Augmented Reality in Cardiovascular Education (HoloHeart): Assessment of Students’ and Lecturers’ Needs and Expectations at Heidelberg University Medical School

Abstract

Background: A detailed understanding of cardiac anatomy and physiology is crucial in cardiovascular medicine. However, traditional learning methods often fall short in addressing this complexity. Augmented reality (AR) offers a promising tool to enhance comprehension. To assess its potential integration into the Heidelberger Curriculum Medicinale (HeiCuMed), we conducted a needs assessment among medical students and lecturers at Heidelberg University Medical School. Methods: Our survey aimed to evaluate the perceived benefits of AR-based learning compared to conventional methods and to gather expectations regarding an AR course in cardiovascular medicine. Using LimeSurvey, we developed a questionnaire to assess participants’ prior AR experience, preferred learning methods, and interest in a proposed AR-based, 2 × 90-min in-person course. Results: A total of 101 students and 27 lecturers participated. Support for AR in small-group teaching was strong: 96.3% of students and 90.9% of lecturers saw value in a dedicated AR course. Both groups favored its application in anatomy, cardiac surgery, and internal medicine. Students prioritized congenital heart defects, coronary anomalies, and arrhythmias, while lecturers also emphasized invasive valve interventions. Conclusions: There is significant interest in AR-based teaching in cardiovascular education, suggesting its potential to complement and improve traditional methods in medical curricula. Further studies are needed to assess the potential benefits regarding learning outcomes.

1. Introduction

The anatomy and physiology of the heart continue to be challenging subjects for medical students in their daily learning. For example, many students struggle to develop a solid understanding of ECG interpretation during their studies [1]. One key reason is that traditional two-dimensional teaching methods, like textbooks, often fall short when it comes to conveying three-dimensional processes, like cardiac excitation propagation, as they are frequently perceived as overly abstract and complex [2].

Studies have shown that the vast amount of anatomical knowledge that students must acquire during their medical studies, combined with the limited opportunities to apply this knowledge in practice, poses a significant challenge to the anatomical learning process [3]. Moreover, difficult anatomical conditions pose a challenge not only for students as future doctors in their daily learning routines but also for many patients with congenital heart defects who have only a limited understanding of their own condition. A deeper understanding can significantly contribute to better health outcomes [4].

Extended reality (XR) encompasses immersive technologies like virtual reality (VR) and augmented reality (AR), which are transforming modern learning methods. VR allows users to fully immerse themselves in a computer-generated 3D environment, completely replacing the real world, while AR enhances the physical environment by overlaying digital information and interactive elements. These technologies hold the potential to create engaging, hands-on learning experiences that improve comprehension, especially for complex subjects, and increase student motivation [5,6].

Background and Literature Review: Current Applications of AR in Medical and Cardiovascular Education

For physicians, AR enables more targeted and individualized therapy planning and execution. For example, data from cross-sectional imaging (CT or MRI) can be used to create complete three-dimensional representations of the heart, which already allow for full simulation of procedures like transcatheter aortic valve replacement (TAVR) [7]. In procedural planning and preparation, it offers added value through a more precise understanding of the three-dimensional spatial relationships of anatomical structures [8]. In congenital heart surgery, the use of 3D models can positively impact preoperative planning for complex heart defects [9] and is already being used in the form of AR and VR for preoperative education and anxiety reduction in patients [10,11]. Likewise, Oudkerk Pool et al. demonstrated that VR-based preoperative planning can reduce anxiety in patients undergoing congenital heart surgery [12]. The recent literature describes that a three-dimensional model can improve the safety and planning of congenital cardiac surgical treatments and is furthermore suitable for the training of medical professionals and the education of parents [13].

