1 Introduction
The progress of Virtual Reality (VR) technology has led to the development and introduction of numerous VR simulators in various fields, including medical education. Educators are eager to explore the potential of VR technology to revolutionise the existing medical training modalities and become the new standard. However, the readiness of the current medical curriculum to integrate this new technology, as well as the willingness of the students to accept it, remains uncertain.
In close collaboration with the Obstetrics and Gynaecology (O&G) department of a medical school, we developed a VR simulator for normal vaginal delivery, driven by our motivation to address challenges in standardised delivery suite experiences, enhance accessibility to hands-on learning material, and provide opportunities for distance learning during pandemics. In the scenario, users, who are undergraduate medical students, are walked through the second and third stages of labour, utilising medical instruments and perform hand manoeuvres.
The overarching exploration in this study goes beyond mere effectiveness to probe more deeply into the utility and the usability of the VR simulator: "How does the incorporation of virtual reality in medical training, particularly in training for childbirth delivery, influence both learning outcomes and the acceptance of the technology among medical students?" This larger question gives rise to 3 sub-research questions:
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RQ1. "How does the VR simulator affect the learning outcomes in terms of knowledge and problem-solving skills in childbirth scenarios?"
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RQ2. "How acceptable is the VR simulator among medical students as an educational tool for childbirth training?"
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RQ3. "What is the relationship between the perceived acceptability and the effectiveness of the VR and manikin simulators in enhancing learning outcomes?"
We have formulated the following hypotheses:
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H1. Integrating a VR simulator in childbirth delivery training will yield significantly improved learning outcomes in medical students, as evidenced by higher scores in knowledge tests, compared to traditional Manikin-based training.
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H2. Medical students will rate the VR simulator as significantly better in terms of the 6 feasibility domains, including learning, confidence, feedback, usability, enjoyment and presence. This affirms that the technology aligns with their educational needs and learning preferences in the context of childbirth delivery training.
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H3. There will be a positive correlation between the levels of acceptability and the effectiveness of the simulator; the higher the acceptability ratings, the greater the improvement in learning outcomes.
We conducted an empirical study with 117 medical students to explore the answer to our research questions and test our hypotheses. Both knowledge gains and feasibility scores were calculated and compared between the manikin training modality and the VR training modality. Additionally, selected interviews were conducted to provide deeper insights into the nuanced relationship between technological innovation and educational impact, guiding future integration of VR into medical training curricula.
The contributions of this paper to the HCI community are:
(1)
A large-scale empirical evaluation with medical students, comparing a VR simulator with the traditional manikin method for childbirth delivery training. While participants showed significantly improved knowledge scores with the VR training, subjective ratings indicated the opposite, i.e. a low acceptance of VR training amongst medical students.
(2)
A qualitative assessment through in-depth interviews with medical instructors and students, providing insights into this discrepancy. The factors affecting VR adoption, pedagogical limitations of and manikin-based training, as well as the broader implications for integration of VR systems into medical training curricula were explored.
(3)
Details on a medical educational VR simulator’s design and development process, including the design requirements, prototyping, translation of teaching materials into virtual content, and a discussion of other key features included in the simulation.
4 Evaluation Study
For our evaluation study, we employed a two-part approach to assess the integration of VR in childbirth delivery training. In Part 1, a large-scale study involving 117 medical students was conducted, where participants engaged in both manikin and VR training sessions. This phase focused on quantitatively assessing improvements in knowledge scores and gathering feedback on user experience. In Part 2, we conducted in-depth interviews with a selected number of students and medical experts. This qualitative phase aimed to gain a more nuanced understanding of the factors affecting VR adoption, the pedagogical benefits and limitations of VR and manikin-based training, as well as the broader implications for medical training curricula.
All studies were approved by the Institutional Review Board (IRB). All medical students were given the opportunity to withdraw from this study and undergo legacy teaching with the manikin and were informed at the start that participation implied consent. Additionally, all medical students were informed on what data would be collected and how they would be used.
While we introduce the selected students and medical experts who participated in Part 2 (refer to 4.2), findings from the interview are integrated into the next section Discussion.
4.1 Large-scale Assessment of Knowledge Gains and User Experience
4.1.1 Participants.
The study was undertaken with an original sample of 134 medical students. Given the dynamic nature of medical students’ schedules and the constraints of fitting this study within their in-class sessions, only 117 students managed to complete both training sessions, knowledge quizzes and feedback questionnaires. This high attrition of 12.7% is not uncommon to studies conducted with medical students, providing an added layer to the study’s real-world relevance [
8,
10,
31].
