Virtual reality (VR) is seeing massive growth in higher education, especially in medical fields like nursing. In this case study, we explore research methods and how they may be utilized in practical research practice to implement this into a dissertation. Research methods discussed in this work revolve around the meaning-making of applicable quantitative methods surrounding student and faculty VR classroom learning participants within the medical field. This study proposes using a quantitative research framework that compares student academic performance when learning in a VR environment versus students learning in a traditional classroom environment. The qualitative research framework proposal is to utilize interpretive research methods and transpositional grammar to define words/objectives/concepts of the learning environment to provide meaning to the data that would be collected during the practical study.
The work also addresses pitfalls and criticisms of VR use in the classroom, such as the suitability of the platform for learning, cybersickness, privacy concerns, user autonomy, safety, and cost, along with solutions for those potential problems.

With Virtual Reality (VR) continuing to see more adoption in a multitude of higher learning environments each year, due to its high level of immersion and improvements in hardware/software technology. "Integrating augmented reality (AR) and virtual reality (VR) into learning solutions is no longer optional; it's a necessity for educational institutions aiming to enhance student engagement. Current market analysis reveals a projected compound annual growth rate (CAGR) of over 30% for AR and VR technologies in education, expected to reach $12 billion by 2025" (Andersen, 2025). It is not only important to study whether students are learning course materials well with it, but since it replaces traditional learning methodologies, we need to do some comparative qualitative research to assess whether students are performing worse, the same, or better-using VR versus traditional learning methods. To study this well, it is essential to use interpretive methods to form meaning behind learning objectives to provide a 1:1 relationship between learning assessments in the traditional and experimental VR learning environments. This work guides interpretive research methods that provide meaningful comparisons between traditional and VR learning environments.
The College of DuPage in Glen Ellyn (my place of work and my research institution) currently has a college-wide AR/VR classroom lab that I manage as a technical lead. Nursing is the department that utilizes this room the most, using SimX (medical/nursing software). Given this classroom use, the work will primarily be narrowed down to the medical field of higher learning.

We can first develop Transpositional Grammar for each learning modality to create meaning behind student performance objectives in both traditional and VR learning environments. Cope & Kalantzis (2022) discuss Text and Speech Transpositional grammar in the following table:

(Cope & Kalantzis, 2022)

This table lists senses, adjacent forms, medium, affordances, grammar, and digital media, then transcribes the meaning behind each of these regarding text and speech modalities. Utilizing the same process, we can evaluate different assessment portions by creating a similar table that transposes grammar into something meaningful we can study, quantifying the research into something understandable. Still, before this table can be developed, we need to make sure that we understand each learning environment's general features and the learning objectives we aim to assess. In order to do this, let us first look at the general features of VR learning environments.
AKGÜN & ATICI (2022) provided meaningful features of the VR learning environment in the following graphic:

(AKGÜN, M & ATICI, 2022)

Each of these features can be interpreted for both VR and traditional modalities; however, since we are only studying student performance in these learning environments, we can narrow these features down to the following:
-Creating a perception of reality
-Possibility to apply knowledge to real-life
-Providing different experiences and learning environments
-Easy adaptation
-Providing experience
-Providing flexibility
-Providing feedback
-Providing an interactive learning environment

Kelly, Hallam, & Bignell (2022) provided themes that we can append to AKGÜN & ATICI (2022)’s features:

(Kelly, Hallam, & Bignell, 2022)

Like the general features AKGÜN & ATICI (2022) provided, we can narrow these themes down so that we can utilize this for transpositional grammar for both the traditional and VR learning environments:

-Visual Satisfaction

-Freedom of Interaction

In synthesizing these sources, we may be able to use the following transpositional grammar table:

Table: Transpositional Grammar Synthesis

Using the concepts discussed and the transpositional grammar table, we can develop a theoretical framework that would track the flow of each learning environment and how students will be assessed through that. The following is a flowchart by Poppe et al. (2023)

(Poppe et al., 2023)

This flowchart describes a barebones workflow of VR learning scenarios. It walks us through a student and moderator's workflow in VR software, emphasizing the various screens for the student and moderator from the launch of the application to the learning scenario to the environment and through the assessment. We can interpret this into a workflow that describes a traditional learning environment by allowing the instructor to teach the same lesson that students are learning in VR inside of a physical classroom instead of interpreting any of the strategies listed in the transpositional grammar table that I created and provided at the end of the Concepts section. From there, students' knowledge will be tested in their respective learning environments.