Beyond procedural planning, AR provides interactive and enhanced learning experiences in medical education [14]. For example, Nicholson et al. demonstrated in a randomized control trial that the use of a 3D virtual anatomical model significantly improved students’ understanding and retention of anatomical structures compared to traditional 2D resources [15]. Studies have shown that learning anatomy in groups can enhance learning performance [16]. A meta-analysis by Yammine and Violato highlighted that three-dimensional visualization technologies are particularly effective in anatomy learning settings [17]. Moreover, VR facilitates the exploration of complex anatomy without the need for expansive cadavers [18].

The use of virtual reality (VR), where users are completely immersed in a virtual environment, can further improve the quality of medical education, especially for interventions and surgeries, thereby reducing potential peri-procedural complications [19].

Furthermore, studies have demonstrated that effective education of expectant parents of children with congenital heart defects contributes to their understanding of the heart disease in their unborn child and improves counseling success for fetal heart disease [20]. Biglino et al. also demonstrated that the use of three-dimensional, patient-specific models can improve interaction and communication with the parents of affected children [21].

We believe this technology holds exciting potential for advancing future cardiovascular education. Accordingly, we plan to introduce an AR-based small-group cardiovascular teaching program in Heidelberger Curriculum Medicinale (HeiCuMed), where individual patient hearts and pathologies will be defined, explained, and used to learn about symptoms, treatments, and prognoses. The course itself will be evaluated based on objective structured teaching evaluations, pre-/post-knowledge assessments, and student satisfaction surveys. To tailor this course to the preferences and needs of future learners, we conducted a needs assessment using the online survey tool LimeSurvey.

2. Materials and Methods

To ensure the optimal design of the planned AR course in a small-group format, we conducted a needs assessment among students and instructors of the Heidelberg Medical Faculty using the online survey tool LimeSurvey via Heidelberg University’s portal.

The questionnaire aimed to obtain answers to our primary research questions:

• What are students’ and lecturers’ prior experiences with AR/VR in medical education?
• How do they assess the potential utility of AR for cardiovascular teaching?
• What preferences exist regarding content, format, and timing for AR integration?

HeiCuMed is a modern medical study program structured into five major thematic blocks. It begins with the preclinical years (first to fourth semester) followed by a propaedeutic block that covers the fundamentals of medicine and by specialized blocks in internal medicine, surgery, neurology/psychiatry, and gynecology/pediatrics. Students complete these modules in small groups, receiving hands-on and practice-oriented training. Theory and practice are tightly integrated, ensuring that patient contact and clinical exercises play a key role from the very beginning. Each module concludes with examinations that assess both theoretical knowledge and practical skills. This structured approach effectively prepares students for their future medical careers.

We first conducted a comprehensive literature review to assess the current state of augmented reality in medical education (Figure 1). For this article, we primarily reviewed studies available in PubMed between 2016 and 2025.

Subsequently, we developed a questionnaire designed to capture the needs, preferences, and expectations of both lecturers and students. The collected information serves as a foundation for the future course design. The current developmental status for the HoloHeart System using HoloLense2 (Microsoft) was used to make demonstration videos for visualization purposes. Details on programming and software can be found in the Supplementary methods. The questionnaire included open-ended questions, as well as single-choice and multiple-choice answer options. Additionally, agreement with the presented statements was assessed using a scoring system in the form of a Likert scale. We included specific questions about prior experience with AR and VR, current learning, and teaching methods, as well as the feasibility and relevance of introducing an AR course into the Heidelberg Curriculum Medicinale (HeiCuMed). The questionnaire included 60 items for students and 65 items for instructors. The complete questionnaires for students (Supplementary Tables S1 and S2) and lecturers (Supplementary Tables S3 and F4) can be found in the Supplementary Materials.

The needs analysis was conducted after ethics approval between September 2023 and July 2024. It was conducted in accordance with the declaration of Helsinki. Participation was voluntary, and students did not face any disadvantages for non-participation. Participants consented to their participation after reading the information within LimeSurvey. Participants did not receive any compensation. All data were collected using the online survey tool LimeSurvey and were anonymized. We recruited our participants through informational sessions held during lectures, as well as via faculty-internal flyers and posters without incentives, and participation was anonymous to reduce response bias. However, as a voluntary survey, self-selection bias remains a limitation.

