SLR articles on VR and education
Tables 3 and 4 show some summarized systematic literature reviews (SLR) on virtual reality and education. There has recently been an increase in the number of documents, possibly due to current circumstances like the Covid pandemic and teleworking, which means that technological innovation in education systems has greater prominence than before.
Table 3 Summary of related systematic literature reviews The use of ICTs in education is commonplace, with VR no exception and often included in the teaching–learning processes. The evolution in the productivity of articles over the period analyzed clearly shows a rapid growth from 2015 to 2021, as shown in Fig. 3.
This growth is due to the development of specific content in VR, with more and more sectors involved such as: real estate, locomotion, security, and even education itself with the new e-Learning systems.
Performance analysis
According to Heradio et al. (2016) the main procedure for research performance evaluation is citation analysis, which means, the more citations of an article, the greater its influence in that field. The h-index is considered a suitable measure of the quantity and impact of the scientific output of the publications of a researcher.
Overview of the analyzed data set
The information from the analyzed data is summarized in descriptive statistics presented in Table 4. Considering the results obtained, we can say that RV is a topic of great academic interest as evidenced by the number of papers (718) and the more than ten average citations per article.
The average number of annual citations are presented in Fig. 4, while Fig. 5 provides an overview of the trends in the knowledge structure of the use of VR in education.
Figure 4 shows that the highest average number of citations per year were in 2010 with 6.9 citations per year and in 2014 with 7.3. Contrary to what the authors expected due to the important advances and changes in the market for VR, there were only 2.55 citations in 2016 continuing with little growth until 2018 and maintaining lower averages thereafter. 2020 and the current, available data for 2021 does not show an impact on citations due to the covid-19 situation.
Figure 5 shows that the main topics of the trends from 2010 to 2017 were about using simulation as a learning tool to obtain greater student attention. 2018 continued integrating technology into the teaching process with topics such as the virtual community of players of 2nd life with customizable avatars that allow players to enjoy a second life. This uses voice text messaging with people from different places and countries and integrates visualization tools. In 2019 education included the design of technological environments. 2020 showed an increase in the literature consulted about e-learning using tools such as virtual or augmented reality. This could possibly be because of the changes in education methods imposed by the Covid-19 pandemic and the change from presential to virtual teaching, which was made abruptly in some cases. It should be noted that 6 months into 2021 the trend is towards platforms that can be used to teach or attend lessons, i.e., information technologies and user acceptance of these take on greater importance and there is also increasing interest in artificial intelligence with deep learning that uses machine learning processes such as speech recognition or automated translation.
The journal with the most impact in this study is Computers & Education with an h-index of 16. This means that a number, h, of publications of the journal have been cited h times. An h-index of 16 implies that this number of publications have been cited at least 16 times. Table 4 shows the journals ordered by the number of documents published, as well as the impact measured with the h-index. We can say that the selected journals contain 207 articles in total, of which 40% correspond to 3 publications: International Journal of Emerging Technologies in Learning, Computers & Education and Virtual Reality (Table 5).
Table 5 Magazines with most productivity and impact Authors with most impact according to h-index
The authors with the highest productivity are shown in Fig. 6 and can be seen to be Chen W., Chen Y. and Lee J. Figure 6 orders the authors according to impact where it can be seen that Chen Y. and Jong M. have the highest impact with an h-index of 7, that is, each author has 7 papers with at least 7 citations each, which means that the author has been included in at least 49 publications (Fig. 7).
The most active authors in the last four years have been Chen W., Lee J., Kim, J., Ly Y. and Makransky G., as shown in Fig. 8.
Chen W. primarily studies problem solving in the classroom using VR technology, to assist in cognitive processing and knowledge transfer to the students. On the other hand, Lee J., studies the adaptation of the three-dimensional visualization made possible by immersive virtual reality.
Other authors, such as Kim J., jointly approach the analysis of VR and augmented reality (AR) whith the current skin electronics are summarized as one of the most promising device solutions for future VR/AR devices.
Ly Yan approaches the study of VR based simulation in hospital settings, that facilitates the acquisition of skills without compromising patient safety. Finally, Makransky's research deals with various aspects of RV in education, such as an important role in education by increasing student engagement and motivation.