Using this workflow for each traditional and VR learning environment, we can implement our conceptual transpositional grammar (provided at the bottom of the Concepts section) to evaluate each learning environment and its effect on student performance. Ultimately, we will want to transpose all of this into a research model similar to what Okul & Şimşek (2025) provide:

(Okul & Şimşek, 2025)

This table is an example of a traditional research method comparing an Experimental group (students learning a lesson through VR) and a Control group (students learning a lesson through traditional classroom methods). It requires that we have the same lessons and course objectives with the same evaluation method between each type of learning environment with an even number of students separated between the control and experimental groups. This type of table is a widespread practice for a traditional versus VR learning environment, as it is very generic and scalable. This makes for an excellent table to utilize for a study assessing students on their academic performance in a traditional learning environment versus a VR learning environment.

While these theories may align well in VR classrooms, they should require a "needs assessment." Is there a need for VR lessons/training in the classroom to enhance student learning beyond the school, or are instructors/students attracted to VR because it's a fun new toy? Like any technology, we should avoid using it for learning if it does not offer positive affordances for the lessons.
In 2023, medical researchers from Canada developed a theoretical framework called "Build Reality" (Gupta, 2023) that guides instructors and hospitals to conduct a needs assessment revolving around VR for medical training. This is their needs assessment chart:

(Gupta, 2023)

The chart defines VR "needs" revolving around location, time, accessibility, personnel, assessment, software, diversity, and the learning environment. All of these factors are important to whether VR can or should be integrated into the learning environment. Questions instructors should ask in conjunction with the lesson/topic: are there notable advantages to all of these factors, and if not, are there at least some factors where VR learning methods are more beneficial to students than traditional learning methods? Answers to this will likely vary depending on the hardware and software choices and the specific lesson being taught.

Since the main users of the VR learning environment at College of DuPage are the Nursing department, I will narrow the research down to the use of SimX that the nursing students/faculty use to supplement traditional lectures and clinical labs to evaluate the theoretical framework discussed. SimX https://www.simxvr.com is one of the leading VR medical simulators that provide various fully immersive realistic scenarios that students work through while being assessed by a moderator who is a faculty member when being used in a higher learning environment. Below are videos SimX provides to guide students and moderators through the software. Together, these videos show examples of the workflow of the student learners and the instructors, taking us from the launch of the software through the assessment phase processed by the moderator/instructor.

Video: SimX, 2023

Video: SimX, 2024

SimX continues to improve the software by adding more scenarios; linked is an exhaustive list of scenarios that SimX provides our nursing students and instructors https://www.simxvr.com/virtual-reality-simulation-for-nurses/

According to our SimX representative and College of DuPage Nursing faculty, SimX is currently working on an AI implementation to provide students with more automated feedback. This will assist the instructors with assessment and give the student learners more autonomy. Although this is a promising development, since the AI portion of this software has not yet been launched, we cannot incorporate AI into our research methods just yet.

Since SimX is now widely used in Nursing education, there have already been several studies indicating how effective SimX is as a supplement to traditional and clinical learning methods. In 2022, a study of 135 nurses across six educational institutions compared VR and traditional learning methods to find the effectiveness of learning and assessment when using VR learning scenarios within SimX. The average scores among the 135 participants indicated that the VR scenarios were “effective or highly effective” in their overall learning and assessment compared to traditional learning methods. Their methodology took place in three phases: 1) selection of scenario content for implementation, 2) implementation and iteration of content, and 3) pilot testing and evaluation of the resulting curriculum. (Sarma et al., 2022)

The breakdown of results comparing traditional (Physical Simulation), Clinical Practice, and VR simulations measured for effectiveness across all six institutions and 135 nurses is shown in the following table:

(Sarma et al., 2022)

These results utilized several scenarios that Sarma et al. (2022) categorized into Fundamental, Medical-Surgical, Pediatrics, and Obstetrics “domains” as seen in the table below:

(Sarma et al., 2022)

Since it would likely not be fruitful research to have students only go through one scenario, we should create our table of multiple scenarios that tackle relevant domains in nursing that also have a 1:1 relationship with traditional lab scenarios that we can use to assess better how well students are performing in each environment. Through this, we can pick proper scenarios for College of DuPage Nursing students and faculty to interpret into realistic domains.
Using the domain table as a guide, faculty can choose a domain that selects a scenario for both traditional and VR learning environments. We can then use the flowchart provided in the Theory section and evaluate students using the meaning table developed in the Concept section. Assessment can be a test evaluating how well the students performed each task. Below is a general flow for VR nursing scenarios. There are over 270 nursing scenarios presently in SimX, each scenario operates in the same way, so this flow is universal to all nursing scenarios in SimX:
Pre-briefing:
-Scenario descprition
-Key concepts
-Scenario Objectives

