studies

Concerning the research methodologies, almost half of the reviewed studies applied quantitative research methods, followed by qualitative research methods, then mixed/multiple method and design-based research. Researchers most frequently focused on K-12 students’ mathematics learning using AR/VR technologies (secondary school students and primary school students), which aligns with earlier reviews [16,17]. K-12 students were followed by undergraduates (other than pre-service teachers), a mixture of teachers and students, pre-service teachers (PSTs), adults, in-service teachers (ISTs), and preschoolers. The vast majority of the studies recruited a relatively small number of participants (fewer than 100, see Table 2).
Owing to the prevalence of quantitative research methods among the reviewed studies (contrary to the findings of Palancı and Turan [17] but consistent with the findings of Ahmad and Junaini [16]), one might have expected the studies to have relatively large sample sizes; contrary to this expectation, however, most of the reviewed studies were found to have small sample sizes. On the one hand, this underscores the need for both large-scale studies that can help visualize the big picture in terms of the impact of AR/VR technologies on mathematics learning and in-depth qualitative research studies that facilitate comprehensive examination of this impact. On the other hand, the recruitment of larger samples may be challenging due to the costs and logistical challenges associated with the implementation of AR/VR technologies in educational settings. Moreover, the distribution of the study participants highlights the shortage of studies on AR/VR that concentrate on pre- and in-service mathematics teachers. This indicates the need for research on the role of AR/VR technologies in mathematics teacher education in particular.

4.1.5. Research Trends in the Use of AR and VR in Mathematics Learning

Our analysis revealed that the vast majority of the studies (80%, n = 47) focused exclusively on the use of AR technologies in mathematics education. By comparison, only a limited number of studies (15%, n = 9) exclusively evaluated the role of VR technologies in mathematics education, and even fewer (5%, n = 3) concentrated on AR and VR technologies in combination [2,4,45].
The reasons that AR technologies were utilized more commonly than VR technologies in educational settings—mathematics education in this case—are likely multiple. One key factor is likely the relatively high cost and complexity of VR systems, which may be prohibitive for many educational institutions. Another factor is the requirement for specialized equipment and tools (e.g., head-mounted displays), which can also be tiresome to use for long periods of time and may cause fatigue. Moreover, the development of VR applications requires considerable technical expertise [2,46]. AR technologies tend to be more accessible than VR technologies, as users can easily access AR applications on their own mobile devices. Finally, the relatively poor adoption of VR technology in education may also be due to a lack of awareness of its potential benefits and applications. However, as VR technologies continue to evolve and become more affordable, their use for educational purposes will likely increase.
Another significant result concerns the lack of attention afforded to the combined use of AR and VR technologies in mathematics education. One study considered the use of AR, VR, and MR together, and two compared the effectiveness of AR and VR in learning outcomes. This result highlights the need for more comparative research to identify the benefits and limitations of both VR and AR technologies in mathematics education. By examining the potential opportunities and drawbacks associated with using these technologies in conjunction with one another, researchers and educators can obtain a more comprehensive understanding of how these technologies may best be used in the classroom to optimize students’ mathematics learning.

4.2. Digital Tools Used in the Reviewed Studies

Our analysis revealed that various hardware and software tools were used to support mathematics learning with AR and VR technologies (see Table 3). Mobile devices were the most popular hardware tools reported in the examined studies, which may be attributed to their cost-effective advantages and suitability for use in classroom settings, as well as their accessibility, affordability, and portability compared to many stationary gadgets [47]. In particular, mobile devices can provide ideal platforms for AR applications [48]. The results revealed that the most frequently employed software programs in the reviewed studies were 3D modeling programs (e.g., Unity, Vuforia, and HP Reveal/Aurasma), which was not unexpected, given that these professional software packages are required to create 3D objects and images in virtual environments. Another significant finding was that GeoGebra was only included in a few studies (8%, n = 5), contrary to our expectation that GeoGebra would be mentioned more frequently in the studies, given that it is a context-specific, free-to-use open-source software program that is widely used in mathematics education [49]. This software is useful for developing 3D models and visualizations for AR applications and supports scripting and programming languages [50]. However, GeoGebra is not specifically optimized for AR/VR platforms, and its compatibility with such platforms is limited. The small number of studies using GeoGebra may be related to this limitation. This result should stimulate researchers and developers to develop free and open-source mathematics/geometry software tailored specifically to AR/VR platforms that can support students’ mathematics learning.

4.3. Potential Benefits and Drawbacks of AR and VR Technologies for Mathematics Learning

In this section, we outline and discuss in detail the key findings regarding the reported benefits and drawbacks of AR and VR technologies that have been identified in mathematics learning processes. As noted above, of the reviewed studies, the majority of the reported results were related to AR technologies, and evidence regarding the role of VR in mathematics learning was relatively limited. This shows that the adoption of VR technologies in the context of mathematics education is relatively infrequent in comparison to AR technologies, which calls for future research that focuses especially on VR technologies.

4.3.1. Benefits of Using AR/VR Technologies in Mathematics Learning

The analysis revealed that both AR and VR technologies positively impacted students’ mathematics learning. All reviewed studies (n = 59), which were scrutinized under three distinct categories (see Table 4), provided empirical evidence for favorable outcomes associated with using AR or VR in mathematics education. The most prevalent favorable outcomes observed were socio-emotional outcomes, with cognitive and meta-cognitive outcomes following closely behind and pedagogical outcomes being less prominent. We devised these categories based on the classifications obtained in our previous studies [40,51,52,53,54].

Benefits of Using AR/VR from Socio-Emotional Perspective

An important observation is that each study documented evidence concerning the favorable impacts of AR/VR technology on mathematics learning, with socio-emotional benefits being the most prevalent.
In particular, a significant number of studies (AR: 34%, n = 20; VR: 10%, n = 6) noted that AR/VR boosted students’ learning interest and motivation as well as their curiosity with respect to mathematics learning. According to a significant portion of the studies (AR: 32%, n = 19; VR: 10%, n = 6), users demonstrated enthusiasm and derived enjoyment in learning mathematics through the use of AR/VR. An additional salient characteristic of AR/VR, as revealed by the outcomes, is its capacity to provide users with interactive and dynamic learning experiences, which, in turn, foster social interaction among them (AR: 31%, n = 18, VR: 10%, n = 6). Several studies established that numerous users expressed satisfaction with their use of AR/VR in mathematics learning (AR: 17%, n = 20, VR: 5%, n = 3), leading to the development of a positive attitude toward the use of AR/VR in mathematics education (AR: 17%, n = 20, VR: 3%, n = 2). According to several studies, the use of AR/VR in mathematics education has been associated with enhanced opportunities for peer collaboration and the cultivation of teamwork skills (AR: 10%, n = 6; VR: 2%, n = 1), as well as heightened levels of confidence among users (AR: 7%, n = 4; VR: 2%, n = 1). Furthermore, several investigations have revealed that AR can help reduce anxiety and stress that students experience in relation to mathematics (AR: 5%, n = 3).
The reported results suggest that AR and VR positively impact students’ socio-emotional development with respect to mathematics education and that the role of socio-emotional factors in mathematics cannot be understated with respect to the learning process and the achievement of proficiency [55]. This positive outcome may be associated with the change in students’ perception of reality that results from AR/VR encounters, which offers them educational prospects that are individually linked to pertinent information [18].