A priori power analysis was not performed, as this was an exploratory survey. However, the total number of respondents exceeded comparable needs-assessment studies and allowed descriptive analysis of trends.

This study focused on descriptive trends and comparisons using non-parametric tests (Mann–Whitney U, chi-squared) where appropriate. The inclusion criteria of this study were the following: participants had to be active medical students or teaching faculty members at Heidelberg University, and all participants had to be legally competent. The exclusion criteria were age under 18 years and incomplete participant information.

3. Results

A total of 101 students (n_total = 101; n_complete = 77) and 27 instructors (n_total = 27; n_complete = 22) participated. General equivalent questions were asked to both students and instructors, covering age, gender, specialty or desired specialty, number of semesters completed, and the start and completion of studies, to allow a comparison of the two sample populations.

Of the student participants, 57 were female, and 44 were male, with a median age of 23 years. Most students (34.7%) were from Block 1 (general internal medicine), followed by preclinical students (first to fourth semester) with 14.9%, and those in the final year internship with 11.9%. Additional participating semesters included Propaedeutic (fifth semester) with 9.9%, Block 4 (gynecology and pediatrics) with 6.9%, Block 2 (surgery) with 5.9%, Block 3 (neurology and ENT) with 5.9%, course-free students with 5.9%, and others with 4% (see

Table 1. Demographics table for students. For description of HeiCuMed Structure for block details, see Figure S1.

Characteristics	Category	Frequency	Percentage
Sex	Female	57	56.4
	Male	44	43.6
Age	<20	6	5.9
[in years]	20–30	91	90.1
	>30	4	4.0
Semester	Block 1	35	34.7
	Preclinical years	15	14.9
	Practical year (PY)	12	11.9
	Propaedeutic block	10	9.9
	Block 4	7	6.9
	Block 2	6	5.9
	Block 3	6	5.9
	Course-free semester	6	5.9
	Others	4	4.0

).

Of the surveyed lecturers, 7 were female, and 20 were male, with a median age of 42 years. Most of the lecturers surveyed came from the field of cardiology (33.3%) but also from anesthesiology (14.8%) and general internal medicine (7.4%), as well as cardiac surgery (7.4%). Other medical disciplines that the participants came from were pediatric cardiology (3.7%), anatomy (3.7%), and physiology (3.7%) (see

Table 2. Demographics table for lecturers. For description of HeiCuMed Structure for block details, see Figure S1.

Characteristics	Category	Frequency	Percentage
Sex	Female	7	25.9
	Male	20	74.1
Age	35	7	25.9
[in years]	35–45	13	48.2
	>45	7	25.9
Field	Cardiology	9	33.3
	Anesthesiology	4	14.8
	General internal medicine	2	7.4
	Cardiac surgery	2	7.4
	Pediatric cardiology	1	3.7
	Anatomy	1	3.7
	Physiology	1	3.7
	Others	7	25.9

).

3.1. Teaching

In total, 96.3% of students (n = 82) rated the introduction of AR-based small-group teaching in the HeiCuMed as meaningful (Figure 2). Only 3.7% found it to be not useful. There was also strong support among the lecturers for the implementation of an augmented reality course in HeiCuMed. Of the 22 instructors surveyed, 20 stated that they considered such an implementation to be beneficial. Only two instructors indicated that they did not find it useful.

3.2. Interest in Augmented Reality

Students (n = 81) were asked about their interest in augmented reality using a scale from 1 (no interest) to 5 (very high interest). The average score was 3.7, indicating increased interest in this technology (Figure 3).

Among the lecturers surveyed (n = 22), there was also a high level of interest in augmented reality. The calculated mean score based on the given rating scale is 3.7.