The main affiliations of institutions can be seen in Fig. 9, which shows National Taiwan Normal University as being the most productive with 17 papers published in the analyzed dataset. In second position is Chinese University Hong Kong with 12 papers and in third position is Texas Aandm University with 11 papers.
Main documents and most frequently used words in the dataset
Table 6 shows the documents with the largest number of citations in this study. The authors of the document with most citations were (Merchant et al., 2014) with 452 citations and, in second place, (Huang et al., 2010) with 236 citations, both of which were published in the Computer & Education journal. In third place was (Jensen & Konradsen, 2018) with 196 citations in the Telematics and Informatics journal. When an article has many citations, it influences the researchers who develop the area under investigation (Rodríguez & Navarro, 2008).
Table 6 Most globally cited documents in the dataset The words which occur with the highest frequency in the dataset can be seen in Fig. 10. The first four words are related to the terms contained in the search strings, but the frequency and hierarchy follows the occurrences of the words “e-learning”, “environments”, “augmented reality”, “technology”, “simulation” and “learning systems”. This highlights the technological component of the field of education. The coincidence of keywords represents the knowledge structure of the literature (Cheng et al., 2018).
Scientific mapping analysis
A similarity measure known as the strength of association was used to construct the bibliometric maps (Cobo et al., 2011; Van Eck & Waltman, 2007). This allows a variety of scientific maps to be prepared which show the structural and dynamic aspects of the data obtained from the scientific research (Börner et al., 2003).
According to Cobo et al. (2011) the maps show the evolution of a field of research and the conceptual structure of the field can be found from the co-occurrence. Co-citation and bibliographic coupling allow us to analyze the intellectual structure of a field of scientific research and the social structure can be found by analyzing the authors, also known as co-authorship analysis, as well as the data found from the author's affiliations such as the organization or country.
Main topics in keywords plus according to factor analysis
Figure 11 shows a two-dimensional graph formed by the topic words in Keywords Plus of the cited papers. A multiple correspondence analysis can be used to summarize big data with multiple variables in a low-dimensional space, creating a two-dimensional map where the words near the central point of the group have received a lot of attention in recent years and those near the edge are topics which have been used less in research or have been incorporated into other topics (Xie et al., 2020).
The first cluster covers words related to VR display devices which are used by users of virtual reality educational products. When it is not clear which device to use in a curriculum, the relevant constituent components of immersive technologies which differentiate their roles must be considered. An example is for the two common modes of virtual reality displays, head-mounted display (HMD) and desktop computer (DT) which may affect spatial learning (Srivastava et al., 2019). On the one hand desktop-based VR has higher installation costs, while mobile device-based virtual reality cannot produce the same environment quality due to the limited processing power. A result of the lower environment quality has, in some cases, caused higher rates of nausea and blurred vision (Moro et al., 2017).
A person can interact in an environment created with VR in a seemingly real or physical way by using special electronic equipment, such as a helmet with a screen inside it or gloves equipped with sensors (Katsioloudis et al., 2017). Jensen and Konradsen (2018) identify situations where HMDs are useful for cognitive skill acquisition, such as remembering and understanding spatial and visual information, psychomotor skills like head movement, visual or observational exploration and affective skills for emotional control and response to stressful or difficult situations.
The second group covers VR applied to education, which includes topics such as technologies that allow the visualization of situations, which receive more attention from students and motivate them. Examples of this type of technology are virtual communities, educational games, interactive learning environments, educational technologies that improve the teaching process, online learning, user experience, immersive learning, immersive virtual reality and deep learning. There is a wide variety of possibilities, most of which are immersive, using helmets, games or applications that provide an interactive learning experience for students.
Learning environments using animation and multimedia highlight a change in VR learning which is more immersive, simulating the real world with 3D models that provide an interactive environment and reinforce the feeling of immersion. Using this technology, educators combine theory and instruction methods that allow intelligent use of these environments (Huang et al., 2010). There are many ways to create these environments with equipment like VR helmets for experiential learning in a virtual space (Kwon, 2019) and new and improved environments, such as the PILE System that integrates video capture technology into the classroom where interaction is made through physical movements (Yang et al., 2010). As technology advances, better graphics and virtually animated actors or avatars can be used. These improve the applications by being more motivating and enjoyable, even though the applications become more complex which may prevent a novice learner from learning effectively (Kartiko et al., 2010).