Benefits of Using AR/VR from the Cognitive/Meta-Cognitive Perspective

The benefits of using AR/VR technology for mathematics education extend beyond the realm of socio-emotional outcomes. Notably, research has revealed that AR/VR can enhance students’ mathematics learning experiences by promoting cognitive and meta-cognitive development. Based on the analyses, it has been found that AR/VR technology has a positive impact on students’ academic performance in mathematics, as it facilitates active learning and enhances conceptual understanding (AR: 53%, n = 31; VR: 15%, n = 9).
According to empirical research, the efficacy of AR and VR in promoting students’ mathematical success and enhancing their levels of learning surpasses that of traditional methods [4]. However, in studies comparing the effects of AR and VR on mathematics learning and achievement, there was no significant difference found between these two technologies. Demitriadou, Stavroulia, and Lanitis [4] revealed that AR and VR technologies were equally effective for mathematics learning.
Several studies, e.g., [43,44,56,57], have indicated that AR/VR represents a significant opportunity for students to enhance their visual thinking skills through the provision of rich visualizations in both physical and virtual environments (AR: 32%, n = 19; VR: 5%, n = 3). Moreover, AR and VR technologies were found to be supportive of students’ development of spatial abilities (AR: 12%, n = 7; VR: 7%, n = 4). While research has reported that AR contributes to students’ problem-solving skills (24%, n = 14), there is no evidence concerning the effects of VR on the problem-solving skills of learners. Several studies have indicated that, through the use of AR/VR, students become more independent and autonomous in their mathematics learning processes (AR: 12%, n = 7, VR: 3%, n = 2).
Relatively few studies have reported on students’ mathematical learning processes from the cognitive and meta-cognitive perspectives. These outcomes include the enhancement of memory retention (AR: 7%, n = 4); mathematical and critical thinking (AR: 7%, n = 4); awareness, attention, and noticing (AR: 5%, n = 3; VR: 8%, n = 5); reasoning and proof (AR: 3%, n = 2; VR: 3%, n = 2); creativity (AR: 2%, n = 1; VR: 2%, n = 1); and inquiry (AR: 2%, n = 1). These are all essential skills for success in mathematics and various other aspects of life. By enhancing these skills, AR/VR technologies have the potential to make a significant contribution to students’ cognitive processes and academic development [51,58]. A single study reported that AR could reduce mathematics learners’ cognitive load, particularly with the help of visual aids. Mathematics is often a challenging subject that requires considerable mental effort, and anything that can reduce the cognitive load can positively impact students’ learning experiences.
An additional noteworthy outcome indicated that several studies (17%, n = 10) examined the efficiency of AR/VR technologies in facilitating mathematics learning among students with learning disabilities (e.g., autism and dyscalculia). The findings demonstrated that the implementation of visually-based AR/VR technologies can effectively support these students in learning mathematics.

Benefits of Using AR/VR Technologies from Pedagogical Perspective

Regarding the pedagogical outcomes, we identified three main benefits for mathematics students. The analysis revealed that AR/VR technologies were useful for learning mathematics; in addition, learners found AR/VR applications and tools to be user-friendly (AR: 25%, n = 15, VR: 3%, n = 2). Several studies noted that AR/VR had a positive effect on student engagement in mathematics education (AR: 22%, n = 13; VR: 8%, n = 5) and that this emerging technology contributed to students’ mathematics competence development, including the mathematical modelling competence (AR: 7%, n = 4, VR: 2%, n = 1). The perceived ease of use of AR/VR technologies by students underscores the pedagogical significance of these innovative approaches, despite being novel learning instruments for many [59].
Overall, these results suggest that the emerging technology of AR/VR holds promise as an effective tool to support students’ mathematical learning, enhancing their engagement and the development of their mathematical competence, which are among the main pedagogical goals of mathematics education [40,60].

4.3.2. Drawbacks to Using AR/VR Technology in Mathematics Learning

In addition to the numerous reported favorable outcomes of AR/VR technologies, it has also been observed that AR/VR technologies may entail certain drawbacks for students engaged in mathematics learning (see Table 5). Only a limited number of studies reported potential drawbacks to AR (29%, n = 17) and VR technologies (7%, n = 4) in mathematics education, basically including pedagogical, socio-emotional, and cognitive issues. This invites future studies exploring further possible drawbacks of AR/VR technologies, which will be crucial in developing robust AR/VR designs.
The most frequently cited drawback to AR/VR technologies concerned technical deficiencies (e.g., poor infrastructure, lack of devices and software) and technological glitches (e.g., internet connection problems, audio-visual problems) (AR: 15%, n = 9; VR: 7%, n = 4). The accessibility of AR/VR applications for all students may be limited due to cost-related factors (AR: 7%, n = 4; VR: 5%, n = 3). Several studies (7%, n = 4) have highlighted that AR applications may be time-consuming, with lengthy waiting times for users due to the lack of adequate devices as a contributing factor. Consequently, it has been reported that even a small number of students who had to wait without being able to participate in learning activities soon became bored (3%, n = 2). One of the notable negativities pertained to the absence of prior AR experience among students and their need for professional support to effectively use AR apps (5%, n = 3). Several studies have reported that AR apps may have the potential to cause health issues due to the high screen time involved and the small screen sizes of the mobile devices (2%, n = 1), and that they may increase the cognitive load of the users in obliging them to absorb information from both real and virtual settings simultaneously (2%, n = 1). Users of AR/VR applications may be restricted in terms of social interaction and communication, particularly in single-user modes (2%, n = 1).
These reported drawbacks may negatively impact the effectiveness of AR/VR technologies for mathematics learning. However, it should be noted that, while the reviewed studies reported the benefits of AR/VR that were applicable to the majority of students in their samples, the drawbacks of AR/VR have been reported for only a small number of students in the study samples. It is noteworthy that the advancement of digital technologies has emerged as a promising avenue by which the reported obstacles may be overcome in the foreseeable future [14]. Overall, to enhance mathematics learning with the successful application of AR/VR, it is important to address the potential drawbacks of AR/VR technologies and to ensure that these technologies are accessible to all students.

5. Summary of the Review Results and the Limitations of the Study

Figure 5 summaries the key findings of the present systematic review, which correspond to the three major categories: (a) socio-emotional outcomes, (b) cognitive/meta-cognitive outcomes, and (c) pedagogical outcomes. In our model, A, B, C, D, E, and F represent the positive effects of AR/VR technologies on learning outcomes (benefits of AR/VR for learners) and AI, BI, CI, and FI represent the negative effects of AR/VR technologies on learning outcomes (drawbacks of AR/VR for learners) reported in the previous section. See Table 6 for a list of the included studies, the assigned study numbers (1–59), and the main characteristics and methodologies of the studies.
The results of our systematic literature review show very clearly that the impact of AR on learning outcomes can be both positive and negative. However, according to the empirical results of the examined studies, the benefits of AR for learners outweigh its drawbacks. Moreover, similarly to AR technology, VR has proven to be beneficial for users in their acquisition of mathematical skills, as evidenced by the various aspects highlighted in Section 4. Based on the presented findings, VR technology was observed to have limitations solely in terms of its impact on pedagogical outcomes. This appears to be a crucial aspect in which the impacts of VR and AR partly differ from each other.
Despite implementing the most recent PRISMA guidelines to enhance the transparency, accuracy, and quality of the study, and conducting a thorough search strategy, the study had certain limitations concerning the manuscript selection criteria. Our emphasis was on peer-reviewed journal articles that were published in English and indexed in selected prestigious databases (i.e., WoS and SCOPUS). Furthermore, our sampling methodology entailed the exclusion of literary works such as books, book chapters, and papers in conference proceedings, as well as studies not penned in the English language. It can be assumed that there exist studies that were indexed in electronic sources other than those which we have selected and, therefore, may have been omitted. Overall, the methodological approach we adopted for the selection process may have excluded studies that hold relevance to the investigation at hand.

