The labor market situation in the area of nursing and caretaking is very tight already. In the future, the need for skilled healthcare workers will increase even further due to demographic change. New skills including language learning are required for healthcare workers in order to keep pace with the changing healthcare landscape, overcome language barriers and ensure that they provide the best possible care to their patients. Healthcare workers must be able to communicate with patients in their native language or at least have a basic understanding of the language. To address this challenge, we present a Mixed Reality (MR)-based language learning system aimed at supporting linguistic competence and communication in healthcare simulations. This paper describes the process for modeling a Mixed Reality application for language learning for medical purposes. We applied the analysis, design, development, implementation, and evaluation (ADDIE) approach to design a VR healthcare simulator in the form of modularised units. Using prototype, we conducted a user study with 7 novices to test the system’s usability. Our findings show (1) effectiveness of the system in transferring skills to real-world health-care environments and, (2) realistic learning experience to users. Using the solution, we envision inexperienced healthcare workers to achieve language competencies faster and be better prepared to enter actual work environments.

 Keywords: Virtual reality, Virtual Reality simulators, Virtual Reality language learning, Language learning


Recently the healthcare sector in Europe and beyond has reported a substantial deficit in healthcare provision and an increasing need for skilled healthcare workers. In the future, the need for skilled healthcare workers will increase even further due to demographic change. Data provided by the World Health Organization (WHO, 2022) indicate that within the European region, the doctor density, that refers to the number of active healthcare workers divided by the population, varies from 17.3 per 10 000 people in Tajikistan and 17.5 in Kyrgyzstan, to 88.7 in Monaco. Western Europe had the highest doctor density (45.5). Nurse density varies significantly by country, from 27.0 in Turkey to 183.7 in Switzerland and 202.7 in Monaco. Countries in the European Region with the lowest densities are those in the western Asia subregion (48.2), followed by those in central Asia (48.9), southern Europe (61.7), and eastern Europe (65.3). Data indicate the increasing demand for community-based care that requires a healthcare workforce with the right composition of professionals and skills (WHO, 2022). A potential solution to the deficit in healthcare is to attract more workers from other EU countries or even from non-EU countries, who must possess the necessary minimum qualifications as well as professional language abilities. Language barriers in the medical field cause miscommunication between the patient and the medical staff, which lowers both parties’ satisfaction and reduces both the quality of healthcare delivery and patient safety (Al Shamsi et al., 2020). Healthcare workers must be able to communicate with patients in their native language or at least have a basic understanding of the language (Olimpia et al., 2021). The importance of language learning for healthcare professionals lies in the fact that it allows them to communicate effectively with patients from diverse cultural and linguistic backgrounds (Bonder et al., 2001). It is imperative that healthcare practitioners have cultural competence in order to recognize and address cultural values, beliefs, and practices when intervening in treatment, which is likely to result in more successful outcomes (Bonder et al., 2001). Moreover, language barriers can lead to misunderstandings and errors in medical care, which can have serious consequences for patients (Waters et al., 2023). Healthcare students and professionals need to practice the language in assimilated healthcare context. The high-costs of placement constraints on the environment restrict access to real-life healthcare facilities, and therefore they cannot overcome the need for language competence of healthcare professionals today. Therefore there arises a necessity to introduce more interactive learning courses and training to enable contextualised and situated language communication for healthcare practitioners.

In this work we address this gap by leveraging one of the emerging technologies that entail the potential to accelerate the development and improvement of the learning competences. Mixed reality  (MR) along with the integrated speech recognition applications supported by Artificial Intelligence (AI) allows a learner to engage with interactive digital enhancements – individually or in a group – in real or digital worlds simulating a typical working environment and standard situations of the healthcare profession. Virtual highly valuable didactic environments comprehend an important number of learning-related strategies and realities, provides freedom in the development process and several valuable and applicable features for foreign language education (Peixoto et al., 2021). We applied the analysis, design, development, implementation, and evaluation (ADDIE) approach (Colpaert, 2006; Caws, 2013) to design a MR healthcare simulator in the form of modularised units. Following the ADDIE model, our process began with the analysis phase, where we collaborated with language and healthcare experts to identify the desired learning outcomes. Next, we proceeded with the design phase, focusing on identifying assessment strategies that aligned with the desired performance. Finally, in the development phase, we designed the learning activities to meet the established goals. As a part of the learning content, we provide a MR platform that accommodates realistic healthcare scenarios, incorporates instant audiovisual feedback and enables students’ active participation and collaboration.  Through MR, the system can transfer healthcare conditions into a MR platform for addressing the communication needs (both receptive and productive) and eventually the transition to a real healthcare workplace. We implemented a training module in the form of prototype comprising one unit and conducted a user study with 7x healthcare students, 5 language instructors and 1 healthcare instructor to evaluate the usability of the MR system, and demonstrate the user engagement of the system to transfer skills into the real-world environment. Through the findings from the study, we want to answer the following research question:

What pedagogical and technological factors/aspects to consider while designing healthcare simulations for language learning and guided activities for healthcare professionals in a MR platform 

Thus, the contributions are as follows:

  • A learning design rationale developed using the ADDIE approach in learning sciences and through discussion with healthcare and language learning experts that shows what to consider while designing an effective language training system for language learning for healthcare professionals;
  • A design framework encompassing structured learning modules to achieve language competence at A2 and B1 Common European Framework of Reference for Languages (CEFR) levels; and
  • The user study and evaluation results to validate the system’s usability using a minimum viable prototype, to evaluate the performance of the proposed alternative in MR towards the development of language learning skills for healthcare professionals

We envision that this work provides insights to the Computer-Assisted Language Learning (CALL) and Human Computer Interaction (HCI) community to better understand how to leverage MR systems in healthcare training processes.