VR applications enable potential learning. Authors such as Johnson-Glenberg, (2018) explore applications of educational theory which design classes using immersive virtual reality with two unique attributes of VR, which are making the student feel present in any given situation and to be able to use gestures and perform manipulations in three dimensions. For decades the primary interfaces of educational technology have been the mouse and keyboard, but now highly immersive environments can enhance learning and affect the way content is retained and encoded.
Games are useful in educational technology with many examples available. Some of these are used to train students in safety through role-playing and social interaction (Palos-Sanchez et al., 2018), which allows students to understand the causes of accidents and inspect risks in an immersive environment provided by the game (Le et al., 2015). Interaction was found to play an important role in understanding mathematics and geometry with problem solving. A whiteboard and a virtual tool were used to solve problems individually or in pairs. Group learning was found to be more effective, although the results of the groups were different as the difficulty of the problems were varied (Hwang & Hu, 2013).
Articles were found concerning online learning which shares digital content and technological tools for e-learning and virtual reality learning. One of these articles compares techniques such as email, attachments, shared use of Web interfaces and a VR engine which provides a virtual interface. The results indicate that users completed their workflow 50% faster with the VR option (Lampert et al., 2018). Another application that marked a change in e-learning is an innovative tool for young adults with mild cognitive impairments. It is an immersive virtual reality game called "In Your Eyes" that focuses on skills related to spatial perspective involving all five senses which shows that an immersive world can be an excellent training method (Freina et al., 2016).
Co-occurrence network mapping
Bibliometric mapping of the keywords used by the author was done to gain a thorough understanding of the conceptual structure. Apart from the Keyword Virtual Reality itself, it highlights those related to education, e-Learning and Students. The co-occurrence analysis is shown in Fig. 12.
Keyword co-occurrence analysis is an effective tool for understanding knowledge structures and research trends. This makes it easier to understand primary and secondary publications (Altınay Ozdemir & Goktas, 2021). In this figure, one should start by distinguishing nodes by their size. This represents the number of documents, while the line between two nodes represents a link between the two groups. A link means a co-occurrence between the two keywords (Guo et al., 2019). If the line is short the link is strong and vice versa.
In this bibliometric analysis we mainly distinguish the following keywords: 'virtual reality', 'e-learning' and 'students' in a first cluster. Each cluster represents a keyword and shows the most linked and repeated keywords in the publications. All clusters have a different colour. In Fig. 12 a distinction is made between the red colour for this cluster and the blue colour showing the following main keywords: 'Education', 'Technology', 'augmented reality', 'performance', 'simulation' and 'environments'. Because this bibliometric study found few papers, the number of co-occurrence links between keywords was not excessive. As Fig. 12 shows, two groups had a stronger relationship: 'Education Technology for simulation environments with augmented reality' and 'Virtual reality for e-learning systems'.
Productivity mapping of items by country
The countries or regions with the highest document productivity in this study are the Republic of China with 273, United States of America with 242 documents, followed by South Korea with 57 and Spain with 50, as shown in Fig. 13. The high productivity of the United States is consistent with the bibliometric mapping for an analysis of studies on foreign language teaching in early childhood education by (Yilmaz et al., 2019) as well as the work of other authors (Hernández-Torrano & Kuzhabekova, 2019). China is a world power in VR technology and Chinese universities have been concerned to increase research in this field to meet the challenges posed by VR technologies. The main reason is that Chinese people are very prone to adopt emerging technologies, we can say that it is an important virtual reality market in the world.
In Fig. 14 we see how the main keywords, students, virtual reality, technology, e-learning, have a greater relationship with the countries of China and the USA, as well as the universities in the last column, which reflects a greater scientific production in topics related to technology applied to education.
VR technology in the educational field is opening up space through e-learning, game-based learning to mobile learning, going from simulation, machine learning to Deep Learning, where immersive virtual reality is part of the topics present as shown in Fig. 15.
In Fig. 15 we can see the thematic evolution through a Sankey energy diffluence diagram, which is a specific type of flow diagram. In this paper, based on the Sankey diagram, we visualise the thematic evolution over time in the field of VR and Education research. This figure helps us to understand the temporal evolution of the conditions in which the different topics in the field of Virtual Reality applied to Education have been flowing. In this Fig. 15 we can clarify quantitative information such as thematic flow, direction of thematic flow and conversion relationships (Soundararajan et al., 2014).
