Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design

Due to the multidisciplinary nature of VR research and its pedagogical applications, it is important to define key terms used. VR can broadly be broken down into two main categories: desktop VR (D-VR), and immersive-VR (I-VR). D-VR is typically classified as non-immersive, in that a headset is not used, and the participant will be controlling and manipulating the virtual environment on a computer screen with traditional keyboard and mouse hardware (Lee et al. 2010). On the other hand, I-VR is typically multi-modal in nature by providing a sense of immersion in the environment through 360° visuals by aid of a HMD, auditory stimulation through the use of earphones, and increasingly the proprioception of limbs by way of controllers and tracking (Freina and Ott 2015; Howard-Jones et al. 2015; Murcia-López and Steed 2016). Although there are a range of HMDs on the market, from high-end hardware like the HTC Vive, to viable low-cost options like the Google Cardboard, they all utilise the same core principals of operation (Brown and Green 2016). Typically, a HMD will feature a set of embedded liquid crystal displays (LCD) which will present each eye an image from a slightly different angle. This mimics natural optic function by allowing the wearer to view a stereoscopic image complete with depth perception and a wide field of view. Mobile VR headsets can achieve the same effect using a single display by dividing the screen down the middle and presenting each half to the corresponding eye. Therefore, the current review defines a HMD as a device worn over the head, which provides a stereoscopic computer-generated or 360° video image to the user. This includes tethered (connected to a computer), stand-alone (no computer needed), or mobile VR headsets (mobile/cell phone connected to a HMD).

There have been a number of systematic reviews that have previously explored the relationship between VR and pedagogical attainment. Lee (1999) reviewed 19 studies from as far back as 1976 and found that 66% of students in simulation groups outperformed those in their respective control groups. However, this review did not focus exclusively on an educational level or age range, so featured both young kindergarten children, as well as higher education students. As a result, the generalisability of VR’s effectiveness as a pedagogical method is difficult to ascertain, with significant differences in age, task difficulty, and applications. Furthermore, all the studies are dated in terms of the technology utilised and feature early D-VR programmes and rudimental computer simulations. This early technology may be primitive when compared with the high-fidelity graphics and immersive components of contemporary technology. Nevertheless, these early studies do help exemplify that the use of technology in education is not a new concept, and computer-based simulations have long been employed as a way of facilitating learning.

A more recent analysis was undertaken by Merchant et al. (2014), and looked at three specific sub-categories of VR: games, simulations, and virtual worlds. Games give the actor autonomy and freedom to move around the virtual world, testing hypotheses, achieving goals, and eliciting motivation and learning through immersion (Gee 2004). Simulations attempt to recreate a real-world environment that can help facilitate learning by allowing for the testing of variables and resulting outcomes. Finally, virtual worlds can provide an immersive or non-immersive sense of presence in a three-dimensional (3D) world, and the ability to manipulate, interact, or construct objects. Furthermore, virtual worlds can give the opportunity for multiple users to interact with one another within the digital environment (Dickey 2005). The meta-analysis showed that although game-based VR produced the highest learning outcomes, simulations and virtual worlds were also effective at increasing educational attainment. Once again, the limitation of this review is that it did not restrict its analysis to exclusively one domain of education. Although higher education made up the greatest number of studies, research from elementary and middle school were also included in the analysis.

One of the most recent systematic reviews to look exclusively at I-VR through the utilisation of HMDs was carried out by Jensen and Konradsen (2018). In their comprehensive search of existing literature published between 2013 and 2017, the review identified 21 quantitative and qualitative papers that focused on both learning outcomes in I-VR, and subjective attitudes and experiences on the part of the user. The review found limited effectiveness of HMD in the acquisition of cognitive, psychomotor, and affective skills when compared with less immersive technologies. However, Jensen and Konradsen (2018) did highlight the relatively low quality of studies included as a concern, and this may impede the ability to draw firm conclusions about the educational utility of I-VR.