The 117 participants (55 female, 62 male) were Year 4 medical students in the first week of their six-week clerkship with obstetrics and gynaecology, with an estimated mean age of 23.5 years. The study employed a counterbalanced design to mitigate order effects: 61 participants started with VR training and then moved on to Manikin training, while 56 experienced the reverse sequence. All students were on the cusp of their practical rotations which included curriculum in obstetrics and gynaecology, ensuring their foundational knowledge was current and robust. They had not yet been exposed to actual childbirth delivery procedures in a professional setting, setting a baseline for the novelty of the training experience, as well as knowledge level on the topic. Additionally, the VR platform used, the Oculus Quest, was unfamiliar to all.
4.1.2 Measures.
4.1.2.1 Knowledge scores. Pre- and post tests were administered via Google Forms before and after the first training session only. Both tests were identical, comprising 10 questions designed to evaluate participants’ understanding of concepts spanning the 2nd and 3rd stages of labour in a normal vaginal childbirth delivery. Among the 10 questions, 8 took the form of multiple-choice questions presenting 4 or 5 options, while two were structured as multiple-select questions, allowing for multiple correct responses to be checked.
In addition, these questions were curated to align with the Year 4 syllabus of the medical school. For authenticity and validity, they were reviewed and approved by the director of undergraduate education for the OBGYN clerkship, who also serves as the instructor for the manikin session.
4.1.2.2 Feasibility of training methods. Post each training session (refer to Section 4.1.4 Design and Procedure), we administered a feasibility questionnaire via Google Forms to assess the pedagogical efficacy and user receptiveness of the two training modalities (VR and Manikin). This offered insights into the multifaceted experiences of participants, complementing the knowledge test scores and providing a comprehensive perspective on the potential advantages and limitations of each modality. There were a total of 14 questions, each classified into one of six domains [
3,
15,
16,
21,
22,
25,
32]:
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Learning (3 Questions): Aimed to evaluate the user’s understanding and internalization of the subject matter.
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Confidence (2 Questions): Addressed the self-belief and assurance participants felt in applying the freshly acquired knowledge.
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Feedback (3 Questions): Explored the clarity and direction the participants perceived during their simulation encounters.
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Usability (2 Questions): Assessed the user’s ease of navigating and interacting with the simulation, indicating its design and operational efficiency.
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Enjoyment (2 Questions): Targeted at understanding the hedonic satisfaction and pleasure derived from the training sessions.
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Presence (2 Questions): Measured the immersive quality, realism, and sense of being "in the moment" during the sessions.
4.1.2.3 Preferred Modality. Post engagement with the VR and Manikin modalities, participants indicated their preferred training method: Manikin, VR, or Both. This metric captures the immediate preference and perceived efficacy of each training format.
4.1.2.4 Open Questions. To delve deeper into the rationale behind preferences and identify potential areas for enhancement, participants responded to two open-ended questions at the end of their second feasibility questionnaire relating to:
(1)
Reason for preferred modality
(2)
Feedback on weakness or area of improvement for the training modality
4.1.3 Apparatus and Training Setting.
4.1.3.1 Manikin Session. The training was held in a simulated High Dependency Unit (HDU) room equipped with the manikin apparatus, the PROMPT Flex Birthing Simulator (Figure
7a). Each Manikin group comprised 12 to 13 students supervised by a single instructor. They received a briefing on relevant medical theories prior to the training session. While the session’s structure is typical of conventional Manikin training, fewer than half of the students got the chance for hands-on engagement with the manikin. This hands-on opportunity arose in one of two ways: students volunteering when the instructor sought a demonstrator or through random selection by the instructor. Each Manikin session lasted approximately 60 minutes.
4.1.3.2 VR Session. The Oculus Quest 2 platform was used for the VR session (Figure
7b). To facilitate occasional real-time monitoring by the experimenters, the headset was connected to a PC using a cable. This enabled the research team to do frequent checks on participants’ in-app activity and progress.
Two dedicated rooms were set up for the VR session, each accommodating three students at a time. As soon as a student concluded their session, another student was invited to occupy the newly vacant slot. Each student would spend around 15 to 20 minutes in VR.
4.1.4 Design and Procedure.
The procedure of the user study is summarised in Figure
8.