3.3. Optimal Semester for AR Implementation

Regarding the most suitable semester for implementing the AR course, on the students’ side the participants rated this on a scale of 1 (not beneficial) to 5 (very beneficial). The first semester (anatomy) was rated as the most suitable (score: 4.6), followed by Block 2 (cardiac surgery) (score: 4.4), Block 1 (general internal medicine) (score: 4.2), and PY surgery (score: 4.1). Other rated semesters included PY general internal medicine (score: 3.9) and physiology (2nd semester) (score: 3.8).

On the part of the lecturers surveyed, it was found that the majority of participants consider the first semester, in which anatomy is taught, to be the most suitable for potential implementation (score: 4.7). Furthermore, cardiac surgery (Block 2, score: 4.2) and general internal medicine (Block 1, score 4.0) were also identified by the lecturers as particularly appropriate areas for the planned course. Additional support was expressed for the cardiac surgery rotation (score: 3.9) during the final year internship (FYI) as well as for the field of physiology (score: 3.9), followed by the internal medicine rotation (score: 3.5) during the final year (Figure 4).

3.4. Favored Teaching and Learning Content

We surveyed the participants regarding their preferences for the content of a potential AR course. In this process, we presented typical cases from cardiovascular education, and the participants were asked to rate each proposed topic on a scale from 1 (no benefit) to 5 (high benefit) (Figure 5).

A total of 81 students participated in the voting. The visualization of anatomy in congenital heart defects (score: 4.6) ranked first, followed by the visualization of anatomy in coronary anomalies (score: 4.6) and the depiction of excitation propagation in arrhythmias and pacemaker stimulations (score: 4.5). In fourth place was the visualization of electrophysiological procedures, such as the ablation of atrial flutter (score: 4.4).

On the lecturers’ side, a total of 22 participants cast their votes. Here, too, the visualization of anatomy in congenital heart defects (score: 4.6) ranked first, followed by the visualization of anatomy in coronary anomalies (score: 4.3). However, unlike the students, the depiction of invasive valve procedures (score: 4.3), such as TAVR or Mitra Clip, ranked third. In fourth place was the visualization of electrophysiological procedures (score: 4.1), such as the ablation of atrial fibrillation.

3.5. Previously Used Learning and Teaching Methods

As part of designing a future AR-based small-group teaching format, we were also interested in the tools and methods students have used for learning so far, as well as the tools instructors have employed to deliver course content.

To determine this, we provided a range of learning and teaching methods, such as textbooks, lecture slides, and videos, as well as augmented reality and virtual reality. We then aimed to find out how familiar these tools are to our surveyed participants and how frequently they are used. We asked the participants to rate, using a scale from 1 (strongly disagree) to 5 (strongly agree), how effective they consider each learning and teaching method for conveying practical skills as well as for learning and teaching topographical content. Additionally, we included the option “I have not used this before” to capture which tools have not yet been incorporated into the learning or teaching process among the respondents.

We first inquired about the tools used for learning and teaching the respective practical skills. The following tools were provided as options: lecture slides, videos, textbooks, group learning, online reference materials, augmented reality, virtual reality, and flashcards. Online reference materials, videos, flashcards, and group learning were particularly popular among the students (n = 77) (Figure 6).

In contrast, augmented reality and virtual reality were unfamiliar to them. Among the lecturers (n = 22), group learning, lecture slides, and videos were considered the most effective methods. Here as well, augmented reality and virtual reality were unfamiliar.

Next, we asked which teaching and learning methods are most effective for learning and teaching topographical content in anatomy and physiology. The following tools were provided: lecture slides, study groups, textbooks, augmented reality, online reference materials, virtual reality, flashcards, model-based learning, and videos. The students surveyed indicated that model-based learning, as well as online reference materials and textbooks, were particularly effective. Augmented reality and virtual reality were mostly reported as not yet used (Figure 7).