Collaboration between countries mapping
This map gives an improved understanding of the social structure, not only of authors, but also of the countries to which they belong. Figure 16 shows collaborative relationships between China, USA, Korea, and Canada, as well as Germany, Denmark and the United Kingdom, along with others, the collaboration between the USA and China are the most important.
Second stage analysis
This section briefly summarizes the most cited articles, and they are classified into categories, in the literature few authors provide us with a panoramic view of virtual reality technology applied to the educational field. In contrast to other authors (Zappatore et al. (2015) who perform an eminently quantitative approach in their analyses, this paper follows the line of Heradio et al. (2016) by providing a dual quantitative–qualitative approach. Thus, our analysis is not limited to counting articles, authors or journals, but describes and comments on the most relevant data for the RV community (Bardakci et al., 2022; Kushairi & Ahmi, 2021). The articles were listed in descending order according to the number of citations to find the main topics addressed and describe the documents that are considered the most important. All papers which had citations were classified and grouped into six categories: (a) papers about VR-based instruction and learning, (b) papers studying VR learning environments, (c) papers presenting the use of VR in different fields of knowledge, (d) papers describing learning processes that use VR applications, devices or games, (e) papers on research about learning processes using simulation, and (f) topics published during the Covid-19 pandemic.
VR-based instruction and learning
Among the most outstanding papers are the following: Merchant et al. (2014), Lee et al. (2010), Makransky and Lilleholt (2018) and Jensen and Konradsen, (2018). Jensen and Konradsen, (2018) seek to update knowledge on the use of head-mounted displays (HMD) in Education and training. The study identifies the acquisition of skills such as cognitive skills, i.e., remembering, understanding information, spatial and visual knowledge; as well as visual exploration or observation, among the most important are the affective skills related to control and emotional response to stressful or difficult situations. These learning tools enhance learning and are very useful in the educational field.
The most cited paper is Merchant et al. (2014). This work performs a meta-analysis that investigates the effectiveness of reality-based virtual instruction on learning outcomes. In order to do this, the authors researched the overall effect and impact of selected instructional design principles of VR technology-based instruction such as, games, simulation, virtual worlds, in higher education settings and as a result found that using games has a greater effect on learning than simulations and virtual worlds.
The study by Lee et al. (2010) examined how desktop VR (VR) enhances learning, finding that VR features have an indirect effect on learning. The learning experience was individually measured by psychological factors, such as presence, motivation, cognitive gains, control, and active learning, as well as reflective thinking which all affected the learning outcomes when using the desktop VR-based learning environment. Further research investigated how spatial ability and learning style enable instructional designers and VR software developers to improve learning effectiveness and therefore increase the amount the software is used. According to Makransky and Lilleholt (2018) much remains to be discovered about the impact and use of immersive VR in e-learning tools that impact students' emotional processes while learning.
Many authors investigate VR as a tool in learning processes. An example is Huang and Liaw, (2018) who explored how virtual reality technology actively focuses on the learner's interactive learning processes and attempts to reduce the gap between learner knowledge and real-life experience. Alfalah (2018) examined perceptions when using VR as a tool for education confirming that teachers and students are willing to use VR.
Allcoat and von Mühlenen (2018) assigned students into three groups who taught with different methods, 1) traditional book learning, 2) virtual reality learning and 3) video. The students were tested for their knowledge of the subject being taught before and after the classes, finding that participants in the virtual reality group showed better recall performance and more positive emotions than the other groups.
Hewawalpita et al. (2018) explored an improved configuration of massive open online courses. Two groups were used, one group were students who had already taken the traditional course and the second group started from scratch and were given virtual reality content. The results showed that the second group had significantly better performance and it was concluded that interactive learning content can be designed for the different learning needs of students.
Wang, (2018) proposed a distance learning virtual reality experiment with computers and VR technology and found practical reasons to promote the development of distance learning using computer.