6. Conclusions

The present study underscores the escalating scholarly attention devoted to exploring the efficacy of integrating AR/VR technology into mathematics education to optimize learning outcomes and pedagogical practices. The review provides evidence that indicates the noteworthy potential for the use of AR/VR in advancing students’ socio-emotional, cognitive/meta-cognitive, and pedagogical development in mathematics learning processes. The main results of this systematic review are promising in that they substantiate the notion that the use of AR/VR technology constitutes an efficacious approach to enhancing students’ mathematics learning outcomes. Notwithstanding, this review highlights certain apprehensions surrounding the incorporation of AR/VR in mathematics education, largely associated with potential technical and technological inadequacies that may hinder students’ mathematics learning.

7. Recommendations and Implications

The results of this systematic literature review study have significant implications for future research and development efforts which are aimed at improving mathematics education through the integration of AR/VR technology.
Concerning the integration of AR/VR technologies into mathematics learning, the study has shown their potential to enhance students’ engagement and mathematics achievement. To achieve these goals, mathematics educators can use AR/VR to create interactive and immersive mathematical environments that allow learners to explore mathematical concepts in a more engaging and intuitive way. They can design AR/VR applications that provide real-world scenarios that require mathematical problem-solving skills, and utilize AR/VR simulations to enable students to visualize complex mathematical concepts. Additionally, AR/VR technology can be employed to personalize the learning experience for learners, making mathematics more accessible and attractive for those with learning difficulties or disabilities. To effectively integrate AR/VR technology into their teaching practice, mathematics teachers should be provided with training and support, and encouraged to collaborate and share best practices within their mathematics education community. By incorporating these suggestions and pedagogical implications, mathematics educators may harness the full potential of AR/VR technology to enhance mathematics learning and promote students’ learning processes.
However, there are still many areas where more research is needed to fully understand the potential benefits and limitations of AR/VR technology in mathematics education. The present investigation, through its rigorous and systematic analysis, has offered compelling evidence in favor of integrating AR/VR technology into mathematics education. Nonetheless, to further strengthen the validity of these findings, it is recommended that future research endeavors consider the possibility of a novelty effect of AR/VR on learning outcomes.
The studies reviewed in the present analysis are limited in number and scope, indicating the need for further research on the effectiveness of AR/VR in different educational settings and with diverse learner populations. To optimize the effectiveness of AR/VR technology in mathematics education, future research should explore its application in foundational areas of mathematics, such as calculus, logic, probability, and statistics, using both longitudinal large-scale quantitative and in-depth qualitative studies with diverse samples. Moreover, research on the amalgamation of AR/VR technology with other pedagogical approaches, such as flipped classroom and blended learning models, in the field of mathematics teacher education is urgently needed. This line of inquiry may hold significant promise for improving mathematics learning outcomes and is thus of critical importance.
Efforts should also be made to develop affordable, accessible, and user-friendly AR/VR software systems that are specifically designed to facilitate mathematics learning. Such development necessitates close collaboration among expert software developers and mathematics educators. The lack of empirical evidence regarding the effectiveness of VR in enhancing mathematics learning highlights the need for further research endeavors to elucidate the impact of VR technology on students’ mathematics learning and their mathematical competence and problem-solving skills. Comparative research examining the differential effects of AR and VR technologies on mathematics learning will also inform educators and policymakers regarding the most appropriate technology for their desired learning outcomes.
Overall, the findings of this systematic literature review have the potential to furnish mathematics educators with critical insights that can facilitate the improvement of the course design, delivery, and effectiveness and overall quality of instruction with AR/VR. This potential is based on consideration of both the opportunities and limitations of AR and VR technology in relation to its effects on mathematics learning, thereby contributing significantly to the discourse on pedagogical innovation. As such, future studies should aim to address the reported gaps to fully understand the potential of AR/VR technologies in enhancing and transforming mathematics education, in line with the requirements of the digital age.

Author Contributions

Conceptualization, M.C., N.B. and G.K.; methodology, M.C., N.B. and G.K.; software, M.C. and N.B.; validation, M.C. and N.B.; formal analysis, M.C. and N.B.; investigation, M.C.; resources, M.C.; data curation, M.C.; writing—original draft preparation, M.C.; writing—review and editing, M.C., G.K. and N.B.; visualization, M.C.; supervision, G.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research has been funded by the “Ideas and Venture Fund of Universität Hamburg”, under the “Excellence Strategy Initiative”. U-7-4-05-EXU-22-01/Z1-V5-058: IRF 2022_Cevikbas.