Among the surveyed instructors, model-based learning, lecture slides, and group learning were considered especially effective. Augmented reality and virtual reality were also largely unused in this group.

3.6. Prior Experience with AR in Medical Education

We asked our participants whether they had prior experience with augmented reality (AR) or virtual reality (VR) as part of their studies. The vast majority of students (n = 93) reported having no experience with AR or VR (82%). Only 4% of the surveyed students had previously encountered augmented reality in their medical education. A similar pattern was observed among the instructors (n = 25). Here, only 4% of the surveyed instructors indicated having prior experience with augmented reality, while 80% reported having no experience with either AR or VR (Figure 8).

4. Discussion

4.1. What Are Students’ and Lecturers’ Prior Experiences with AR/VR in Medical Education?

Based on the observed results, there is significant interest in AR from both students and instructors. However, it must be emphasized that AR and VR technologies have not yet been fully integrated into clinical practice, and education is no exception there [22]. While there has been a rapid increase in AR-based projects in medicine over a relatively short period, very few of the surveyed participants had prior experience with augmented reality. Therefore, alongside the establishment and implementation of a course structure, there is also a need for education in this technology itself. Only through proper interaction with the technology can meaningful learning and teaching outcomes be achieved [6]. Many students are already using innovative learning methods such as online websites and videos. However, AR and VR technologies are—due to their novelty and also cost aspects—not yet established in everyday learning.

4.2. How Do They Assess the Potential Utility of AR for Cardiovascular Teaching?

The results of the survey indicate that a potential AR course could be beneficial: both students and instructors stated that they consider group learning as well as learning with models to be effective or frequently used. Both of these—group learning and model-based learning—are key components of our planned course. Building on this point, it is worth considering whether it would be beneficial to train specific lecturers in augmented reality, enabling them to deliver the course in a standardized manner. This would help ensure that the selection of a particular instructor does not influence or distort the learning outcomes [6,23].

4.3. What Preferences Exist Regarding Content, Format, and Timing for AR Integration?

Looking at the topics requested by both students and instructors, it becomes apparent that these pathologies are primarily encountered in larger hospitals. Congenital heart defects and coronary anomalies are important but relatively rare conditions in standard hospitals. Since we plan to build our models based on real patient data, it is particularly sensible to implement this at a larger institution, such as a university hospital. Here, unlike in smaller hospitals, these patients present more frequently, and there are also specialized clinics for these conditions. This allows us to draw on the expertise and case database of a specialized team in our course, enabling us to train cardiology-focused students in our planned AR course on these rare conditions.

At the same time, it is also important to us not to overlook the more common diseases and treatments. For this reason, we consider visualizations of impulse propagation in arrhythmias and pacemaker stimulations, as well as representations of electrophysiological procedures (e.g., ablation of atrial flutter), to be highly valuable (Figure 9).

With regard to the results obtained in Section 3.5, it can be stated that learning in groups is not only a relatively widespread learning method but can also be effectively combined with AR. For this reason, we are of the opinion that conducting the planned AR course in multiplayer mode should be an essential component of the course concept.

With the help of a multiplayer mode, instructors and students can simultaneously view and interact with the same three-dimensional model in augmented reality small-group instruction. This allows students to actively verify whether their acquired knowledge is correct and complete. Augmented reality thus creates a new form of active learning, which has been proven to lead to better outcomes than purely passive learning [24]. Therefore, augmented reality can be considered a valuable complement to traditional teaching methods [25]. The multiplayer mode in augmented reality (AR) not only promotes active learning but also enables real-time collaborative work. Students can apply their knowledge directly, identify mistakes immediately, and work together to develop solutions. The visual and interactive components make complex material more tangible, which can improve understanding and retention [26] (

Table 3. Benefits and challenges of a possible AR-based small-group learning course.

BENEFITS	CHALLENGES
Improved spatial understanding Better observation of group learning processes Didactic variety and more interactive teaching Increased motivation and engagement Easy repetition without resource consumption Practice-oriented skill development	Lack of prior exposure Cost of devices Technical setup and maintenance effort Risk of feeling overwhelmed by new technology Possible distraction from learning objectives

).