There are several fundamental reasons that necessitate an updated assessment of the topic area, such as the increase in relevant published literature, as well as the narrow scope of previous reviews. The last major review looking at I-VR and HMDs as an educational tool was carried out by Jensen and Konradsen (2018), with the most recent studies featured in that paper being published in 2016. Since then, there has been a significant increase in relevant published literature, with > 70% of the papers included in the current review being published since 2017, and therefore not included in the previous systematic review. Additionally, unlike previous reviews, the current examination of I-VR’s pedagogical utility focuses exclusively on studies where I-VR is directly compared to a less immersive method of learning. As a result, the current paper is able to highlight not only whether I-VR is an effective medium, but also whether it is more effective when compared to alternative methods. Additionally, no other systematic review looking at I-VR and HMDs has had a particular focus on the experimental design, assessment measures, and intervention characteristics of the included studies. The review also addresses the underlying methodology of the included studies, to offer an understanding of how I-VR is being employed in experimental literature. Based upon the findings of previous studies as well as areas yet to be sufficiently explored, this paper has a number of core research questions:

The current systematic review included peer-reviewed journal articles and conference proceedings that passed all the inclusion criteria detailed. An initial scoping review identified seven databases that could be utilised in a comprehensive literature review, as well as associated keywords and search terms. These included Web of Science (Core Collection), Science Direct, Sage, IEEE Xplore, EBSCO, Taylor & Francis, and Google Scholar. These databases encompass a mixture of general, social science, and technological literature.

Each of the seven databases was searched using a series of keywords based on the following Boolean logic string:

("Virtual Reality" OR "Virtual-Reality" OR “Immersive Virtual Reality” OR “Head Mounted Display” OR “Immersive Simulation”) AND (Education OR Training OR Learning OR Teaching)

Due to the scope and parameters of the research objectives, only peer-reviewed literature published between January 2013 and December 2018 was included in the final review. Early access articles due to be published in 2019 were also included if these were found using the database searches. Date criteria was based upon an initial scoping review that found a substantial growth in relevant I-VR literature from 2013 onwards. A major contributing factor was the release of the Oculus Rift Development Kit 1 (DK-1) in early 2013, which is regarded as one of the first economically viable and high quality HMDs that could be used both within educational institutions, and at home (Lyne 2013).

The literature search across the databases yielded more than 12,000 references from a variety of sources. After the removal of duplicate records, 9,359 unique references were included for the title and abstract screening stage of the review.

The open and general nature of the search string used led to a large number of references being returned for screening. As Jensen and Konradsen (2018) already alluded to in the last major review, VR research transcends various academic disciplines. The result is a lack of a clear taxonomy of definitions and terms. This means a wide net must be cast to ensure comprehensive capture of relevant material. This review defined I-VR as either a completely computer-generated environment, or the viewing of captured 360° video through the use of a HMD. Studies that utilised surgical or dental simulators and trainers such as the da Vinci Surgical System, were excluded as these represent a separate domain of both technological and pedagogical application. For example, surgical simulation based VR typically combines computer-generated visuals with simulated surgical tools, haptic feedback, and robotic components (Li et al. 2017). This type of technology would therefore not be applicable for general pedagogical application. Additionally, references were excluded if they: (1) focused on using I-VR as a rehabilitation or therapeutic tool; (2) were not in English; or (3) where the full-text was not available.

After title and abstract screening was performed, 197 references remained to be included in the full-text review. Each reference had to pass an inclusion flowchart based on each of the following criteria:

After full-text screening, 29 references passed all stages and were included in the systematic review. See Fig. 1 for a summary of the selection process by stage.

Inter-rater reliability checks were conducted at the title and abstract screening stage to assess the agreement of included studies. There were four individual evaluators that assessed the suitability of each reference based upon the inclusion criteria, which yielded an average agreement of 96%. Where any disagreement existed, the paper was discussed among all assessors until a unanimous decision was reached as to its suitability.

To assess the quality of the studies, the Medical Education Research Study Quality Instrument (MERSQI) was used (Reed et al. 2007). Although this tool was primarily designed to examine the quality of studies in the field of medical education, it is in practice subject neutral. As the MERSQI assesses not only the quality of experimental design and outcomes measures, but also the assessment instrumentation used, it was viewed as a suitable and comprehensive tool for quality appraisal. In addition, the same instrument was used in a previously peer-reviewed systematic review examining VR, by Jensen and Konradsen (2018).

The MERSQI tool covers six quality assessment domains. These include: study design, sampling, type of data, validity of evaluation instrument, data analysis, and outcomes. Each domain is scored out of three, with a maximum overall score of 18. Unlike Jensen and Konradsen (2018), the current review gave full points in the study design category for experimental trials with participant randomisation, as well as appropriate pre-intervention measures. This decision was made as true randomised control trials featuring random sampling is unrealistic in I-VR pedagogical research, as the participant sample can only be drawn from an educational establishment.