Data Availability Statement

All data were retrieved by WoS and SCOPUS and can be replicated.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Graafland, J.H. New Technologies and 21st Century Children: Recent Trends and Outcomes; OECD: Paris, France, 2018. [Google Scholar]
  2. Cabero-Almenara, J.; Barroso-Osuna, J.; Martinez-Roig, R. Mixed, augmented and virtual, reality applied to the teaching of mathematics for architects. Appl. Sci. 2021, 11, 7125. [Google Scholar] [CrossRef]
  3. Kaufmann, H.; Schmalstieg, D. Mathematics and geometry education with collaborative augmented reality. In Proceedings of the ACM SIGGRAPH 2002 Conference Abstracts and Applications, San Antonio, TX, USA, 21–26 July 2002; pp. 37–41. [Google Scholar]
  4. Demitriadou, E.; Stavroulia, K.E.; Lanitis, A. Comparative evaluation of virtual and augmented reality for teaching mathematics in primary education. Educ. Inf. Technol. 2020, 25, 381–401. [Google Scholar] [CrossRef]
  5. Monteiro Paulo, R.; Pereira, A.L.; Pavanelo, E. The constitution of mathematical knowledge with augmented reality. Math. Enthus. 2021, 18, 641–668. [Google Scholar] [CrossRef]
  6. Álvarez-Marín, A.; Velázquez-Iturbide, J.Á. Augmented reality and engineering education: A systematic review. IEEE Trans. Learn. Technol. 2021, 14, 817–831. [Google Scholar] [CrossRef]
  7. Barteit, S.; Lanfermann, L.; Bärnighausen, T.; Neuhann, F.; Beiersmann, C. Augmented, mixed, and virtual reality-based head-mounted devices for medical education: Systematic review. JMIR Serious Games 2021, 9, e29080. [Google Scholar] [CrossRef]
  8. Yung, R.; Khoo-Lattimore, C. New realities: A systematic literature review on virtual reality and augmented reality in tourism research. Curr. Issues Tour. 2019, 22, 2056–2081. [Google Scholar] [CrossRef]
  9. Gavish, N. The dark side of using augmented reality (AR) training systems in industry. In Systems Engineering in the Fourth Industrial Revolution; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2019; pp. 191–201. [Google Scholar] [CrossRef]
  10. Scavarelli, A.; Arya, A.; Teather, R.J. Virtual reality and augmented reality in social learning spaces: A literature review. Virtual Real. 2021, 25, 257–277. [Google Scholar] [CrossRef]
  11. Dede, C.J.; Jacobson, J.; Richards, J. Introduction: Virtual, augmented, and mixed realities in education. In Virtual, Augmented, and Mixed Realities in Education; Liu, D., Dede, C., Huang, R., Richards, J., Eds.; Springer: Berlin/Heidelberg, Germany, 2017; pp. 1–16. [Google Scholar]
  12. Akcayir, M.; Akcayir, G. Advantages and challenges associated with augmented reality for education: A systematic review of the literature. Educ. Res. Rev. 2017, 20, 1–11. [Google Scholar] [CrossRef]
  13. Maas, M.J.; Hughes, J.M. Virtual, augmented and mixed reality in K–12 education: A review of the literature. Technol. Pedagog. Educ. 2020, 29, 231–249. [Google Scholar] [CrossRef]
  14. Sırakaya, M.; Alsancak Sırakaya, D. Augmented reality in STEM education: A systematic review. Interact. Learn. Environ. 2022, 30, 1556–1569. [Google Scholar] [CrossRef]
  15. Skarbez, R.; Smith, M.; Whitton, M.C. Revisiting milgram and kishino’s reality-virtuality continuum. Front. Virtual Real. 2021, 2, 647997. [Google Scholar] [CrossRef]
  16. Ahmad, N.; Junaini, S. Augmented reality for learning mathematics: A systematic literature review. Int. J. Emerg. Technol. Learn. (iJET) 2020, 15, 106–122. [Google Scholar] [CrossRef]
  17. Palanci, A.; Turan, Z. How does the use of the augmented reality technology in mathematics education affect learning processes?: A systematic review. Uluslararası Eğitim Programları Ve Öğretim Çalışmaları Derg. 2021, 11, 89–110. [Google Scholar] [CrossRef]
  18. Bujak, K.R.; Radu, I.; Catrambone, R.; MacIntyre, B.; Zheng, R.; Golubski, G. A psychological perspective on augmented reality in the mathematics classroom. Comput. Educ. 2013, 68, 536–544. [Google Scholar] [CrossRef]
  19. Cai, S.; Liu, E.; Yang, Y.; Liang, J.C. Tablet-based AR technology: Impacts on students’ conceptions and approaches to learning mathematics according to their self-efficacy. Br. J. Educ. Technol. 2019, 50, 248–263. [Google Scholar] [CrossRef]
  20. Dünser, A.; Steinbügl, K.; Kaufmann, H.; Glück, J. Virtual and augmented reality as spatial ability training tools. In Proceedings of the 7th ACM SIGCHI New Zealand Chapter’s International Conference on Computer-Human Interaction: Design Centered HCI, Christchurch, New Zealand, 6–7 July 2006; pp. 125–132. [Google Scholar]
  21. Stranger-Johannessen, E. Exploring math achievement through gamified virtual reality. In Proceedings of the Lifelong Technology-Enhanced Learning: 13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Leeds, UK, 3–5 September 2018; pp. 613–616. [Google Scholar]
  22. Villena-Taranilla, R.; Tirado-Olivares, S.; Cozar-Gutierrez, R.; González-Calero, J.A. Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis. Educ. Res. Rev. 2022, 35, 100434. [Google Scholar] [CrossRef]
  23. Esin, S.; Ozdemir, E. The metaverse in mathematics education: The opinions of secondary school mathematics teachers. J. Educ. Technol. Online Learn. 2022, 5, 1041–1060. [Google Scholar] [CrossRef]
  24. Lubega, J.; Paul, M. Adoption of the SAMR model to asses ICT pedagogical adoption: A case of Makerere University. Int. J. e-Educ. e-Bus. e-Manag. e-Learn. 2014, 4, 106–115. [Google Scholar]
  25. Wahono, B.; Lin, P.-L.; Chang, C.-Y. Evidence of STEM enactment effectiveness in Asian student learning outcomes. Int. J. STEM Educ. 2020, 7, 36. [Google Scholar] [CrossRef]
  26. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Int. J. Surg. 2021, 88, 105906. [Google Scholar] [CrossRef]
  27. Azuma, R.T. A survey of augmented reality. Presence Teleoper. Virtual Environ. 1997, 6, 355–385. [Google Scholar] [CrossRef]
  28. Milgram, P.; Kishino, F. A taxonomy of mixed reality visual displays. IEICE Trans. Inf. Syst. 1994, 77, 1321–1329. [Google Scholar]
  29. Azuma, R.; Baillot, Y.; Behringer, R.; Feiner, S.; Julier, S.; MacIntyre, B. Recent advances in augmented reality. IEEE Comput. Graph. Appl. 2001, 21, 34–47. [Google Scholar] [CrossRef]
  30. Ibáñez, M.-B.; Delgado-Kloos, C. Augmented reality for STEM learning: A systematic review. Comput. Educ. 2018, 123, 109–123. [Google Scholar] [CrossRef]
  31. Dengel, A.; Iqbal, M.; Grafe, S.; Mangina, E. A review on augmented reality authoring toolkits for education. Front. Virtual Real. 2022, 3, 1–15. [Google Scholar] [CrossRef]
  32. Lai, J.W.; Cheong, K.H. Adoption of virtual and augmented reality for mathematics education: A scoping review. IEEE Access 2022, 10, 13693–13703. [Google Scholar] [CrossRef]