(1)
Briefing ( 5 minutes): Each group of participants arrived at their designated training venue. Upon arrival and after giving their informed consent, participants underwent a structured briefing regarding the flow of the study. Specific to the VR training session, participants were given a visual and verbal demonstration by the experimenters, teaching them from how to wear the headset to how to use the VR interface. Key interaction such as pinching their fingers to pick up medical instruments within the virtual environment was strongly emphasised.
(2)
Pre-simulation Knowledge Quiz ( 3 minutes): Following the briefing, participants filled in the pre-simulation knowledge quiz on their mobile device, which aimed to assess their baseline understanding before engaging with the training sessions.
(3)
First Simulation Session ( 55 minutes): For the manikin group, participants have a didactic lecture for about 15 minutes. Then, they spend 5 minutes observing the instructor’s demonstration on the hand manoeuvres and 5 minutes to orientate and familiarise themselves with the manikin. After that, the few selected or volunteered students are guided by the instructor through the process on the manikin for 25 minutes. For the VR group, participants have about 3 minutes to familiarise themselves with the headset and VR interface, and then have a 20-minute session in VR.
(4)
Post-simulation Knowledge Quiz & Feasibility Questionnaire ( 5 minutes): Upon completion of their first simulation, participants completed the post-simulation knowledge quiz followed by a feasibility questionnaire on their mobile device.
(5)
Second Simulation Session ( 55 minutes): Participants were directed to their next assigned training venue, this time experiencing the remaining modality.
(6)
Feasibility Questionnaire & Overall Feedback ( 5 minutes): After completing the second simulation, they filled out the feasibility questionnaire on their phone for the second modality and overall preference, including open-ended questions.
4.1.5 Results.
4.1.5.1 Knowledge scores. We conducted a between-subjects analysis, the independent samples t-test, to compare the score improvements in VR training and Manikin training modalities, in percentage. Both Sphericity (Levene’s test, p>0.05) and Normality (Shapiro-Wilk test, p>0.05) assumptions were met.
There was a significant difference in score improvements between VR training (M=39.8%, SD=18.8%) and Manikin training (M=14.9%, SD=19.9%); t(115) = 6.96, p<0.001 (Figure
9).
4.1.5.2 Feasibility Questionnaire. We used a within-subjects analysis to compare feasibility ratings. The Shapiro-Wilk test indicated that the data for all six domains were not normally distributed (p < .001). Thus, an Exact Wilcoxon-Pratt Signed-Rank Test was used to compare the median rankings of VR and Manikin training sessions for each of the 6 feasibility domains (Figure
10):
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Learning: The median of VR was 4.33 (IQR = 1) and of Manikin was 4.33 (IQR = 1). This difference was not statistically significant according to a Wilcoxon signed-rank test (Z = -0.067, p>0.05).
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Confidence: The median of VR was 4.0 (IQR = 1.5) and of Manikin was 4.0 (IQR = 1). This difference was statistically significant according to a Wilcoxon signed-rank test (Z = -2.93, p<0.01).
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Feedback: The median of VR was 4.33 (IQR = 1) and of Manikin was 4.33 (IQR = 1). This difference was statistically significant according to a Wilcoxon signed-rank test (Z = -2.22, p<0.05).
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Usability: The median of VR was 4.0 (IQR = 2) and of Manikin was 4.0 (IQR = 1). This difference was statistically significant according to a Wilcoxon signed-rank test (Z = -4.31, p<0.001).
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Enjoyment: The median of VR was 4.5 (IQR = 1) and of Manikin was 4.5 (IQR = 1). This difference was statistically significant according to a Wilcoxon signed-rank test (Z = -3.35, p<0.001).
•
Presence: The median of VR was 4.0 (IQR = 1.5) and of Manikin was 4.0 (IQR = 1). This difference was statistically significant according to a Wilcoxon signed-rank test (Z = -3.43, p<0.001).
4.1.5.3 Preferred Mode of Instruction. After exposure to both Manikin and VR simulations, 49 participants (41.9%) preferred a combined approach, 62 participants (53.0%) favoured the Manikin alone, and 6 participants (5.1%) chose the VR Simulation. The combined and Manikin approaches were dominant, while VR was the least favoured.
4.1.5.4 Open-ended questions. The top two reasons why participants favoured the manikin modality are “tactility” and the presence of an “engaging tutor”. In the manikin session, they appreciated the tactile feedback from the manikin and the ability to interact directly with the instructor, who provided immediate clarification for any doubts. This hands-on approach made them feel like they were actively participating in the delivery procedure.