The first domain examined for quality was the study design of the papers. There were 20 studies (69%) that featured an experimental design with stated random allocation of participants between control and experimental group. The review featured nine studies (31%) that were quasi-experimental in nature, meaning there was non-random allocation of participants into experimental groups.

In terms of the type of data presented, all included studies featured an objective measure of learning outcomes such as test scores or completion times. No studies used self-assessment on the part of the participant to gauge learning outcomes.

The most pronounced weakness of the studies included in the review was the validity of the evaluation instrument used to assess learning outcomes. This domain pertained to the physical assessment instrumentation such as the quiz, test, or questionnaire that was given to the participant. Only six of the included studies (21%) reported the internal structure sufficiently through dimensionality, measurement invariance, or reliability using the criteria set down by Rios and Wells (2014). In addition, only 10 studies (34%) stated how the content was validated, with the majority (N = 19) not reporting this information. Only three studies (Kozhevnikov et al. 2013; Makransky et al. 2017; Molina-Carmona et al. 2018) appropriately outlined both the internal structure and validity of evaluation content. The majority of studies (N = 16) did not report either item.

Of the 29 studies in the current review, 26 scored full marks on the data analysis domain with both an appropriate and sufficiently complex analysis and reporting of the findings. Three studies scored lower than this due to reporting descriptive statistics only (Angulo and de Velasco 2013; Babu et al. 2018; Ray and Deb 2016).

Overall, the average quality score of a study in this systematic review was 12.7 with a range of 10.5–14.5 (SD = 1.0). This was 1.8 points higher than the review carried out by Jensen and Konradsen (2018), which could in part be due to differences in study design criteria which was previously outlined. A full summary of the MERSQI scores for each study can be found in Table 2 in the Appendix.

Table 1 provides a summary of all 29 articles that were included in the review. Studies were first categorised by the population that was sampled. Most I-VR studies took place in a higher education establishment (college or university) using undergraduate or postgraduate students (N = 25). A smaller number of studies used high school pupils (N = 2), or adult education students (N = 2) such as those in vocational or work-based programmes.

Each of the included studies were then examined for the topic and subject area they pertained to. This was based upon the nature of the VR experience, participant pool, and intervention. In total, six main subject areas were identified. This included: medicine (N = 4), science (biology, chemistry, and physics) (N = 13), social science (human geography) (N = 1), computer science (N = 2), engineering and architecture (N = 7), and safety education (N = 1). One of the included studies (Molina-Carmona et al. 2018) did not neatly fit into one of the pre-defined categories as it utilised I-VR to teach abstract spatial concept abilities to multimedia engineering students. It was therefore categorised as ‘other’. Figure 2 shows the percentage of papers included by subject area.

In addition to the subject area, the learning outcomes were also categorised into three specific domains based upon the findings of previous systematic reviews, as well as the taxonomy of learning developed by Bloom et al. (1956). The first was cognitive which related to studies that intended to teach specific declarative information or knowledge. The second was procedural which intends to teach the user how to perform a specific task or learn psychomotor skills that pertain to a certain activity. Finally, the third learning outcome was affective skills which can be defined as a growth in areas relating to emotion and attitude. Most of the included studies (N = 24) concentrated on the cognitive domain, with two studies focusing on purely procedural and psychomotor skills. The remaining studies were a blend of two domains with Sankaranarayanan et al. (2018) and Smith et al. (2018) examining both cognitive and procedural skills, and Gutiérrez-Maldonado et al. (2015) utilising both cognitive knowledge and affective awareness in psychiatric diagnosis training. Figure 3 shows the percentage of studies included by learning domain.

For I-VR to gain wide-spread acceptance as a reliable pedagogical method, it must be shown to confer a tangible benefit in terms of learning outcomes over less immersive or traditional teaching methods.

The findings of the review suggest a relatively homogenous application of I-VR in terms of both the subject areas represented, as well as the learning domain being taught. Almost 70% of the studies were from the field of science or engineering, with other subjects being marginally represented. It is worth noting, however, that although medical disciplines made up a small proportion of the studies included (14%), this was because most medical applications of I-VR feature surgical simulators and therefore were not part of the current review’s inclusion criteria. Most studies utilised I-VR as a way of teaching cognitive skills, with only a handful examining the procedural or affective applications.

