The following inclusion criteria were used: studies written in Spanish and English; peer-reviewed manuscripts; works with full-text access. As exclusion criteria, doctoral theses and manuscripts from unreliable sources were rejected. The sample for the systematic review comprises studies that have used VR, AR or MR in collaborative teaching experiences, and studies that have theorised about their possibilities in the educational setting.

The search for studies was done on 23 May 2023 in two of the most important online databases in the areas of social sciences and health sciences: ISI Web of Science and SCOPUS. By editorial decision, the search for studies was updated for the final time on 13 May 2024. Table 1 shows the details of the searches in JCR and in SCOPUS, using the following search term: [collaborative learning AND VR OR virtual reality OR AR OR augmented reality OR MR OR mixed reality]. The search in SCOPUS was filtered by title, abstract and keywords, and in ISI Web of Science by TOPIC, since 2009. A quantitative ad-hoc table was prepared, ordered by year and assigning a record number to the studies that permitted their subsequent selection in the classification phase.

During the review of the full text, the reviewer assessed the eligibility of the studies in accordance with the predefined inclusion and exclusion criteria. In this case, as one single person carried out the selection process in the study, it was important to ensure that the process was impartial and exhaustive. This was achieved by having a second reviewer independently examine a randomly selected subset of the studies to guarantee consistency in the selection process. With regards to the data extraction process, the data were extracted using a standardised form to guarantee consistency and precision. In this case, the data extraction was done by one single person and recorded in an Excel spreadsheet, which included information about the design of each study, the characteristics of the participants, the interventions, the results and the risk of bias, among other relevant aspects, helping ensure that the data would be complied in a consistent and precise way and thus improving the quality and reliability of the systematic review.

Moreover, to analyse the scientific production, the Guidance for Quality Assessment Tool for Systematic Reviews and Meta-Analyses of the National Heart, Lungs and Blood Institute (NHLBI, 2020) was used. The NHLBI guidance is a well-established and widely recognised tool in the field of health and medicine. Its use provides credibility and reliability to the assessment of the quality of the systematic review. It also provides a standardised and systematic framework to assess the quality of scientific evidence, including considerations on the methodology of the studies included and the clarity and coherence in the presentation of the results among other relevant aspects for the thematic area of the present review.

The Quality Assessment of Controlled Intervention Studies scale was also used to assess the original experimental studies in which an intervention or treatment is implemented and is compared with a control group. This scale centres on various key methodological quality domains, such as study design, random allocation, allocation concealment, blinding of participants and assessors, comparability of the groups at the start of the study, handling of deviations from the protocol and the attrition rate, among others. Each domain is assessed against a series of specific criteria, and a score is assigned to each study according to whether these criteria are fulfilled. This allows a quantitative assessment of the quality of the studies included in the review.

Finally, the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies scale was used to assess the original observational studies, such as cohort studies and cross-sectional studies, that did not involve experimental interventions. Like the scale for experimental studies, this tool centres on various domains of methodological quality that are relevant to observational studies, such as study design, the size and representativeness of the sample, the validity and reliability of the measurements, the handling of confounding factors and biases, and the follow-up of participants. Each domain is assessed by means of specific criteria, and a score is assigned to each study according to its fulfilment, which allows a quantitative assessment of its quality.

Both tools are designed to be used by systematic reviewers as part of the process of critical assessment of scientific literature. They allow a standardised and rigorous assessment of the methodological quality of the studies included in the review, something that contributes to the validity and reliability of the findings of the review. To measure the quality of the experimental studies and of the controlled intervention or observational and transversal cohort studies, the quality criteria from the NHLBI (2020) quality assessment tools were followed, using cutoff points that define a quality scale of 1 to 4 stars depending on the number of criteria that were fulfilled [1 star, ★☆☆☆ (< 3), 2 stars, ★★☆☆ (3–6), 3 stars, ★★★☆ (7–10), 4 stars, ★★★★ (11–14)]. The NHLBI quality assessment tools are not designed to assess the quality of articles in the field of education. However, responses provided above are based on the sections of the tool that are applicable to this review.