On the other hand, the VR simulator excelled in “visualisation” and providing a smooth and complete “flow” of information. Participants were played in the role of a physician assisting a primigravida and learned the entire procedure of the normal vaginal delivery step by step, with important operations and hand manoeuvres being animated. Some participants even expressed a desire to have access to the recording of the VR gameplay for revision purposes.
Common suggestions for improving the manikin session included extending the duration and ensuring that everyone gets an opportunity to practise on the manikin. For the VR simulator, the most common improvement mentioned was enhancing usability such as the ease and intuitiveness of picking up and holding the virtual instruments in hand to ensure a smoother simulation experience. Other suggestions include improving the frame rate and graphics further.
4.2 In-depth Interviews for Qualitative Insights
In-depth interviews were conducted with medical students who participated in the previous evaluation, as well as medical experts. Consent to capture and utilise their quotes was obtained. The interviews were thematically analysed.
4.2.1.1 Medical experts. Three experts from the department of obstetrics and gynaecology were invited to be interviewed online. One of them is the director of the Year 4 O&G posting who collaborated with us. The other two are associate consultants who are keen in exploring VR technology in the childbirth delivery education. The interview durations were 55 minutes, 15 minutes, and 10 minutes, respectively. We interviewed them to understand:
(1)
Student behaviour during the manikin session
(3)
Opinion on traditional manikin training and VR training
(4)
Potential use of VR simulations in O&G training
4.2.1.2 Selected medical students. We conducted in-depth interviews with 5 randomly selected participants, 2 of whom were in Year 4 and 3 in Year 5 of the OG settle-in programme. Interviews were conducted either online or face-to-face. The interview durations were about 10 to 15 minutes each. All interviewees have attended four VR anatomy sessions in year 1 and one VR surgical safety session in year 3. Each of their VR sessions lasted less than half an hour, including briefing on theories and debrief to facilitate content reflection. All sessions used HTC Vive as the head-mounted display and its controllers as the input method. We interviewed them to understand:
(1)
Prior experience with VR simulations in their education
(3)
Opinion on training manikin training and VR training
(4)
Potential use of VR simulations in the O&G training
5 Results and Discussion
Our hypotheses, H1 and H2, proposed that medical students would both demonstrate improved learning outcomes and show a high level of acceptance of our VR simulator for childbirth training. While the data confirms H1, providing positive feedback in response to RQ1 ("How does the VR simulator affect the learning outcomes in terms of knowledge and problem-solving skills in childbirth scenarios?"), H2 was not empirically supported by the results. The significantly lower ratings for VR training compared to Manikin training in 5 out of 6 feasibility domains: Confidence, Usability, Enjoyment, Feedback and Presence answers RQ2 ("How acceptable is the VR simulator among medical students as an educational tool for childbirth training?"). This discrepancy between learning outcomes and user acceptance (RQ3 and H3) highlights a pivotal challenge in the integration of VR technology into traditional medical curriculum. Below, we explore relevant themes that emerged from our in-depth interviews with medical experts and students. Insights from our studies, reflections and suggestions provide valuable guidance for addressing this challenge and enhancing the effectiveness and acceptance of VR in medical education.
5.1 The Irreplaceable Role of Instructor Engagement
Despite the advancements in VR technology, thematic analysis of open-ended responses from our feasibility questionnaire (Section 4.1.5.2) reveal a preference for face-to-face interaction with instructors. For instance P8963 noted that a "VR system is not as interactive as a tutorial with a instructor," highlighting the essential role of human instructors in the learning process. This is potentially tied to the lower “Feedback” ratings in the VR simulation, and a critical reason why 94.9% of the participants were not willing to dispense with in-person sessions, i.e. participants preferred Manikin-only or both Manikin and VR modalities as part of their childbirth delivery training.
Expert 1 concurred to the vital role of instructor engagement during their interview, expressing that in-person experiences simply cannot be replaced, much less by “videos on YouTube". This medical expert emphasised the importance of the apprenticeship model, which offers a blend of observation, experience, and inspiration, that is effective not just for knowledge transfer, but for contextual experience and decision-making capabilities that are difficult to replicate in simulated environments. This may explain why H3 ("There will be a positive correlation between the levels of acceptability and the effectiveness of the VR simulator; the higher the acceptability ratings, the greater the improvement in learning outcomes.") was not supported by the data.
To address this limitation while still leveraging VR’s advantages, we suggest future explorations of a hybrid training model combining modern technology’s benefits with the wisdom and adaptability of live instruction. A next direction worth exploring includes remote VR training incorporating real-time instructor feedback. The use of cloud-based technology could alleviate the need for dedicated physical spaces, and a multi-player login feature could allow instructors to interact with multiple students in a simulated environment. This approach ensures the instructor remains an integral part of the training process.