Furthermore, AR may vary based on cultural openness to technology, faculty training, and infrastructure. Future multicenter studies could deliver new data related to this phenomenon.

Another important consideration is the small-group format planned for our AR course. This decision is primarily driven by the apparently high costs of AR headsets (e.g., Microsoft HoloLens2) [6]. Consequently, the success of both this study and the course itself will depend heavily on the active engagement of participating students and instructors, as well as sufficient funding.

In summary, this course places a strong emphasis on anatomical and physiological complexity, while simultaneously incorporating established standards such as regional and global wall motion abnormalities into our clinical case discussions.

In our view, understanding the heart’s electrophysiology forms not only the fundamental basis for diagnosing cardiac diseases but also for understanding their treatment options.

4.4. Limitations

In our survey, we exclusively gathered feedback from students and instructors within the medical faculty at Heidelberg University. This makes our analysis a single-center study, limiting the direct applicability of our results to other universities. Nevertheless, we believe that an AR course would also be valuable at other institutions. Through academic exchange with colleagues from other universities, whether during lectures or conferences, we have observed a significant demand for innovative teaching and learning methods, particularly in the field of (cardiovascular) education, and the need for scientific evaluation of potential learning benefits. Key elements of our study (e.g., modular curriculum, AR-ready infrastructure, and the need for anatomy education enhancement) can be found in other institutions too. This is why we think that the approach is transferable.

Moreover, the data collection period spanned nearly a year (September 2023 until July 2024), which may introduce temporal biases. However, the curriculum and exposure to AR/VR remained stable during the data collection window.

Participation was anonymous, uncompensated, and without incentives, in an effort to minimize response bias. Nonetheless, due to the voluntary nature of the survey, the potential for self-selection bias cannot be fully excluded and should be considered when interpreting the findings.

5. Future Directions

Preliminary evidence from related pilot testing (unpublished) supports improved 3D comprehension, comparable to 3D-printed hearts based on the conducted needs analysis, so the course establishment and implementation will now begin. The success of the course itself will be evaluated using the following criteria: objective structured teaching evaluations, pre-/post-knowledge assessments, and student satisfaction surveys. To ensure that the participants’ enthusiasm is based on actual utility rather than mere novelty, we have planned structured feedback rounds, blinded assessments of knowledge improvement, and a comparison with traditional teaching to distinguish utility from novelty.

Beyond our institution, we believe the findings and framework of our study hold broader relevance and transferability to other medical schools. Key elements of our approach—such as the modular curriculum structure, the use of AR-ready infrastructure, and the identified need to strengthen anatomical education—are present in many other academic environments worldwide. This alignment supports the potential for adaptation of our concept across institutions with similar educational challenges and infrastructures, offering a valuable model for the integration of AR in medical education on a larger scale.

Towards Implementation: A Proposed Protocol for AR Integration in Medical Education

Based on a university-wide survey involving both medical students and teaching faculty, there is a growing interest in using innovative technologies to enhance cardiovascular education. Augmented reality (AR), particularly when used with devices like the Microsoft HoloLens, has emerged as a promising tool to support the teaching of complex anatomical and pathophysiological content. This project aims to develop a modular, small-group AR-based teaching course that incorporates patient-specific heart models to supplement and enrich traditional cardiovascular instruction.

• Phase 1: Conceptualization and Didactic Integration

The initial phase involves aligning the course with the existing curriculum and defining clear educational objectives. The focus will be on improving the understanding of cardiac anatomy and topography, especially congenital heart defects, electrical conduction disorders, coronary anatomy, and valvular interventions. The course is designed to allow students to engage with clinical cases comprehensively, from initial symptoms and diagnostics to therapeutic decision making and follow-up care.