Scenario
-Complete the learning objectives

Debriefing:
-Review and Analysis of the scenario, learning objectives, and student accuracy
-Moderators provide feedback to the student in real life based on the results shown in the moderator view and the student's analysis
-Student reflection on the learning scenario, review, analysis, and moderator feedback

VR usage in the classroom does not exist without its criticism. Several studies over the years have identified user and technology-based problems regarding the platform's suitability for learning, cybersickness, privacy concerns, user autonomy, safety, and cost. I know many of these issues, given that I have been developing VR software and teaching students to do the same for the last 12 years. While some of these concerns are still valid, others are outdated and/or have to do with the selected hardware and software with which an instructor would be teaching students.
Skulmowski (2023) from Karlsruhe University of Education in Germany, addresses specific concerns when it comes to VR, shown in the table below:

(Skulmowski, 2023)

The table not only discusses problems but also provides possible solutions to these problems. I find some of these concerns still valid today. "Ensuring suitability" is a concern, but also a concern when utilizing any teaching methodology or lesson, even outside of VR. In terms of the suitability of VR, VR is not always the best medium for learning. Plenty of instructors at the College of DuPage utilize our AR/VR room for their classes (13 different departments). While VR labs in Nursing using SimX have been pivotal in student learning, other departments use VR because it is a fun toy. In addition, some departments would like to use VR for their classes but cannot find the right software suitable for their lessons. The same problem exists in all other form factors in the learning environment that instructors will have to ensure that their teaching methodologies enhance learning/knowledge, as Skulmowski (2023) describes.
"Preserving privacy" of the users usually falls under the IT department at a school. When colleges adopt software, it traditionally must go under an IT review, where privacy, data collection, and security are at the top of their review. This is a software issue and not exclusive to VR. "Autonomy" of users is a big concern when it comes to any form of media (not just VR); the realism/immersiveness of VR can make the experience more convincing, thus elevating the concerns of researchers like Skulmowski (2023) because it could contain false information harms a student's knowledge base. However, the solution that Skulmowski (2023) provided (lowering the realism of VR) is not the best answer, given that any form of media that doesn't even have the realism of VR can pose a risk of delivering false information to the students. Not only that but if the realism of VR is lowered and students are learning from a greater distance, it destroys the immersiveness of VR, thus defeating the purpose of the medium. A better solution to this problem is for teachers to review the material before utilizing it in class, as they should do for any material they deliver to the students.
"Cybersickness" is often discussed in studies as an issue among students. Skulmowski (2023) brought up the issue of cybersickness. Skulmowski (2023) suggests that alternative learning methods are provided to students, which is a common and viable solution to what can be looked at as a health/safety issue. While cybersickness still exists today, it is not what it used to be, and developers have been correcting this issue through many iterations of VR; in a 2025 study out of Massachusetts General Hospital Institute of Health Professions, Department of Health Professions in Education in Boston, MA, Stallo, 34 participants ages 19-30 tested VR on a rollercoaster ride utilizing various VR headsets to record instances of cybersickness among these participants comparing their experiences with the Meta Quest 2 and Meta Quest Pro. While the findings indicated that age and gender were not factors in cybersickness, it was discovered that resolution, refresh rate, and IDP match (Interpupillary Distance alignment between the user's pupils and internal VR displays). The Meta Quest Pro saw notable decreases in cybersickness in comparison to the Meta Quest 2, which Stallo et al. (2025) attribute to the higher resolution and higher refresh rate, in addition to virtually no IDP mismatch given the wide range of eye distance adjustments (55mm-75mm in range). See the table below for the full specs of these headsets:

(Stallo et al., 2025)

The table shows that over time, most of these values improved, which can explain why earlier studies indicated a higher level of cybersickness compared to recent studies. This also illustrates why researchers/instructors should not treat all VR headsets equally, given that the technology within each headset is different and can cause less/more cybersickness depending on which headset is selected.
There are additional common criticisms when it comes to utilizing VR in education. Baniasadi et al. (2020) published a study on challenges and practical considerations in applying VR technology to medical education and treatment in the Oman Medical Journal. The flowchart below illustrates the challenges faced when using VR technology in medical education and treatment:

(Baniasadi, 2020)

There is overlap with other studies conducted, like that of Skulmowski (2023) like whether VR and its application is a suitable of the platform for learning, user autonomy, and privacy (which falls under the Design and Evaluation and validation of VR applications elements of the (Baniasadi et al. (2020) study. In addition to that, safety, side effects, and cost were also concerns. In that common side effects like cybersickness (which continues to become less of a barrier with better technology, as Stallo et al. (2024) pointed out), addiction also showed a large factor given its game-like features, which could also be spun into a positive if the application is educational. As well as misuse of VR, which is a concern with any piece of classroom equipment. Safety considerations were also brought up in that there should be an expert to address any possible safety issues with the utilization of the VR (cybersickness also falls under safety considerations). Cost is also a factor, where not every institution can afford the cost of headsets and software, but as illustrated by Skulmowski (2023), the cost of VR is significantly cheaper than many other classroom/lab technologies, so it is a non-issue for many institutions.