The findings of the review raise several issues when trying to assess the general effectiveness of I-VR in education. Similar to the findings of others (e.g. Jensen and Konradsen 2018; Radianti et al. 2020), the arts, humanities, and social sciences were underrepresented in in the current review. This makes generalisable conclusions as to the cognitive benefit of the technology in these subjects challenging. One major reason for this under representation may be the lack of I-VR learning content, experiences, and teaching tools. Jensen and Konradsen (2018) highlighted that instructors are restricted to the material published and produced by VR designers, and this may not necessarily meet the individual needs of the teacher, or the learning outcome trying to be achieved. The skillset needed to produce and create wholly virtual environments that can be rendered and displayed in a HMD is still demanding, despite the release of affordable VR creation suites. Therefore, the bespoke I-VR experiences required to teach social science lessons (or indeed any subject) is completely dependent on an appropriate I-VR tool already existing or having the technical proficiency to create one. A potential solution to the lack of bespoke material could be the examination of the pedagogical effectiveness of HMD 360° video in the classroom, as opposed to computer-generated environments. This content is comparatively easier to create using appropriate video equipment and can be tailored to the individual needs of the instructor or student group. Widespread research that examines the potential of I-VR in a multitude of diverse disciplines and learning domains will continue to be constrained by the availability of the requisite material. That is until such a time where bespoke and individually tailored I-VR experiences become more accessible.

One of the most striking characteristics of the assessment instrumentation used in the studies was the reliance on the MCQ to assess learning outcomes. Although there have been many debates on the respective advantages and disadvantages of utilising the MCQ, it has generally been considered that it is most appropriate for testing large amounts of surface knowledge over the course of an entire module or syllabus (Excell 2000). As O’Dwyer (2012) points out, the assessment instrumentation encourages comprehensive learning of the entirety of the taught material, as opposed to just specific components. However, since most of the studies featured single interventions of between 6 and 30 mins, doubts are cast on whether MCQs are the most appropriate way to assess learning. Since the MCQ was most commonly administered immediately after the I-VR experience, much of the information may still be stored in short-term memory, and this may not give an accurate reflection of more comprehensive learning or long-term retention.

A second disadvantage associated with the heavy reliance on the MCQ is the limited breadth of knowledge that can be assessed. In Jensen and Konradsen’s (2018) systematic review, the researchers found that none of the cognitive studies went beyond teaching lower level cognitive skills as defined by Bloom’s taxonomy (Bloom et al. 1956). Similar results were found in the current review, with most studies requiring only a knowledge of previously learned material to successfully achieve the desired learning goal. Previous research on pedagogical assessment material (e.g. Ozuru et al. 2013) has suggested that the MCQ cannot assess higher levels of cognitive understanding or conceptual knowledge. Therefore, it may not only be the nature of the I-VR experience itself that restricts the learning of higher level cognitive skills, but also the restrictive nature of the assessment instrumentation that may impede an appropriate demonstration of learning outcomes. The utilisation of short or long form answers could be able to provide a more appropriate measure of the depth of learning achieved, giving the student an opportunity to demonstrate their conceptual knowledge of a given subject. Furthermore, I-VR research could benefit by expanding the very definition of what constitutes a learning outcome. This could be achieved by not relying exclusively on test score comparisons, but rather examine how I-VR could be used to foster deeper conceptual understanding through experiential learning and subsequent classroom discussions with peers or instructors.

The current review examined how I-VR is being utilised in experimental and applied settings, and the implications this has for assessing its pedagogical suitability. In most studies, the participant took part in a single I-VR experience that was also short in duration. This presents several key challenges. Most importantly, the novelty of the I-VR technology itself may have impeded the learning experience of the user, especially if they had never used the technology before or were unfamiliar with it. This seemed to be demonstrated by Ray and Deb (2016) who found that in the initial sessions of I-VR learning, performance was on average poorer than those who underwent traditional teaching methods. It was only after the participants began to become familiar with the technology (on session number five) that learning surpassed the control group. Similarly, studies that allowed for extended exposure to I-VR (e.g. Akbulut et al. 2018; Alhalabi 2016; Molina-Carmona et al. 2018), either through free navigation, repeated sessions, or scheduled class time, tended to show an advantage of using I-VR over non-immersive or traditional methods. It is therefore important to address the potentially negative influence that I-VR’s novelty as a learning tool may have, especially when outcomes are directly compared to another medium or method. Scepticism for media comparison studies was highlighted in the 1980s by Clark (1983), and then later re-addressed by Parong and Mayer (2018). As Parong and Mayer (2018) put it, the side-by-side comparison of two learning methods is an “apples-to-oranges type of comparison” (p. 788). This “apples-to-oranges” comparison is made starker when considering that I-VR is an unfamiliar technology to most in an educational capacity, and its pedagogical outcomes are being directly compared with familiar methods such as textbooks or lectures. It is important to consider that the novelty of HMDs and I-VR may hinder learning outcomes and classroom application, and it is therefore prudent to ensure that the degree of familiarity with I-VR technology is factored into any direct comparison with other methods. In practice, this could mean that participants require extended familiarisation trials or free navigation before the start of experimental studies as a means of mitigating against potential problems caused by technological novelty.