In view of the works analyzed in the context of VR-based Instruction and Learning, we can say that the VR-based learning process is a useful tool for the educator, as it can replicate or complement traditional teaching methods. It is a fully effective concept even using basic forms, such as VR glasses or smartphones. This method is suitable for classroom teaching, distance learning, self-learning and other educational environments, and allows the simulation of scenarios that enrich teaching, even those dangerous experiments that cannot be reproduced in reality.
These papers conclude that it is essential to design useful and learner-friendly VR learning tasks and activities in order to improve learning outcomes. These activities should be adapted to learners with different learning styles and special abilities. Although this is a novel experience, the gap in these research models lies in the need for new longitudinal studies to verify whether improvements in teaching processes are maintained over time. It is necessary to identify differences in teaching processes, such as context, sample, duration, cultural background or learning programs with different content.
There is a need to deepen and explore the influence of virtual reality on the relationship between motivation and learning performance. That is, it is desirable to know whether students' disappointment can have a negative influence on their learning, using qualitative and quantitative methods in the study of prolonged periods.
VR learning environments
Geng et al. (2021) explore the pedagogical potential of Interactive Spherical Virtual reality based on video in geographic education, considering the perspective of teachers, they were given an introduction to this technology to know the acceptance, creation and experience, it was intended that teachers know the potential of this technology for teaching and learning purposes, the main concerns were the technological integration in pedagogy, they find that they need more professional development to design and refine this methodology. Perhaps it is more change adversity that is reflected in the need to ask for more training in the use of technology.
VR learning environments are explained by Huang et al. (2010) who indicate that there is a shift in learning from conventional multimedia to a more immersive, interactive, intuitive and exciting VR learning environment. It combines positive pedagogy and the use of technological innovations that are immersive and trigger the imagination of the learner.
Fowler, 2015 tried to give a more pedagogical description of adopting learning in three-dimensional (3-D) virtual learning environments (VLE) using a "design for learning" perspective that is useful for those who design learning activities in 3D VLEs, but considers that the risk of high-fidelity 3D VLEs is that using them to create virtual classrooms that "feel" and look like real classrooms means that they miss the opportunity to create pedagogically new and innovative learning environments.
Yang et al. (2010) investigated designing and developing a physically interactive learning environment. This was a PILE system that integrated VR video capture technology in a classroom. The group using the system showed a significant difference in pre-test and post-test knowledge. Makransky and Petersen (2019) believe that VR has the potential to enrich students' educational experiences. The authors investigated the affective and cognitive factors that play a role in learning when using desktop virtual reality simulation and concluded that learners can benefit from desktop virtual reality simulation in which emphasis is given to effective virtual reality features with a high level of usability.
The works analyzed emphasize that previous experiences with virtual reality in education have improved significantly. Although in the beginning they only used a mouse and keyboard as input devices, the benefits and educational effectiveness of 3D virtual learning and new virtual tools such as the PILE system, which allows students to interact with objects on the screen through physical movements, are gradually emerging.
Although technology has accompanied the teaching process exponentially in recent years, replacing traditional whiteboards with smart boards and VR elements, the gap in these research models lies in the need for new research is needed to explore the variables that may affect learning outcomes when using VR simulations. The described works suggest that it would be convenient to explore aspects such as duration, users' prior knowledge or dual cognitive/affective component.
The study of individual student differences, the long-term implications for knowledge acquisition, the frequent use of technology outside of teaching, the ease of use of different VR tools and the willingness of teachers to implement new VR-based utilities are also considered. This analysis evidences the importance of VR-based simulation processes, especially in areas of knowledge development that teachers deem necessary, allowing a balance between the cost and benefit of the experiences obtained.
Use of VR in various fields of knowledge
Osti et al. (2021) They seek to train construction workers using a novel VR system, this simulated a virtual training site, implemented a 3D training video with a VR head-mounted display, and compared it with a second group shown simple 2-D instructional video training, the first group presented better results in terms of retention, task performance, learning speed and participation. The practical application of VR as a teaching and learning tool is remarkable.
Schmidt and Glaser (2021) investigated the use of virtual reality by individuals with autism using 360-degree video modeling and headset-based virtual reality to investigate skills acquirement in adults on the autism spectrum in order to promote safety and the appropriate use of public transport. The results suggest a very positive learning experience and that the intervention is feasible and relevant for the unique needs of the target population.