As researchers, while conducting quantitative or qualitative research methods, we must use transpositional grammar, like what I have provided in this work, to interpret the data we collect during our research. This work can serve as a framework for anybody conducting research in VR, particularly quantitative research of comparative (traditional vs VR) learning assessments.
While the use of VR in education is not new, it is still seeing significant advances year to year on a hardware technology level and a software/application level, which is a significant reason why the medical field is seeing broad adoption of the learning modality. VR hardware is improving in the areas of eye alignment, resolution, framerate, and cost, which has been shown to address problems many users deal with that revolve around cybersickness and safety. VR Software is consistently improving with not only the release of viable medical software like SimX but such software is released or updated immersiveness and interactivity provides closer to a 1:1 relationship in the real world providing work-based learning opportunities in a virtual environment that is vetted by many medical faculty and professionals from around the world. In addition to that, software like SimX provides user feedback (something that older or less advanced VR applications tend to lack), with further improvements like generative AI feedback being worked on by the SimX software developers.

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Andersen, G. (2025, May 2). Future trends – The growth of AR and VR in the education app market. MoldStud. https://moldstud.com/articles/p-future-trends-the-growth-of-ar-and-vr-in-the-education-app-market

Baniasadi, T., Ayyoubzadeh, S. M., & Mohammadzadeh, N. (2020).Challenges and practical considerations in applying virtual reality in medical education and treatment. Oman Medical Journal, 35(3). https://doi.org/10.5001/omj.2020.43

Gupta, S., Wilcocks, K., Matava, C., Wiegelmann, J., Kaustov, L., & Alam, F. (2023). Creating a successful virtual reality–based medical simulation environment: Tutorial. JMIR Medical Education, 9. https://doi.org/10.2196/41090

Kalantzis, M., & Cope, B. (2022). After language: A grammar of multiform transposition. In C. Lütge (Ed.), Foreign language learning in the digital age: Theory and pedagogy for developing literacies (pp. 34–64). Routledge.

Kelly, N. J., Hallam, J., & Bignell, S. (2022). Using interpretative phenomenological analysis to gain a qualitative understanding of presence in virtual reality. Virtual Reality, 27(2), 1173–1185. https://doi.org/10.1007/s10055-022-00719-2

Okul, T., & Şimşek, G. (2025). The impact of using virtual reality applications on academic success and retention in tour guiding education. Journal of Hospitality, Leisure, Sport & Tourism Education, 36, 100540. https://doi.org/10.1016/j.jhlste.2025.100540

Poppe, M., Dorsch, J. R., Weiss, T. L., Andre, T., Barrie, M. G., Polson, J. S., Ribeira, R. J., & Sarma, K. V. (2023). Integrated learner assessment for readiness tracking within virtual reality medical simulation. MODSIM World 2023, Paper 3213. 3213. https://www.modsimworld.org/papers/2023/MODSIM_2023_paper_3213.pdf

Sarma, K., Parikh, N., Shah, M., Bambini, D., Barakat, S., Pohlman, H., Malmgren, L., Carr, N., Chan, C., Limberg, S., Weiss, T., Ribeira, J., Polson, J., Barrie, M., Andre, T., Namperumal, S., & Ribeira, R. (2022). Development and pilot evaluation of a virtual reality healthcare simulation curriculum for nursing education: SLS with VR. Technology Proceedings Manuscripts of the 23rd International Meeting for Simulation in Healthcare (IMSH 2023). http://dx.doi.org/10.2139/ssrn.4453655

SimX. (2023, September 26). SimX student tutorial [Video]. YouTube. https://www.youtube.com/watch?v=3dszlL21K8Y

SimX. (2024, March 11). SimX moderator tutorial [Video]. YouTube. https://www.youtube.com/watch?v=836U5jNjbi8

SimX (2025, January 17). SimX virtual reality simulation for nurses. https://www.simxvr.com/virtual-reality-simulation-for-nurses

Skulmowski, A. (2023). Ethical issues of educational virtual reality. Computers & Education: X Reality, 2, 100023. https://doi.org/10.1016/j.cexr.2023.100023

Stallo, P., Kardong-Egren, S., & Bauman, E. (2023). The impact of virtual reality headset selection on cybersickness severity. Society for Simulation in Healthcare (SSH), 3(2), 3-14. https://ssih.org/sites/default/files/2025-03/Volume%203%2C%20Issue%202.pdf