5.2 Adaptability and Learning Curve in VR
While the VR simulation led to improved knowledge scores (thereby supporting H1) in our large-scale empirical study, a steep learning curve might have played a role in the discrepant results between knowledge and experiential outcome. Specifically, given students’ lack of experience with VR systems, they were less confident, affecting the system’sperceived usability. Feedback provided by students substantiates this – P2107 for instance, acknowledged VR for its immersive qualities but also cautioned that it "takes some time to get used to [the experience]." Multiple students echoed P8884’s report of feeling "dizzy" initially, a common issue when adapting to VR simulations. Past research indeed alludes to the importance of designing VR experiences to help alleviate these early-stage challenges [
19], suggesting thatfuture implementations of the VR simulator can have in-built design adaptations to improve the usability and acceptability of the VR simulator as part of the core training modality [
7].
In addition, two out of three medical expert interviewees proactively recommended longitudinal studies to monitor how users’ comfort and proficiency evolve with sustained exposure to VR environments. Such studies could serve as a feedback mechanism, leading to design iterations that better accommodate students’ learning. By understanding these factors more comprehensively, we can address the initial barriers that impede VR’s effectiveness.
5.3 Integration of Different Realism Aspects
Based on student feedback in the feasibility questionnaire’s open-ended responses and interviews, there is a general consensus that VR simulations provide a degree of visual realism that benefits learning. This is evidenced by comments such as "[VR makes it] more visualisable" (P8903). However, VR simulations fall short in aspects of tactile realism, a salient aspect in the training of procedures like surgery or childbirth, whereby the precision and subtlety of hand movements are crucial [
20].
For instance, P2108 highlighted the lack of tactile engagement with medical equipment. Specifically, this participant referred to the pinching gesture used in the simulation as non-naturalistic: "Performing the steps and usage of instruments is not very realistic"), failing to simulate the actual experience of using medical instruments. To this end, the VR simulator’s lack of tactile realism is likely to have adversely affected the ’Presence’ and ’Enjoyment’ ratings in the feasibility questionnaire.
To address the gap between interactions in the digital and physical world, the potential of the Mixed Reality (MR) platform becomes evident. The MR platform may be suitable for incorporating tactile elements from the real world into the simulation, thereby offering an enriched sensory experience that better represents real-world tools and procedures. This has the potential to improve both learning outcome and user acceptance, allowing students to effectively learn about the tasks and tool usage that medical professionals routinely perform.
5.4 Chaos Simulation
In keeping with the need for integrated realism, all of our medical expert interviewees also highlighted the importance of integrating real-world scenarios into the VR design as a means of improving the level of realism. Expert 1 emphasised the importance of replicating the "natural chaos" found in labor wards during her interview; this is a key need for effective training in realistic high-stakes, high-stress medical environments. This includes simulations of medical complexities, unpredictable interpersonal and environmental variables such as interruptions from colleagues, input from family members, and unforeseen emergencies. Students tend to lack exposure to these naturalistic elements in classroom teaching, and it increases the challenge of navigating real-life medical situations.
To meet this educational need, we foresee that future iterations of our VR simulations will leverage AI-driven scenarios and randomized elements. This approach aims to simulate the rapidly evolving, multi-variable environment that undergraduates need to become proficient in before entering their residency. Additionally, integrating biometric feedback systems could offer real-time monitoring of stress and performance, providing a nuanced understanding of each trainee’s adaptability to simulated ’chaos’.
One of our medical expert interviewees also highlighted the importance of students’ psychological well-being. High-fidelity simulations must stimulate sufficient levels of stress, preparing trainees for the kinds of high-pressure situations they might encounter in the future. However, the simulations should not be so stressful as to be traumatize or to jeopardise their mental health, a balance supported by previous research [
11]. To ensure this balance,real-time feedback mechanisms can be implemented, allowing either students or instructors to adjust the simulation’s complexity during training, based on student performance and stress levels. We recommend safe and iterative user testing as part of the implementation process.
5.5 Resource Constraints
The VR simulation was initially conceptualized as a potential solution to resource constraints, given the possibilities of scalability and standardisation. While the data does support the VR simulator’s efficacy in improving learning outcomes, the challenges related to Usability suggest that resource constraints remain an issue, impacting the simulation’s overall acceptance too.