  33. King, W.R.; He, J. Understanding the role and methods of meta-analysis in IS research. Commun. Assoc. Inf. Syst. 2005, 16, 32. [Google Scholar] [CrossRef]
  34. Paré, G.; Trudel, M.-C.; Jaana, M.; Kitsiou, S. Synthesizing information systems knowledge: A typology of literature reviews. Inf. Manag. 2015, 52, 183–199. [Google Scholar] [CrossRef]
  35. Miles, M.B.; Huberman, A.M. Qualitative Data Analysis: An Expanded Sourcebook; Sage: Thousand Oaks, CA, USA, 1994. [Google Scholar]
  36. Creswell, J.W.; Poth, C.N. Qualitative Inquiry and Research Design: Choosing Among Five Approaches; Sage: Thousand Oaks, CA, USA, 2016. [Google Scholar]
  37. Coburn, J.Q.; Freeman, I.; Salmon, J.L. A review of the capabilities of current low-cost virtual reality technology and its potential to enhance the design process. J. Comput. Inf. Sci. Eng. 2017, 17, 031013. [Google Scholar] [CrossRef]
  38. Alexander, B.; Ashford-Rowe, K.; Barajas-Murphy, N.; Dobbin, G.; Knott, J.; McCormack, M.; Pomerantz, J.; Seilhamer, R.; Weber, N. Educause Horizon Report: 2019 Higher Education Edition; Educause: Louisville, CO, USA, 2019. [Google Scholar]
  39. Brown, M.; McCormack, M.; Reeves, J.; Brook, D.C.; Grajek, S.; Alexander, B.; Bali, M.; Bulger, S.; Dark, S.; Engelbert, N. 2020 Educause Horizon Report Teaching and Learning Edition; Educause: Louisville, CO, USA, 2020. [Google Scholar]
  40. Cevikbas, M.; Kaiser, G.; Schukajlow, S. A systematic literature review of the current discussion on mathematical modelling competencies: State-of-the-art developments in conceptualizing, measuring, and fostering. Educ. Stud. Math. 2022, 109, 205–236. [Google Scholar] [CrossRef]
  41. Boaler, J. Mathematical Mindsets: Unleashing Students’ Potential through Creative Mathematics, Inspiring Messages and Innovative Teaching; John Wiley & Sons: Hoboken, NJ, USA, 2022. [Google Scholar]
  42. Joyner, J.; Reys, B. Principles and standards for school mathematics: What’s in it for you? Teach. Child. Math. 2000, 7, 26–29. [Google Scholar] [CrossRef]
  43. Jesionkowska, J.; Wild, F.; Deval, Y. Active learning augmented reality for STEAM education—A case study. Educ. Sci. 2020, 10, 198. [Google Scholar] [CrossRef]
  44. Chen, Y.C. Effect of mobile augmented reality on learning performance, motivation, and math anxiety in a math course. J. Educ. Comput. Res. 2019, 57, 1695–1722. [Google Scholar] [CrossRef]
  45. Medina Herrera, L.; Castro Pérez, J.; Juárez Ordóñez, S. Developing spatial mathematical skills through 3D tools: Augmented reality, virtual environments and 3D printing. Int. J. Interact. Des. Manuf. (IJIDeM) 2019, 13, 1385–1399. [Google Scholar] [CrossRef]
  46. Dede, C. Immersive interfaces for engagement and learning. Science 2009, 323, 66–69. [Google Scholar] [CrossRef]
  47. Wu, W.-H.; Wu, Y.-C.J.; Chen, C.-Y.; Kao, H.-Y.; Lin, C.-H.; Huang, S.-H. Review of trends from mobile learning studies: A meta-analysis. Comput. Educ. 2012, 59, 817–827. [Google Scholar] [CrossRef]
  48. Henrysson, A.; Billinghurst, M.; Ollila, M. Face to face collaborative AR on mobile phones. In Proceedings of the Fourth IEEE and Acm International Symposium on Mixed and Augmented Reality (Ismar’05), Vienna, Austria, 5–8 October 2005; pp. 80–89. [Google Scholar]
  49. Jones, K.; Lavicza, Z.; Hohenwarter, M.; Lu, A.; Dawes, M.; Parish, A.; Borcherds, M. Establishing a professional development network to support teachers using dynamic mathematics software GeoGebra. Proc. Br. Soc. Res. Into Learn. Math. 2009, 29, 97–102. [Google Scholar]
  50. Hohenwarter, M.; Jones, K. Ways of linking geometry and algebra, the case of Geogebra. Proc. Br. Soc. Res. Into Learn. Math. 2007, 27, 126–131. [Google Scholar]
  51. Cevikbas, M.; Kaiser, G. Can flipped classroom pedagogy offer promising perspectives for mathematics education on pandemic-related issues? A systematic literature review. ZDM–Math. Educ. 2023, 55, 177–191. [Google Scholar] [CrossRef]
  52. Cevikbas, M.; König, J.; Rothland, M. Empirical research on teacher competence in mathematics lesson planning: Recent developments. ZDM Math. Educ. 2023. [Google Scholar] [CrossRef]
  53. Cevikbas, M.; Kaiser, G. Promoting personalized learning in flipped classrooms: A systematic review study. Sustainability 2022, 14, 11393. [Google Scholar] [CrossRef]
  54. Cevikbas, M. Fostering mathematical modelling competencies: A systematic literature review. In Initiationen mathematikdidaktischer Forschung; Buchholtz, N., Schwarz, B., Vorhölter, K., Eds.; Springer Spektrum: Berlin/Heidelberg, Germany, 2022; pp. 51–73. [Google Scholar] [CrossRef]
  55. Schukajlow, S.; Rakoczy, K.; Pekrun, R. Emotions and motivation in mathematics education: Where we are today and where we need to go. ZDM–Math. Educ. 2023, 55, 249–267. [Google Scholar] [CrossRef] [PubMed]
  56. Rodríguez, J.L.; Romero, I.; Codina, A. The influence of NeoTrie VR’s immersive virtual reality on the teaching and learning of geometry. Mathematics 2021, 9, 2411. [Google Scholar] [CrossRef]
  57. del Cerro Velázquez, F.; Morales Méndez, G. Application in augmented reality for learning mathematical functions: A study for the development of spatial intelligence in secondary education students. Mathematics 2021, 9, 369. [Google Scholar] [CrossRef]
  58. Saforrudin, N.; Badioze Zaman, H.; Ahmad, A. Technical skills in developing augmented reality application: Teachers’ readiness. In Proceedings of the Visual Informatics: Sustaining Research and Innovations: Second International Visual Informatics Conference, IVIC 2011, Selangor, Malaysia, 9–11 November 2011; pp. 360–370. [Google Scholar]
  59. Huang, H.-M.; Liaw, S.-S. An analysis of learners’ intentions toward virtual reality learning based on constructivist and technology acceptance approaches. Int. Rev. Res. Open Distrib. Learn. 2018, 19(1), 91–115. [Google Scholar] [CrossRef]
  60. Cevikbas, M.; Kaiser, G. Student engagement in a flipped secondary mathematics classroom. Int. J. Sci. Math. Educ. 2022, 20, 1455–1480. [Google Scholar] [CrossRef]
  61. Rebollo, C.; Remolar, I.; Rossano, V.; Lanzilotti, R. Multimedia augmented reality game for learning math. Multimed. Tools Appl. 2022, 81, 14851–14868. [Google Scholar] [CrossRef]
  62. Kounlaxay, K.; Shim, Y.; Kang, S.J.; Kwak, H.Y.; Kim, S.K. Learning media on mathematical education based on augmented reality. KSII Trans. Internet Inf. Syst. (TIIS) 2021, 15, 1015–1029. [Google Scholar] [CrossRef]
  63. Bos, R.; Doorman, M.; Drijvers, P.; Shvarts, A. Embodied design using augmented reality: The case of the gradient. Teach. Math. Its Appl. Int. J. IMA 2022, 41, 125–141. [Google Scholar] [CrossRef]