In addition to the short intervention and exposure time, most studies did not complement I-VR with an additional method of teaching or self-learning. The limited number of studies that did tended to utilise web-based textbooks or modules, as well as lectures and scheduled class time. Encouragingly, those studies that combined or supplemented traditional class-based learning with I-VR (e.g. Akbulut et al. 2018; Fogarty et al. 2017; Johnston et al. 2018; Sankaranarayanan et al. 2018; Yoganathan et al. 2018) tended to show a learning advantage. This suggests that I-VR may be best employed as form of blended or multi-modal learning to supplement and complement class-based instruction (Garrison and Kanuka 2004). An area for investigation would be to examine I-VR’s application longitudinally in a natural classroom environment. The current review contained only a limited number of studies that employed this approach, however, by implementing and studying how I-VR can be adopted and integrated into a module or syllabus, a clearer picture of its capabilities can emerge.

Learning theories ultimately provide a theoretical framework and foundation as how best to design educational interventions (Pritchard 2017; Schunk 2011). However, the review found that few papers explicitly state that any predetermined learning theory was used to advise the characteristics or methods of the study. Similar findings were reported in a systematic review by Radianti et al. (2020) examining I-VR use in higher education exclusively. Radianti et al.’s (2020) review found that in around 70% of the 38 studies included, no learning theory was mentioned as forming the foundation of the VR activity. Several studies have shown that educators regard clear pre-defined intervention characteristics and objectives as essential components of I-VR teaching (Fransson et al. 2020; Lee and Shea 2020). It is therefore essential that future experimental and applied research is based on a sound theoretical basis that can advise how the technology can be appropriately utilised and assessed.

The current review examined learning outcomes across three domains: cognitive, procedural, and affective. By far the most popular domain was the teaching of cognitive skills and knowledge which made up 83% of the studies in the current review. Around half of those demonstrated a positive effect on learning when using I-VR over less immersive pedagogical methods. Most of the remaining studies showed no significant effect either way, with only a small number of papers exhibiting detrimental results. Researchers have suggested that the increased levels of immersive content that stimulate multisensory engagement can ultimately lead to more effective learning outcomes (Webster 2016). When this is implemented in cognitive learning activities that require a high degree of spatial understanding and visualisation (e.g. Maresky et al. 2019), I-VR can allow the user to gain insights that are difficult to reproduce in reality. This review has already identified scientific subjects such as biology and physics as promising avenues for educational I-VR implementation. However, other scientific disciplines that require abstract or conceptual understanding (e.g. chemistry, mathematics) could also benefit from the visualisation afforded by I-VR.

Studies that utilised I-VR for the teaching of procedural skills and knowledge produced encouraging results, with three of the four studies finding a significantly positive increase in learning (Bharathi and Tucker 2015; Sankaranarayanan et al. 2018; Yoganathan et al. 2018). Interestingly, two of the studies featured a transfer component by having the user first practice the procedure in I-VR, and then use this form of experiential learning to complete a task in the real world. Yoganathan et al. (2018) had students practice how to tie a surgical knot in I-VR and then complete this task for real in-front of an expert. Sankaranarayanan et al. (2018) had medical students learn how to deal with an operating theatre fire by first practicing the procedure in I-VR, and then applying this knowledge to a mock emergency in a real operating room. Both studies found a positive effect of using I-VR as the training method by demonstrating improved results when performed in a real environment. These are encouraging findings for I-VR’s effectiveness in psychomotor and procedural education, as there has been a degree of scepticism over whether I-VR simply produces a “getting good at the game” effect. For instance, Jensen and Konradsen (2018) point out that the honing of procedural skills within I-VR may simply lead to the participant becoming proficient when performing the task virtually, and this may not necessarily transfer to the real world. The current review has identified that the two procedural studies that implemented a transfer task did indeed demonstrate a significant benefit to using I-VR as an initial education method. This demonstrates that virtual training can be a successful precursor to implementation in the real world. This suggests that I-VR could be useful in educating students in dangerous vocational subjects such as electrical engineering without risk to themselves or others. However, this view is based on a small number of studies, and it is therefore important that future procedural tasks utilise a transfer activity to understand the potential scope and parameters surrounding I-VR training and real-world application.