The studies are centred on exploring the benefits and applications of AR and VR in education, as well as in collaborative learning. Many of them also seek to comprehend how these technologies can improve social interaction, creativity and the idea creation in collaborative learning (Rodríguez et al., 2018; Sanabria & Lizárraga, 2017). Some of the studies included in the systematic review have the aim of exploring, developing and validating the effectiveness of VR and AR in collaborative learning (Ke & Hsu, 2015; Lindgren et al., 2016; Veer et al., 2022; Watson & Livingstone, 2018). These studies seek to investigate the ways these technologies can improve learning experiences, foster collaboration and improve academic performance in different areas, such as biology, technological education, geography and engineering, focussing on different age groups.

The studies also centre on the development of collaborative interfaces in VR and AR environments, as well as on identifying the effects of haptic systems and 3D models on learning (Kucukyilmaz & Issak, 2019; Webb et al., 2022). Furthermore, some studies have compared the results of collaborative learning in virtual reality and augmented reality environments with traditional text books. Some studies have sought to compare the performance of students in virtual settings with the use of conventional text books (de Back et al., 2020). Others seek to develop improved tools with AR and VR and assess their effectiveness in learning (Sanabria & Lizárraga, 2017), and others explore how technical limitations can be overcome to improve the experience of collaborative learning in AR and VR environments (Alhumaidan et al., 2018; Ahsen et al., 2019; Bekele et al., 2021; Jovanović & Milosavljević, 2022; Rusli et al., 2023)

Although some of the objectives of the studies that are centred on AR and VR can complement one another, there are some notable differences. Studies that centre on AR generally seek to examine how AR technology can improve the learning experience, for example, how AR can be used to improve comprehension of abstract concepts or to improve interaction between students and learning materials. Studies have also explored how AR can improve creativity and collaboration in class (Chung et al., 2021; Matcha & Rambli, 2013; Sanabria & Lizárraga, 2017; Strada et al., 2023).

In contrast, the studies that centre on virtual reality generally seek to examine how virtual reality technology can improve the immersive learning experience and provide students with a simulated environment for experiencing real-life situations (de Back et al., 2020; Lindgren et al., 2016; McArdle et al., 2011). Studies have also been done to explore how virtual reality can improve collaboration and problem solving among students (Wang et al., 2021; Webb et al., 2022).

In summary, augmented-reality studies centre on how the technology can improve comprehension and interaction, while virtual-reality studies centre on providing an immersive simulated learning experience. In conclusion, these studies underline the importance of mixed reality in collaborative learning and they suggest that these technologies have the potential to improve collaborative learning and students’ academic performance significantly. They also show that technologies can improve social interaction and creativity, significantly improving learning and collaboration in a close future.

With regards to the principal contributions of the articles reviewed, AR and VR are technologies with great potential in different areas of application, such as entertainment, tourism, architecture, medicine, education and industry. In particular, immersive virtual reality improves collaborative learning, especially in spatial awareness and navigation, and it can improve the participation of students in a collaborative problem-solving task and improve collaborative group communication (de Back et al., 2020). It is also worth mentioning the potential of collaborative virtual environments (CVE) for supporting socio-communicative interactions in people with autism spectrum disorder (ASD) (Wallace et al., 2017). Moreover, technological pedagogical content knowledge (TPACK) is important for teachers and students in designing and implementing educational technologies. In this sense, the design of mobile augmented reality devices tended to be better at promoting technological knowledge competences, while the visualisation on mobile phones with AR technology appeared to be better at supporting the development of content knowledge, in both cases increasing students’ scientific interest and collaboration skills (Ke & Hsu, 2015).

AR and VR technologies have great potential to improve collaborative learning and socio-communicative interaction in different areas of application, but it is necessary to continue researching the use of these technologies in real educational environments and to assess their efficacy for improving learning and group collaboration (Wallace et al., 2017). AR and VR are also effective tools for improving the education and understanding of the sciences, transforming passive learning into attractive interaction with 3D objects and improving students’ motivation for the intervention (McArdle et al., 2011; Stromberga et al., 2021; Tüzün et al., 2019; Watson & Livingstone, 2018; Webb et al., 2022)

As for learning social skills, intervention through AR/VR has proven to be effective in the majority of the studies, which suggests that combining these technologies can provide a more effective intervention (Mosher & Carreon, 2021). In the field of medicine, AR and VR also improve learning of practical skills and comprehension of anatomy. In particular, MR has shown value for facilitating meaningful learning opportunities and improving students’ knowledge of dynamic systems and control concepts (Richards, 2023). Likewise, VR and AR technologies are valuable tools that complement traditional teaching methods, providing an attractive and motivational educational experience. Nonetheless, their efficacy depends on various factors and requires more research.