  64. Hsieh, M.C.; Chen, S.H. Intelligence augmented reality tutoring system for mathematics teaching and learning. J. Internet Technol. 2019, 20, 1673–1681. [Google Scholar]
  65. Alqarni, A.S.; Alzahrani, R.R. The impact of augmented reality on developing students’ mathematical thinking skills. IJCSNS Int. J. Comput. Sci. Netw. Secur. 2022, 22, 553–556. [Google Scholar]
  66. Cangas, D.; Morga, G.; Blancas, J.L.R. Geometry teaching experience in virtual reality with NeoTrie VR. Psychol. Soc. Educ. 2019, 11, 355–366. [Google Scholar]
  67. Ozcakir, B.; Cakiroglu, E. Fostering spatial abilities of middle school students through augmented reality: Spatial strategies. Educ. Inf. Technol. 2022, 27, 2977–3010. [Google Scholar] [CrossRef]
  68. Ozcakir, B.; Ozdemir, D. Reliability and validity study of an augmented reality supported mathematics education attitude scale. Int. J. Hum.–Comput. Interact. 2022, 38, 1638–1650. [Google Scholar] [CrossRef]
  69. Li, S.; Shen, Y.; Jiao, X.; Cai, S. Using augmented reality to enhance students’ representational fluency: The case of linear functions. Mathematics 2022, 10, 1718. [Google Scholar] [CrossRef]
  70. Gargrish, S.; Mantri, A.; Kaur, D.P. Evaluation of memory retention among students using augmented reality based geometry learning assistant. Educ. Inf. Technol. 2022, 27, 12891–12912. [Google Scholar] [CrossRef]
  71. Su, Y.S.; Cheng, H.W.; Lai, C.F. Study of virtual reality immersive technology enhanced mathematics geometry learning. Front. Psychol. 2022, 13, 760418. [Google Scholar] [CrossRef]
  72. Schutera, S.; Schnierle, M.; Wu, M.; Pertzel, T.; Seybold, J.; Bauer, P.; Teutscher, D.; Raedle, M.; Heß-Mohr, N.; Röck, S.; et al. On the potential of augmented reality for mathematics teaching with the application cleARmaths. Educ. Sci. 2021, 11, 368. [Google Scholar] [CrossRef]
  73. Mailizar, M.; Johar, R. Examining students’ intention to use augmented reality in a project-based geometry learning environment. Int. J. Instr. 2021, 14, 773–790. [Google Scholar] [CrossRef]
  74. Kellems, R.O.; Cacciatore, G.; Osborne, K. Using an augmented reality–based teaching strategy to teach mathematics to secondary students with disabilities. Career Dev. Transit. Except. Individ. 2019, 42, 253–258. [Google Scholar] [CrossRef]
  75. Morris, J.R.; Hughes, E.M.; Stocker, J.D.; Davis, E.S. Using video modeling, explicit instruction, and augmented reality to teach mathematics to students with disabilities. Learn. Disabil. Q. 2022, 45, 306–319. [Google Scholar] [CrossRef]
  76. Miundy, K.; Zaman, H.B.; Nordin, A.; Ng, K.H. Screening test on dyscalculia learners to develop a suitable augmented reality (AR) assistive learning application. Malays. J. Comput. Sci. 2019, 1, 92–107. [Google Scholar] [CrossRef]
  77. Moreno, L.A.H.; Solórzano, J.G.L.; Morales, M.T.T.; Villegas, O.O.V.; Sánchez, V.G.C. Effects of using mobile augmented reality for simple interest computation in a financial mathematics course. PeerJ Comput. Sci. 2021, 7, e618. [Google Scholar] [CrossRef] [PubMed]
  78. Xie, Y.; Hong, Y.; Fang, Y. Virtual reality primary school mathematics teaching system based on GIS data fusion. Wirel. Commun. Mob. Comput. 2022, 2022, 7766617. [Google Scholar] [CrossRef]
  79. Arican, M.; Ozcakir, B. Facilitating the development of preservice teachers’ proportional reasoning in geometric similarity problems using augmented reality activities. Educ. Inf. Technol. 2021, 26, 2327–2353. [Google Scholar] [CrossRef]
  80. Cheng, Y.W.; Wang, Y.; Cheng, I.L.; Chen, N.S. An in-depth analysis of the interaction transitions in a collaborative Augmented Reality-based mathematic game. Interact. Learn. Environ. 2019, 27, 782–796. [Google Scholar] [CrossRef]
  81. Aldalalah, O.; Ababneh, Z.; Bawaneh, A.; Alzubi, W. Effect of augmented reality and simulation on the achievement of mathematics and visual thinking among students. Int. J. Emerg. Technol. Learn. (iJET) 2019, 14, 164–185. [Google Scholar] [CrossRef]
  82. Root, J.R.; Cox, S.K.; Davis, K.; Gonzales, S. Using augmented reality and modified schema-based instruction to teach problem solving to students with autism. Remedial Spec. Educ. 2022, 43, 301–313. [Google Scholar] [CrossRef]
  83. Ibili, E.; Resnyansky, D.; Billinghurst, M. Applying the technology acceptance model to understand maths teachers’ perceptions towards an augmented reality tutoring system. Educ. Inf. Technol. 2019, 24, 2653–2675. [Google Scholar] [CrossRef]
  84. Akman, E.; Cakir, R. Pupils’ opinions on an educational virtual reality game in terms of flow experience. Int. J. Emerg. Technol. Learn. 2019, 14, 121–137. [Google Scholar] [CrossRef]
  85. Wu, C.L. Using video modeling with augmented reality to teach students with developmental disabilities to solve mathematical word problems. J. Dev. Phys. Disabil. 2022, 35, 487–507. [Google Scholar] [CrossRef]
  86. Pozo-Sánchez, S.; Lopez-Belmonte, J.; Moreno-Guerrero, A.J.; Fuentes-Cabrera, A. Effectiveness of flipped learning and augmented reality in the new educational normality of the COVID-19 era. Texto Livre 2022, 14, e34260. [Google Scholar] [CrossRef]
  87. Ahmad, F.A.R.O.B. The effect of augmented reality in improving visual thinking in mathematics of 10th-grade students in Jordan. Int. J. Adv. Comput. Sci. Appl. 2021, 12, 352–360. [Google Scholar] [CrossRef]
  88. Saundarajan, K.; Osman, S.; Kumar, J.; Daud, M.; Abu, M.; Pairan, M. Learning algebra using augmented reality: A preliminary investigation on the application of photomath for lower secondary education. Int. J. Emerg. Technol. Learn. (iJET) 2020, 15, 123–133. [Google Scholar] [CrossRef]
  89. Kellems, R.O.; Eichelberger, C.; Cacciatore, G.; Jensen, M.; Frazier, B.; Simons, K.; Zaru, M. Using video-based instruction via augmented reality to teach mathematics to middle school students with learning disabilities. J. Learn. Disabil. 2020, 53, 277–291. [Google Scholar] [CrossRef]
  90. Kazanidis, I.; Pellas, N. Developing and assessing augmented reality applications for mathematics with trainee instructional media designers: An exploratory study on user experience. J. Univers. Comput. Sci. 2019, 25, 489–514. [Google Scholar]
  91. Kellems, R.O.; Cacciatore, G.; Hansen, B.D.; Sabey, C.V.; Bussey, H.C.; Morris, J.R. Effectiveness of video prompting delivered via augmented reality for teaching transition-related math skills to adults with intellectual disabilities. J. Spec. Educ. Technol. 2021, 36, 258–270. [Google Scholar] [CrossRef]