Interviews with medical experts revealed a trend in the landscape of medical training; there has been an increasing emphasis on breadth, with "more postings added to curriculum" resulting in shorter periods of exposure to specialized areas such as obstetrics and gynaecology, from "12 weeks to 6 weeks". As a result, there is the challenge of standardisation, i.e. medical students’ exposure to real-world situations differ widely due to the unpredictable nature of childbirth events, such as "how many patients come in [those 6 weeks]" or “how many patients actually give birth on the day they visit the ward”.
These findings from the interviews highlight the need for more standardised, accessible, and scalable training solutions, and VR simulations can function as an invaluable supplement to traditional training. With the development of scenario-based learning exercises, VR simulation platforms can offer controlled environments where students can repeatedly practice, enhance competency on both knowledge and psychomotor skills, and be assessed without taxing already constrained resources like physical space, instructor time, and training equipment. Training using such simulations has the potential to reduce the theory-practice gap that Brown [
4]suggests in his study with graduate nurses through the use of high-fidelity simulations. Whilst not a replacement for real patient scenarios, technology can certainly supplement traditional education modalities, such as the Manikin.
The financial requirements for implementing our childbirth delivery training module can be categorised into development and deployment expenses. The development aspect encompasses funds allocated for recruiting a dedicated developer and a contract-based artist. Additionally, it includes contributions from engineering students who are integrating this project into their design and research curriculum. On the deployment front, the costs involve purchasing standard VR headsets, each estimated at around $299, with no extra expenditure on software owing to in-house development. The human resources needed for facilitating the VR sessions are relatively modest, possibly just two engineering students, with each supervising one of the two designated training environments.
However, several administrative and logistical challenges still arise that need careful consideration, in order to effectively blend VR technology into current curriculum. Venue limitations, particularly concerning the capacity to accommodate large student cohorts that come through each year, pose a barrier to the technology’s scalability. While VR equipment has become more portable and user-friendly, the necessity for individualised learning environments remains a point of contention. The medical experts emphasised the value of such personalised settings, arguing that they allow for greater immersion in the VR scenario. To integrate rather than replace opportunities for face-to-face peer learning, we recommend exploring into blended learning approach. In the blended model, VR could be used for individualised, high-fidelity simulations to allow deep immersive learning while traditional educational methods could provide opportunities for peer-to-peer interaction and team-based training.
Medical experts also alluded to the issue of differing paces at which students complete VR simulations during the experiment. The variability in pace can be attributed to both unfamiliarity with the technology and individual learning styles, such as how thoroughly students read through explanations or take time to contemplate questions. To address this in future training implementations, instructors could offer tiered scenarios or implement adaptive algorithms that modify the simulation’s difficulty and guidance in real-time, thereby accommodating individual learning needs even in a group-based setting.
5.6 Limitations
There are inherent limitations in this user study that warrant attention.
Firstly, due to constraints related to time and manpower, the pre- and post-tests were designed to only examine the basic knowledge using multiple-choice questions. More advanced psychomotor skills, such as hand manoeuvres, were not evaluated after the sessions. We could not conclude the effectiveness of the design of teaching the hand manoeuvre in VR.
Secondly, our methodology did not include an assessment of long-term retention rates for learning through VR or manikins.
Thirdly, recruiting volunteers for interviews proved challenging due to the busy schedules of medical students, and the limited number of selected interviewees may not be fully representative for the entire cohort. A potential solution could involve interviewing participants who already completed their simulation and are waiting in the briefing room. This approach can significantly increase in the number of interviewees to enhance the generalisability of interview results.
5.7 Future Work
As the semesters progress, more batches of students will be using our simulator in their O&G posting. We have several plans for our future work.
Firstly, we aim to improve the user experience, especially for novice users in VR. Our goal is to explore a more natural interaction so that users can quickly engage with the content without being distracted by complex gestures and mechanisms. More time can be spent on learning the content instead of system familiarisation.
Secondly, we are currently developing a new VR simulation focused on shoulder dystocia complication, which contains more complicated situations than the normal vaginal delivery. We plan to assess the cognitive load experienced by the users during various sudden events within this scenario and study how these events impact their learning.
Lastly, we are also investigating enhancing the transfer of psychomotor skills in VR, particularly through an episiotomy simulation. This involves recording and analysing detailed hand movement trajectories to improve skill acquisition.
These initiatives reflect our commitment to addressing the needs of simulation in O&G training and attempts to ensure a smooth integration of the technology.