Only one of the studies had a firm focus on the training of affective skills, namely by using I-VR as a way of teaching diagnostic interview techniques in a psychiatric setting (Gutiérrez-Maldonado et al. 2015). Although this study found no clear advantage to using I-VR, other research out with the domain of education has demonstrated promising results in utilising the technology for affective and behavioural change. This included applying the technology successfully in areas such as exposure therapy, anxiety disorder treatment, and empathy elicitation (Botella et al. 2017; Maples-Keller et al. 2017a, b; Schutte and Stilinović 2017). As a result of the strong non-educational body of literature suggesting I-VR can facilitate affective and behavioural change, future research should examine how this can be applied in an educational context, and then transferred to real-world scenarios. For instance, in their psychiatric interview experience, Gutiérrez-Maldonado et al. (2015) had users interact solely with virtual avatars, and did not have the participants demonstrate their learning with a real actor or patient. Therefore, just like with procedural skill acquisition, affective I-VR experiences should seek to understand how virtual learning can then be applied to real situations.

The current review has been able to identify a body of experimental and applied research that show the potential benefits of using I-VR in education. It has already been noted that I-VR has traditionally been used to teach low level or fundamental skills and knowledge, and has not necessarily been used to facilitate what Bloom et al. (1956) would consider higher level learning. This would include analysing and evaluating experience. By expanding the definition of learning outcomes to encompass potential benefits such as an increased depth of understanding or the ability to identify complex themes, pedagogical practice can take advantage of the inherent strength of the medium. These should be comprehensively analysed to investigate learning outcomes that go beyond simple test scores.

The review has also been able to identify areas for improvement in future studies, which would address confounding variables and expand the scope of research. Firstly, as Allcoat and von Mühlenen (2018) suggest, the novelty of I-VR could hamper learning outcomes due to unfamiliarity with the technology. Therefore, it is important to factor in an extended familiarisation or free navigation period that would help alleviate this concern. Additionally, follow-up qualitative analysis such as interviews or focus groups could help explore the phenomenology or direct experience of using I-VR, and highlight concerns relating to unfamiliarity or technological anxiety. The biggest concern relating to the assessment instrumentation was the over reliance on the MCQ (62% of studies used it as the sold method of assessment). Although this method is deemed appropriate for assessing large amounts of surface knowledge, it may not reveal more nuanced forms of learning that extend beyond mere recall of information. Therefore, long form essay questions, oral examinations, or group discussions could be used to facilitate students’ ability to present their in-depth understanding and applied knowledge. Future research must base the nature of these interventions on a sound theoretical framework. This would assist in identifying specific learning objectives and methods of assessments. An explicit theoretical approach was commonly lacking in the included studies.

I-VR has already been demonstrated to be an effective tool in non-pedagogical behaviour change, such as treating phobias, mental health conditions, or as a tool for rehabilitation (Botella et al. 2017; Maples-Keller et al. 2018; Ravi et al. 2017). Research should therefore concentrate on I-VR’s potential as an acquisition tool for affective skills. There is already a strong body of evidence suggesting I-VR experiences can elicit high levels of empathetic response and perspective taking, and this should be explored within an educational context (Herrera et al. 2018; Shin 2018). For example, Dyer et al. (2018) used I-VR to allow health care students to take the perspective of an older patient with age-related medical conditions, which led to increased empathy. Future studies should investigate whether this perspective taking ability can lead to higher domains of learning, such as evaluating one’s actions, applying problem solving skills, or creating new solutions as a direct result of the insights they received from I-VR. This will require researchers and instructors to carefully consider their tools for evaluation and assessment, perhaps incorporating mixed-methods to give a more holistic overview of learning achieved.