According to Fu and Liu (2018), because of the specific nature of construction projects, the use of AR/VR (for example, investing in hardware and simulation of construction) can result in a high cost and time spend. For virtual reality, the main drawbacks are an effect of limited immersion, inadequate sensory feedback (that is, the virtual sense predominates with less presence of the sense of hearing, haptic sense and others), lack of comfort for users (motion sickness, difficulties with the body), and the cost or accessibility of this technology. On this line, according to Elmqaddem (2019), better accessibility of VR and AR is the primary element that should help to popularise these technologies. Google was the pioneer in proposing low-cost virtual reality platforms and headsets, starting with Google Cardboard in 2014 (the first virtual reality platform and virtual reality headsets). In 2016, Google presented a new virtual reality platform and headset called Daydream (which costs under 50 euros). Given that the high importance of accessibility of virtual reality, Oculus has been working on a project for new displays. To benefit from higher quality virtual reality headsets such as Oculus Rift, an expensive computer is needed (that meets the needs of Oculus Rift). And Oculus Rift itself, cost 700 euros. According to Miller et al. (2020) portable headsets, like Microsoft HoloLens, are increasingly common and are an example of new technologies that are mature for further research from an educational research perspective. Microsoft HoloLens is a portable computer running Windows 11 that allows interaction with MR. The head-mounted display (HMD) superimposes three-dimensional (3D) virtual images on the real world, enabling users to interact with these holographic projections through voice commands and gestures. According to Sonntag and Bodensiek (2022), most of the research in this field is still limited to tablet-based augmented reality (AR), although MR through HMDs offers advanced possibilities to support students in laboratory-based learning activities: use of an HMD allows experimentation with the hands free, virtual representations or simulations can be shown and perceived three-dimensionally and superimposed on the physical environment more naturally, and intuitive gesture-based interaction with the virtual elements. Therefore, MR-HMD is able to combine laboratory learning with the advantages of interactive computer simulations such as PheT. The few studies that explicitly use MR-HMD indicate a positive impact on conceptual knowledge (Scaravetti & Doroszewski, 2019; Sonntag et al., 2019). The MR-HMDs recently available on the market, such as Microsoft HoloLens 2, which are used in the study by Sonntag and Bodensiek (2022), feature integrated eye tracking functions.

On the other hand, McArdle et al. (2011) suggested that while CLEV-R provides asynchronous access to reading material through the library, synchronous reading is where most learning occurs. As it offers both forms of e-learning, students can decide which they find more beneficial. CLEV-R also offers few opportunities for asynchronous online communication, such as message boards, email and forums. These can easily be incorporated into the design and form the focus of future studies to determine how they compare with the real-time communication that CLEV-R currently offers, and, ultimately, improve the students’ learning experience. However, there are technical limitations on the use of MR technologies, especially in the AR subcategory, such as response time in collaborative environments. There will also be difficulties replicating MR experiments in real educational environments and scenarios, and an absence of assessment processes in collaborative educational environments that incorporate technologies in the continuum of virtuality with the introduction of new optical head-mounted displays (OHMD), such as HoloLens, Oculus Rift, and HTC Vive.

As for the difficulties of applying these technologies in an educational context, Jovanović and Milosavljević (2022) suggest that the educational aspects and problem solving through 3D avatars aspects could be a good way of personalising the experience and attracting users so that they support the platform. Nonetheless, monitoring students’ activities is difficult because attention is centred on the virtual environment. It is suggested that real world class sessions are more reliable for the activities of the students. Alalwan et al. (2020) indicate that there is a shortage of guidelines for VR, with a lack of long-term participation in AR, a lack of instructional design, a lack of competence, and a lack of focussed attention in VR and AR being the most important factors to address to ensure its usability in the educational system.