Vélaz et al. (2014) studied the influence of interaction technology on the learning process when performing assembly tasks and learning processes using games and VR applications for industrial education. Sampaio et al. (2013) investigated the use of VR in civil engineering education by using it as a tool to create interactive applications as part of research work with students in which VR applications were developed for use in the construction industry.
A study by Eaves et al. (2011) determined the effects of two variations of real-time VR and feedback when learning a complex dance movement. Crocetta et al. (2018) presented and described a VR software package that helps in the rehabilitation of people living with disabilities. The findings of the study suggest that motor skills could be influenced differently depending on the environment and interface in which the software is used.
Learning with VR apps, devices or games
Chen and Hsu (2020) used a VR game-based English mobile learning application to investigate the effectiveness in English learning from a cognitive and psychological perspective, finding that interaction with the virtual reality application and the challenges of a game-based design allow students to enter the flow state easily and enhance their motivation to learn.
Authors M. Zhang et al. (2018) studied recent developments in game-based VR educational laboratories. According to the author there are several inherent disadvantages of VR that prevent its widespread deployment in the educational field such as unrealistic representation, lack of customization and flexibility, financial feasibility and the physical and psychological discomfort of users.
Sood and Singh (2018) considered that educational games for electroencephalography (EEG) can be widely used to improve the cognitive and learning skills of students. This can be achieved with the combination of VR and computing that provides accessible e-learning education worldwide. Psotka (2013) indicated that new technology such as VR and educational games can often disrupt established practices and are therefore considered disruptive technologies. The author believes however that they are appropriate for education and training today but have not been accepted in education due to changing social lifestyles.
Learning processes using simulation
Makransky et al. (2020) investigated the value of using immersive virtual reality (IVR) laboratory simulations in science education in two studies. The first study used an IVR laboratory safety simulation with pre- and post-test design. The second study compared the value of using IVR simulation and video simulation for learning the topic of DNA analysis. The results show that in both groups there were significant gains in self-efficacy and physical outcome expectations, but the increase in career aspirations and personal outcome expectations did not reach statistical significance.
Hsu et al. (2016) considered that visual simulation technologies have received considerable attention in learning. A vehicle driving simulation system was created to assist novice drivers in practicing their skills by considering various environmental driving factors that may be encountered while traveling. Dubovi et al. (2017) evaluated the effectiveness of VR learning simulation in pharmacology for higher education students requiring special skills to learn about medications and the procedure for administering them. The results revealed higher conceptual and procedural knowledge than with solely lecture-based learning.
Topics published during the Covid-19 pandemic
Wu et al. (2021) They use an immersive virtual reality approach based on video, they developed a landscape architecture VR learning system, due to the fact that during the Covid-19 pandemic the fields are closed, in addition, online education lacks the necessary scenarios for the courses taught during the pandemic, so better results and learning attitudes are achieved than students not subjected to this VR system. The importance of VR as a learning tool is evidenced in the face of the limitation of a real environment, here technology becomes an important ally.
Paszkiewicz et al. (2021) presented an educational process for Industry 4.0 that included the design, creation, implementation and evaluation of individual courses implemented in a virtual reality environment, identifying significant advantages and disadvantages of VR-based education. The development and implementation of appropriate courses in the virtual reality environment was found to reduce costs and increase the safety and efficiency of activities.
Yerden & Akkuş, (2020) examined the effects of the use of a Virtual Reality Supported Remote Access Laboratory (VRRALAB) system using remote access and virtual reality technologies on students' learning experience. The interactive use of a real device with a VR-supported remote access laboratory environment does not have any risks for novice users. The results indicate that remote access labs using virtual reality are likely to increase learning quality and student satisfaction levels.
Taçgın, (2020) investigated the characteristics of an immersive virtual reality learning environment (IVRLE) by evaluating perceived simulation effectiveness for student learning, attitude, and confidence by using gesture interaction to teach preoperative surgical procedures and concepts to undergraduate nursing students. Well-designed and targeted IVRLE was found to help to improve students' confidence in practical skills. Wang, (2020) applied virtual reality techniques in modular teaching to construct virtual simulation teaching resources and built two teaching modules that are visual, interactive, scalable, upgradable and optimizable. The results of the research suggest a new method of modular teaching and are a useful reference.