  92. Flores-Bascuñana, M.; Diago, P.D.; Villena-Taranilla, R.; Yáñez, D.F. On augmented reality for the learning of 3D-geometric contents: A preliminary exploratory study with 6-grade primary students. Educ. Sci. 2019, 10, 4. [Google Scholar] [CrossRef]
  93. Gargrish, S.; Kaur, D.P.; Mantri, A.; Singh, G.; Sharma, B. Measuring effectiveness of augmented reality-based geometry learning assistant on memory retention abilities of the students in 3D geometry. Comput. Appl. Eng. Educ. 2021, 29, 1811–1824. [Google Scholar] [CrossRef]
  94. Jones, S.R.; Long, N.E.; Becnel, J.J. Design of virtual reality modules for multivariable calculus and an examination of student noticing within them. Res. Math. Educ. 2022, 1–24. [Google Scholar] [CrossRef]
  95. Akman, E.; Cakir, R. The effect of educational virtual reality game on primary school students’ achievement and engagement in mathematics. Interact. Learn. Environ. 2020, 1–18. [Google Scholar] [CrossRef]
  96. Haas, B.; Kreis, Y.; Lavicza, Z. Integrated STEAM approach in outdoor trails with elementary school pre-service teachers. Educ. Technol. Soc. 2021, 24, 205–219. [Google Scholar]
  97. Yiannoutsou, N.; Johnson, R.; Price, S. Non visual virtual reality. Educ. Technol. Soc. 2021, 24, 151–163. [Google Scholar]
  98. Shi, A.; Wang, Y.; Ding, N. The effect of game–based immersive virtual reality learning environment on learning outcomes: Designing an intrinsic integrated educational game for pre–class learning. Interact. Learn. Environ. 2022, 30, 721–734. [Google Scholar] [CrossRef]
  99. Cahyono, A.N.; Sukestiyarno, Y.L.; Asikin, M.; Ahsan, M.G.K.; Ludwig, M. Learning mathematical modelling with augmented reality mobile math trails program: How can it work? J. Math. Educ. 2020, 11, 181–192. [Google Scholar] [CrossRef]
  100. Amir, M.; Ariyanti, N.; Anwar, N.; Valentino, E.; Afifah, D. Augmented reality mobile learning system: Study to improve PSTs’ understanding of mathematical development. IJIM 2020, 14, 239–247. [Google Scholar] [CrossRef]
  101. Andrea, R.; Lailiyah, S.; Agus, F.; Ramadiani, R. “Magic Boosed” an elementary school geometry textbook with marker-based augmented reality. TELKOMNIKA (Telecommun. Comput. Electron. Control) 2019, 17, 1242–1249. [Google Scholar] [CrossRef]
  102. Nabila, N.I.; Junaini, S.N. A mobile augmented reality mathematics card game for learning prism. Int. J. Comput. Digit. Syst. 2021, 11, 217–225. [Google Scholar] [CrossRef]
  103. Awang, K.; Shamsuddin, S.N.W.; Ismail, I.; Rawi, N.A.; Amin, M.M. The usability analysis of using augmented reality for linus students. Indones J. Electr. Eng. Comput. Sci. 2019, 13, 58–64. [Google Scholar] [CrossRef]
  104. Elsayed, S.A.; Al-Najrani, H.I. Effectiveness of the augmented reality on improving the visual thinking in mathematics and academic motivation for middle school students. Eurasia J. Math. Sci. Technol. Educ. 2021, 17, em1991. [Google Scholar] [CrossRef]
  105. Hanafi, H.F.; Zainuddin, N.A.; Abdullah, M.F.N.L.; Ibrahim, M.H. The effectiveness of teaching aid for a mathematics subject via mobile augmented reality (Mar) for standard six students. Int. J. Recent Technol. Eng. 2019, 7, 121–125. [Google Scholar]
  106. Hanid, M.F.A.; Said, M.N.H.M.; Yahaya, N.; Abdullah, Z. The elements of computational thinking in learning geometry by using augmented reality application. Int. J. Interact. Mob. Technol. 2022, 16, 28–41. [Google Scholar] [CrossRef]
  107. Miundy, K.; Zaman, H.B.; Nosrdin, A.; Ng, K.H. Evaluation of visual based Augmented Reality (AR) learning application (V-ARA-Dculia) for dyscalculia learners. JOIV Int. J. Inform. Vis. 2019, 3, 343–354. [Google Scholar] [CrossRef]
  108. Ozcakir, B.; Cakiroglu, E. An augmented reality learning toolkit for fostering spatial ability in mathematics lesson: Design and development. Eur. J. Sci. Math. Educ. 2021, 9, 145–167. [Google Scholar] [CrossRef]
  109. Rohendi, D.; Wihardi, Y. Learning three-dimensional shapes in geometry using mobile-based augmented reality. Int. J. Interact. Mob. Technol. 2020, 14, 48–60. [Google Scholar] [CrossRef]
  110. Stotz, M.; Columba, L. Using augmented reality to teach subitizing with preschool students. J. Interact. Learn. Res. 2018, 29, 545–577. [Google Scholar]
Figure 1. Simplified representation of a reality–virtuality continuum [28].
Figure 1. Simplified representation of a reality–virtuality continuum [28].
Systems 11 00244 g001
Figure 2. Flow chart of the article selection process.
Figure 2. Flow chart of the article selection process.
Systems 11 00244 g002
Figure 3. The publication years of the studies.
Figure 3. The publication years of the studies.
Systems 11 00244 g003
Figure 4. Geographical distribution of the authors of the reviewed studies.
Figure 4. Geographical distribution of the authors of the reviewed studies.
Systems 11 00244 g004
Figure 5. Summary of the key results integrated into the reality–virtuality continuum model.
Figure 5. Summary of the key results integrated into the reality–virtuality continuum model.
Systems 11 00244 g005
Table 1. Study domains.
Table 1. Study domains.
Categoryn%
Geometry3153
Algebra1322
Mixture of geometry, algebra, and calculus610
Calculus58
Probability12
Other (financial mathematics and school mathematics)35
Table 2. Methodological bases of the studies.
Table 2. Methodological bases of the studies.
CategorySub-Categoryn%
Research methodQuantitative research methods2847
Qualitative research methods1322
Mixed/multiple methods1322
Design-based research method58
SampleSecondary school students2237
Primary school students1424
Undergraduates other than PSTs915
Mixture of teachers and students712
PSTs35
Adults23
ISTs12
Preschoolers12
Sample Size1–1004983
101–500712
501–100023
Not mentioned12
Table 3. Digital tools (hardware and software) used in the reviewed studies.
Table 3. Digital tools (hardware and software) used in the reviewed studies.
CategorySub-Categoryn%
HardwareTablet PCs2746
Smartphones2441
AR/VR Glasses-Headsets-Controllers1322
QR code/Marker-based systems1119
Desktops1017
Calculator47
Camera23
Checklists, guidelines booklets, MagicBook23
3D Printers12
Sandbox12
Projector12
MP3 player12
SoftwareUnity1627
Vuforia1119
HP Reveal/Aurasma814
GeoGebra58
Adobe Illustrator, Adobe Photoshop, and Adobe Audition58
Game-based applications (LetsGo Hiking, Beijing Travel Plan, Kesfet Kurtul)610
C#35
3ds Max23
Zappar23
NeoTrie12
Krpano12
ENTITI Creator12
Maya12
Mixamo12
Zoom12
Blender12
PhET12
VisualMath12
Table 4. Benefits of using AR/VR in mathematics learning.
Table 4. Benefits of using AR/VR in mathematics learning.
CategorySub-CategoryARVR
n%n%