As for interaction, according to Wanis (2019), VR technology is centred on replacing reality with a complete virtual environment. To manipulate virtual content in the AR and VR work space, adequate interaction is needed. Interaction is one of the most studied topics in research into virtual reality and augmented reality. Interaction with AR should work well when it is a case of using real objects to manipulate virtual objects.

The integration of MR technologies and mobile visualisation in higher education is an important contribution that can improve educational practice. AR, VR, and MR have the potential to improve scientific comprehension and education, and the combination of these technologies can provide a more effective intervention in the teaching of social skills. Although use of these emerging technologies in education has benefits, there are also challenges that must be faced, such as the lack of competence, limited instructional design, the lack of focussed attention, the lack of time, and limited environmental resources.

Augmented reality (AR) and virtual reality (VR) technologies have emerged as powerful tools in the field of education, especially for fostering collaborative learning. The studies reviewed reflect a varied focus, from exploring their benefits and applications to development of collaborative interfaces and comparison with traditional teaching methods. The following conclusions stand out in this review:

- The studies reviewed centre on exploring how AR and VR can improve the experience of collaborative learning and foster social interaction, creativity, and generation of ideas. Furthermore, the effectiveness of these technologies in various academic and age groups is investigated. VR is oriented towards the creation of simulated environments for immersive experiences, while AR is focussed on improving comprehension and interaction. Both technologies display significant potential to improve academic performance and group collaboration.

- Despite their potential, the use of AR and VR in collaborative environments faces significant challenges. These include high implementation costs, technological limitations such as inadequate sensory feedback, and limited accessibility. Furthermore, the lack of competence and appropriate instructional design, along with the lack of high quality research works, represent barriers to their effective adoption in educational environments.

-Although the studies reviewed display promising results, further research is needed to fully understand the impact of these technologies on collaborative learning. It is crucial to consider the limitations identified and develop effective strategies for their implementation in real educational environments. This includes improving competence in the use of these technologies, designing effective pedagogical interventions and assessing their long-term efficacy.

- In light of the results, greater quality is needed in the experimental studies that consider collaborative experiences through the use of AR, VR, and MR. Moreover, further research is needed to determine the effectiveness of these technologies in collaborative learning in comparison with other teaching tools.

Possible selection bias stands out as a potential limitation of the review, as this was done by a single reviewer, which could introduce biases. Furthermore, although an exhaustive search strategy in two major databases was used, the breadth of the sample of studies included might have been limited by restricting the language to Spanish and English and excluding doctoral theses. Moreover, despite the efforts to guarantee the exhaustiveness of the search, it is possible that some relevant studies were not identified and so are not included in the review. This could be because of limitations in the search terms used or lack of access to particular databases or information sources. Finally, there might be limitations in the assessment of the methodological quality, as, even though established tools were used to assess the quality of the studies included, such as the NHLBI quality assessment guidance, these tools might not be fully applicable to the field of education. This could limit the validity of assessments of methodological quality and, so, the reliability of the findings of the review. Despite these limitations, the systematic review provides an exhaustive overview of the current state of literature on the use of AR, VR, and MR in collaborative experiences in the educational context. Nonetheless, caution is recommended when interpreting the results and considering these limitations when applying the conclusions in educational practice or when designing future research in this field.

Regarding future lines of research, more research is needed to assess the effectiveness of AR and VR technologies in collaborative learning in comparison with other teaching tools. This includes studies that examine the impact on students’ academic performance, social interaction and creativity. It is also crucial to investigate strategies to improve competence and training in the use of AR and VR technologies among educators and students. This could include the development of specific training programmes and the creation of clear guidelines for the design and implementation of educational activities based on these technologies. Finally, research into how to design effective educational settings that appropriately integrate AR and VR technologies is recommended. This includes exploring different pedagogical focuses and assessment methods that make the most of the potential of these technologies to improve collaborative learning. As a corollary, while AR and VR offer exciting opportunities to transform collaborative learning, it is necessary to tackle key challenges and continue researching to exploit fully their potential in the educational environment.