The course will be structured in multiple sessions, beginning with an introductory unit on AR technology and device handling. This will be followed by thematic modules covering key content areas: normal heart anatomy, congenital defects, arrhythmias, interventional procedures, and a final case-based session that allows students to manage a complete patient case using AR heart models. This culminating session will guide participants through every step of clinical reasoning, using a fully interactive, patient-specific 3D heart model.

Didactically, the course is planned as a blended learning format. Self-paced digital learning materials will prepare students for in-person sessions, which will be conducted in small groups of four to six participants in AR multiplayer sessions with one instructor. This format promotes active learning, hands-on engagement, and direct feedback from instructors.

• Phase 2: Technical and Logistical Preparation

Simultaneously, the technical infrastructure must be established. Representative patient cases will be selected, and imaging data (CT, MRI, or ultrasound) will be processed to create detailed 3D heart models. Using segmentation software, such as 3D Slicer 5.8.1 or comparable alternatives, DICOM datasets will be transformed into high-quality digital reconstructions suitable for AR use.

To enable immersive interaction, these models will be optimized for AR devices. The implementation will utilize platforms such as Unity or other suitable development environments to ensure stable and high-performance visualization. Interactivity features like rotation, transparency layers, annotations, and animations (e.g., cardiac conduction pathways) will enhance educational value.

The physical setup will require dedicated lab space with reliable Wi-Fi, power sources, and open movement zones. Devices like the HoloLens will be equipped with user-friendly interfaces, enabling intuitive navigation of the 3D heart models. Multi-user synchronization features will also be explored, allowing all participants to interact with the same virtual model in real time. Faculty training for future course tutors will be established.

• Phase 3: Pilot Implementation and Evaluation

The initial pilot phase will involve a selected group of clinical-year students, for example, those in their final years or in the practical year (PJ). The aim is to test the feasibility of the course format, collect feedback, and identify areas for improvement both technically and pedagogically.

Evaluation will be conducted using a combination of quantitative surveys and qualitative interviews with both students and instructors. Pre- and post-testing will assess learning outcomes, such as improvement in anatomical comprehension or clinical reasoning related to the cases discussed. Particular attention will be paid to usability, AR experience quality, and overall perceived value in clinical education.

Based on the feedback, the course content and AR interface will be iteratively improved. This may include technical enhancements (e.g., better control mechanisms, smoother animations), pedagogical adjustments (e.g., pacing, case complexity), or additional learning tools (e.g., voice commands, interactive quizzes).

• Phase 4: Curriculum Integration and Scaling

Following successful pilot implementation, the course will be formally integrated into the medical curriculum. Depending on institutional preferences and logistical factors, it may be offered as an elective module, an embedded component of the cardiology course, or as a stand-alone session within the clinical skills lab.

Long-term goals include expanding the AR-based teaching approach to other medical disciplines, such as pulmonology, nephrology, or emergency medicine. Interprofessional learning opportunities, involving students from nursing or medical technology programs, may also be developed.

Scientific evaluation and publication of outcomes are planned to share findings with the broader medical education community. Presenting results at academic conferences and applying for funding through educational foundations or innovation programs will help support further development, scalability, and technical advancement of the project.

The introduction of an AR-supported teaching module for cardiovascular education represents an innovative advancement in medical training. By combining patient-specific 3D heart models with interactive case-based learning, this approach enhances anatomical understanding and strengthens clinical reasoning. With thoughtful implementation and rigorous evaluation, the project has the potential to become a scalable and transferable model for AR integration across multiple areas of medical education.

6. Conclusions

Based on the data collected, augmented reality demonstrates not only strong potential but also widespread support for its role in transforming cardiovascular education. Rather than serving merely as a complementary tool, AR should be purposefully and systematically integrated into teaching through structured, needs-driven protocols that directly address identified learning gaps and stakeholder expectations. This approach ensures that AR becomes an embedded, pedagogically meaningful component of modern medical education.