Socio-emotional outcomesLearning interest, curiosity2034610
Learning motivation2034610
Enthusiasm, enjoyment, entertaining1932610
Social interaction, interactivity/dynamism1831610
Satisfaction 101735
Attitude, perception101723
Collaboration, teamwork61012
Sense of confidence4712
Anxiety, stress35--
Cognitive and meta-cognitive outcomesAchievement/performance, active learning, understanding3153915
Visual thinking/visualization193235
Problem-solving1424--
Spatial thinking/ability71247
Autonomy, independency71223
Memory retention47--
Mathematical/computational/critical thinking47--
Noticing/awareness, attention/concentration3558
Proof and reasoning2323
Creativity 1212
Cognitive load12--
Inquiry12--
Pedagogical outcomesUsefulness152523
Engagement132258
Competence development4712
Table 5. Drawbacks of AR/VR technology in mathematics education.
Table 5. Drawbacks of AR/VR technology in mathematics education.
CategorySub-CategoryARVR
n%n%
Pedagogical outcomesTechnological glitches, technical deficiencies91547
Cost4735
Time-consuming47--
Lack of user knowledge/experience in using AR tools35--
Health problems 12--
Socio-emotional outcomesBeing bored23--
Lack of interaction and communication1212
Cognitive outcomesCognitive load12--
Table 6. The list of the reviewed studies.
Table 6. The list of the reviewed studies.
Study NoAuthor(s)CountrySampleResearch MethodTechnologyDomain
1Cabero-Almenara, et al. [2]SpainUndergraduatesQuantitativeAR, VR, MRGeometry
2Demitriadou, et al. [4]CyprusPrimary school studentsQuantitativeAR, VRGeometry
3Medina Herrera, et al. [45] MexicoUndergraduatesMixedAR, VRCalculus,
Geometry
4Rebollo, et al. [61]Spain, ItalyPrimary school studentsQuantitativeARAlgebra
5Monteiro Paulo, et al. [5]BrazilUndergraduatesQualitativeARCalculus
6Kounlaxay, et al. [62]South KoreaUndergraduates, ISTsQuantitativeARGeometry
7Bos, et al. [63]NetherlandsUndergraduatesDesign-based researchARCalculus,
Algebra
8Jesionkowska, et al. [43]England, BelgiumSecondary school students, ISTsQualitativeARGeometry
9Hsieh and Chen [64]Taiwan, ChinaSecondary school students, ISTsMixedARAlgebra,
Geometry
10Alqarni and Alzahrani [65]Saudi ArabiaSecondary school studentsQuantitativeARGeometry
11Cangas, et al. [66]Spain, PolandSecondary school studentsQualitativeVRGeometry
12Ozcakir and Cakiroglu [67]TurkeySecondary school studentsQuantitativeARGeometry
13Ozcakir and Ozdemir [68]TurkeySecondary school studentsMixedARAlgebra,
Geometry
14Li, et al. [69]China, USASecondary school studentsQualitativeARCalculus
15Gargrish, et al. [70]IndiaSecondary school studentsDesign-based researchARGeometry
16Su, et al. [71]TaiwanSecondary school studentsQuantitativeVRGeometry
17Schutera, et al. [72]GermanySecondary school students, ISTsQualitativeARGeometry
18Mailizar and Johar [73]IndonesiaSecondary school studentsQuantitativeARGeometry
19Cai, et al. [19]China, USASecondary school studentsMixedARProbability
20Kellems, et al. [74]USASecondary school studentsQualitativeARAlgebra
21Morris, et al. [75]USASecondary school studentsQuantitativeARAlgebra
22Miundy, et al. [76]MalaysiaPrimary school students, ISTsMixedARAlgebra
23Moreno, et al. [77]MexicoUndergraduatesMixedAROther
24Xie, et al. [78]ChinaPrimary school studentsMixedVRGeometry
25Arican and Ozcakir [79]TurkeyPSTsQualitativeARGeometry
26Chen [44]TaiwanSecondary school studentsQuantitativeARAlgebra,
Geometry
27Cheng, et al. [80]Taiwan,
Australia
Secondary school studentsMixedARAlgebra
28Aldalalah, et al. [81]Saudi Arabia, Arab EmiratesSecondary school studentsQuantitativeARGeometry
29Root, et al. [82]USAAdultsQuantitativeAROther
30Ibili, et al. [83]Turkey,
Australia
ISTsQuantitativeARGeometry
31Akman and Cakir [84]TurkeyPrimary school studentsQualitativeVRAlgebra
32Wu [85]TaiwanPrimary school studentsQuantitativeARAlgebra
33Pozo-Sánchez, et al. [86]SpainSecondary school studentsQuantitativeARGeometry
34Ahmad [87]JordanSecondary school studentsQuantitativeARGeometry
35Saundarajan, et al. [88]MalaysiaSecondary school studentsQuantitativeARAlgebra
36Kellems, et al. [89]USASecondary school studentsQuantitativeARAlgebra
37Kazanidis and Pellas [90]GreeceUndergraduatesMixedAROther
38Kellems, et al. [91]USAAdultsQuantitativeARAlgebra
39Flores-Bascuñana, et al. [92]SpainSecondary school studentsQuantitativeARGeometry
40Gargrish, et al. [93]IndiaUndergraduatesQuantitativeARGeometry
41Rodríguez, et al. [56]SpainPrimary and secondary school students, ISTsQualitativeVRGeometry
42Jones, et al. [94]USAUndergraduatesQualitativeVRCalculus
43Akman and Cakir [95]TurkeyPrimary school studentsMixedVRAlgebra
44Haas, et al. [96]Luxembourg, AustriaPSTsMixedARGeometry
45del Cerro Velázquez and Morales Méndez [57]SpainUndergraduatesQuantitativeARCalculus
46Yiannoutsou, et al. [97]Spain, UKPrimary school studentsDesign-based researchVRGeometry
47Shi, et al. [98]ChinaSecondary school studentsQuantitativeVRCalculus
48Cahyono, et al. [99]Indonesia,
Germany
Secondary school students, ISTsDesign-based researchARGeometry
49Amir, et al. [100]IndonesiaPSTsQualitativeARGeometry
50Andrea, et al. [101]IndonesiaPrimary school studentsQuantitativeARGeometry
51Nabila and Junaini [102]MalaysiaPrimary school studentsQuantitativeARGeometry
52Awang, et al. [103]MalaysiaPrimary school studentsQuantitativeARGeometry
53Elsayed and Al-Najrani [104]Saudi
Arabia
Primary school studentsQuantitativeARGeometry
54Hanafi, et al. [105]MalaysiaPrimary school studentsQuantitativeARAlgebra,
Geometry
55Hanid, et al. [106]MalaysiaPrimary school studentsQualitativeARGeometry
56Miundy, et al. [107]MalaysiaPrimary school studentsMixedARAlgebra
57Ozcakir and Cakiroglu [108]TurkeySecondary school studentsDesign-based researchARGeometry
58Rohendi and Wihardi [109]IndonesiaSecondary school studentsQualitativeARGeometry
59Stotz and Columba [110]USAPreschoolersMixedARAlgebra
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Cevikbas, M.; Bulut, N.; Kaiser, G. Exploring the Benefits and Drawbacks of AR and VR Technologies for Learners of Mathematics: Recent Developments. Systems 2023, 11, 244. https://doi.org/10.3390/systems11050244

AMA Style

Cevikbas M, Bulut N, Kaiser G. Exploring the Benefits and Drawbacks of AR and VR Technologies for Learners of Mathematics: Recent Developments. Systems. 2023; 11(5):244. https://doi.org/10.3390/systems11050244

Chicago/Turabian Style

Cevikbas, Mustafa, Neslihan Bulut, and Gabriele Kaiser. 2023. "Exploring the Benefits and Drawbacks of AR and VR Technologies for Learners of Mathematics: Recent Developments" Systems 11, no. 5: 244. https://doi.org/10.3390/systems11050244

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop