Introduction

Health professional education has traditionally relied on educational strategies, clinical rotations, and hands-on activities to prepare students for their roles and equip them with the knowledge, skills, and competencies necessary for safe patient care. Despite these well-established methodologies and pedagogies, several longstanding barriers in health education persist. These issues include maintaining educational quality amidst rising student numbers, securing appropriate clinical placements, and keeping pace with rapidly changing medical knowledge and practices (Cook et al., 2011; Gates et al., 2012). Furthermore, the COVID-19 pandemic has complicated the educational landscape by necessitating shifts toward distance and blended learning, thus presenting new challenges and opportunities for both teachers and students (Almeida, 2023; Chan et al., 2024; Ofosu-Ampong et al., 2024). Health educators likewise face numerous challenges in providing adequate education. One major challenge is the limited availability of medical facilities, which are essential for hands-on experience. As competition for these facilities increases, it becomes difficult for educators to ensure that all students have a positive learning experience. The limited number of clinical sites means that students might not get adequate exposure to diverse medical conditions and procedures, potentially compromising their preparedness for real-world practice (Grainger et al., 2024). Additionally, faculty must continually update their courses to incorporate new developments in medical science and technology – a process that can be resource-intensive and time-consuming (Harder, 2010; Silva et al., 2023). Traditional instructional methods, such as lecture-based learning, may not always meet the diverse learning needs of students. These methods often fail to engage students actively and may not effectively develop critical thinking and problem-solving skills, calling for new and adaptive approaches that leverage interactive and experiential learning techniques.

The continuous disruptions caused by pandemics, calamities, and other crises have further highlighted the critical importance of technology-enhanced learning (TEL) in sustaining both the continuity and quality of health education. TEL has emerged as a crucial tool in addressing the myriad challenges faced by health educators (Choi-Lundberg, 2023; Naeem et al., 2023), with a broad array of technologies, including simulation, virtual reality (VR), augmented reality (AR), and other digital tools improving learning experiences and enhancing educational outcomes (Almeida, 2024; Cabero-Almenara et al., 2023; Miranda & Tolentino, 2023). For example, simulation-based education has gained recognition as an alternative to traditional clinical teaching, allowing students to practice clinical competencies in a secure, controllable environment, which has been shown to enhance knowledge acquisition and test scores (Gates et al., 2012). According to a meta-analysis by Kim et al., (2016), simulation-based interventions across various domains most effectively improve cognitive skills. Integrating TEL into health professional education is therefore crucial for overcoming the multifaceted challenges that educators and students face today. By leveraging modern instructional technologies and innovative solutions, TEL enhances educational effectiveness and ensures that future health professionals are thoroughly equipped to meet the rigorous demands of their field.

Main Focus of the Chapter

This chapter focuses on exploring different TEL approaches and highlighting their critical importance in health professions education. As the healthcare landscape continues to evolve, the integration of advanced technologies into educational practices becomes increasingly essential. TEL not only enhances the teaching-learning process but also ensures that future health professionals are well-versed in the technologies they will encounter in clinical assessments and interventions. Given the continuous advancements in educational technology, there is a pressing need to bridge the research gap concerning the effective integration of these technologies in health professions education. Despite the proliferation of digital tools and platforms, there is still much to learn about optimizing their use to enhance learning outcomes, ensure equitable access, and address ethical concerns such as data privacy and algorithmic biases. This chapter is important because it reviews current trends and applications that may guide educators, policymakers, and technology developers in creating more engaging, efficient, and inclusive educational environments. Overall, the chapter underscores the necessity of ongoing research and thoughtful technology integration to prepare health professionals who are not only competent and knowledgeable but also adaptable to the ever-changing demands of the healthcare field.

Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly transforming the landscape of health professions education. AI encompasses a broad array of technologies designed to mimic human cognitive functions (e.g., learning, problem-solving, and decision-making, while ML is a subset of AI that focuses on the ability of systems to learn from data and improve over time without being explicitly programmed (Maaliw et al., 2022; Mishra et al., 2024). The inception of AI dates to the 1950s, and while it might once have seemed a distant future akin to the visions of Aldous Huxley or George Orwell, it is now a palpable reality affecting daily life profoundly. In health professions education, these technologies are employed to create adaptive learning environments and to facilitate the simulation of complex medical scenarios. By integrating AI and ML into educational tools, institutions can offer customized learning experiences that adapt to each student's individual learning pace and style (Lobo et al., 2024). One example is using a simulation program that can replicate real-life medical emergencies or surgical procedures with great accuracy. These simulations allow students to practice and hone their skills in a risk-free environment and help them gain confidence in their decision-making abilities. AI-driven simulations are particularly effective in training students for high-stakes environments where quick and accurate decision-making is crucial. For example, AI can generate virtual patients (see Figure 1) with diverse symptoms and histories and then require students to diagnose and treat these virtual patients as they would in real life (Suárez et al., 2022). This simulation training is highly effective in enhancing students' cognitive skills, as they can repeatedly practice complex scenarios and receive instant feedback on their performance.

Furthermore, implementing AI and ML in health professions education extends beyond training and into assessment and feedback (Miller et al., 2024). AI systems can analyze a student’s performance in real-time and provide tailored feedback that can help pinpoint areas of weakness and recommend targeted studies or practices. This personalized approach makes learning more efficient and engaging, as students can see measurable improvements in their skills and knowledge base. Moreover, AI and ML can help educators and institutions monitor the effectiveness of their programs and make data-driven decisions to improve their curriculums. The predictive capabilities of AI can also be used to identify students who may be at risk of falling behind, allowing for early intervention to keep them on track. The implications of AI and ML in health professions education are profound. These technologies promote a significant shift from a one-size-fits-all educational model to a more customized and responsive approach that can meet the diverse needs of students. Additionally, by automating routine tasks, AI frees educators to focus more on mentoring and one-on-one student interactions. Nevertheless, integrating AI and ML raises several challenges, including ethical considerations around data privacy, the need for robust data sets to train AI systems effectively, and the potential for technology to reinforce existing biases if not carefully managed. As these technologies continue to evolve, it will be essential for educational institutions to address these challenges head-on to fully harness the potential of AI and ML in shaping the future of health professions education.

Smart Classrooms

The transition into the 21st century marks a revolutionary phase in the field of education, punctuated significantly by the integration of smart classrooms. This transformative pedagogical journey has shifted traditional teaching paradigms from their analog roots into a digital era dominated by tools like PowerPoint and digital projections. The teaching-learning process, which previously leaned heavily on paper-based resources and handwritten notes, now embraces a range of digital technologies. This shift challenges educators to continuously update their technical and pedagogical skills to cater to a digitally-savvy student body. Smart classrooms, as defined by Song et al., (2014), epitomize the integration of advanced technologies such as the Internet of Things, Cloud Computing, and Big Data into the educational environment. These classrooms are not merely spaces equipped with high-tech tools but are ecosystems designed to optimize teaching and learning through the strategic use of a variety of media (see Figure 2). The iSMART model highlighted in the literature provides a comprehensive framework comprising infrastructure, network sensors, central management, augmented reality, real-time recording, and ubiquitous technology. Although not every component is essential in every smart classroom setting, the model underscores the potential of such environments to enhance educational outcomes. Furthermore, Alfoudari et al., (2023) illustrated that the adoption of smart classrooms need not be prohibitively expensive, as educators can leverage existing devices like tablets, phones, and smartwatches to enrich the learning experience. This approach not only makes technological integration feasible but also accessible, particularly in socio-economically developed regions.

The challenges and opportunities presented by smart classrooms extend beyond the technological dimension. According to Alfoudari et al., (2023), the effectiveness of these environments is also influenced by social factors such as personalization, involvement, and interactivity. Personalization addresses the need for a healthy and safe learning environment, while involvement and interactivity are crucial for fostering proactive behavior and motivation among students. These elements are vital for creating a dynamic and engaging learning experience that encourages the acquisition of new skills through innovative teaching methods like gamified tasks and inverted classrooms. The push for more active and engaging teaching-learning practices necessitates a sustained pedagogical investment through dedicated pedagogical offices or departments (Acut et al., 2024; Diaz et al., 2024; Kononowicz et al., 2019). This support structure is crucial for helping educators transition to and excel in smart classroom settings, which consequently promotes continuous experimentation and improvement akin to a clinical pilot project. Investing in smart classrooms, therefore, is not just a technological upgrade but a comprehensive strategy aimed at preparing future professionals. Studies by Dai et al., (2023) and Phoong et al., (2019) further validated this investment, indicating that smart classrooms significantly enhance student engagement, performance, and overall attitude toward the educational process. Such environments not only meet the current demands of educational technology but also set the stage for addressing future challenges, ensuring that both students and teachers are active participants in a continually evolving educational landscape.

Extended Realities

Extended Reality (XR) is an umbrella term for technologies that create immersive experiences by merging the physical and digital worlds (Miller et al., 2024). It has three main types: virtual reality (VR), augmented reality (AR), and mixed reality (MR). Like other emerging technologies, XR is revolutionizing the educational sector by paving the way for creating and making learning experiences more engaging, accessible, and potentially effective. For instance, XR plays a role in creating immersive experiences where it might be impractical or impossible for both students and teachers to be in place or situations (MacCallum, 2022). XR also provides more than immersive experiences. It also helps make passive lectures engaging, in which students can actively participate, mainly through simulations, experiments, and problem-solving activities (Tunur et al., 2021). Accessibility is also another advantage, as it can reduce and bridge the gap in geographical physical limitations. For instance, through XR, schools can accommodate students situated in remote locations, help them participate in virtual tours, and provide physically challenged students with a way to participate and offset disruptions in their education (Petil Jr et al., 2024; Rameshwar & King, 2023). In the case of health professions education, XR is being embraced to improve training and education among health professionals. For example, VR simulations allow soon-to-be surgeons to practice complex procedures in safe and controlled environments before operating on actual patients (Bakhuis et al., 2023). XR can also create scenarios that may help students or medical professionals improve and develop their soft skills, such as communication, empathy, and teamwork (Beverly et al., 2022). Lastly, XR can also help medical professionals treat mental health, where exposure to specific environments helps in therapy and relaxation among patients (Jones et al., 2023).

XR is transforming education across various fields of health education by providing more immersive and interactive training and educational experiences to both students and health professionals. XR is also seen to help improve academic outcomes and deliver better patient care. For example, in medicine, VR simulations help medical students practice complex procedures, and AR aids in patient data by overlaying the information with real-life scenarios (Papadopoulou et al., 2019). In nursing, creating realistic environments for training nursing students for various situations is now possible through XR (Koukourikos et al., 2021). Other instances where XR is beneficial include physical and occupational therapy, speech-language pathology, radiology, and respiratory therapy (Andrews et al., 2019). XR is being applied in various simulation-based learning contexts. For instance, medical students and professionals can rehearse complex procedures before operating on real patients. Additionally, they can practice their skills in administering specific medications and performing various medical tasks (e.g., CPR; see Figure 3) in a realistic and controlled setting. Immersive simulation-based training also provides situations where learners must be prepared for high-stakes, high-pressure scenarios, improving and practicing their soft skills such as critical decision-making and communication. In anatomy, kinesiology, and physiology, XR is used to create interactive 3D visualizations of human anatomy, particularly human organs (Stirling & Moro, 2020). For professional training and education, XR supports health professionals in their quest for lifelong learning and continuous skills updates (Beverly et al., 2022). Advancements in XR allow them to access and engage with medical topics and lectures more effectively. Participation in various training programs and telemedicine is now feasible through XR regardless of location (Papadopoulou et al., 2019).

Mobile Learning Applications

Mobile learning applications are software designed for use on mobile devices like smartphones and tablets to facilitate learning. These applications offer flexible and accessible learning opportunities, making them suitable for both formal and informal educational settings (Çalış et al., 2023; Garcia, 2019; Hashim et al., 2024; Mansouri et al., 2020; Miranda, 2024; Park, 2011). As of 2024, there are more than eight million smartphone apps, with the number of educational apps increasing from 439,000 in 2021 to 455,000 in 2022. Educational apps rank as the second largest sector in the Google Play Store and the third in the Apple App Store (Wylie, 2024). The adoption of mobile learning applications has proven particularly beneficial in health and professional education. These applications are highly appealing to health sciences educators and professionals due to their numerous affordances (Alhamad & Agha, 2023; Garcia & Oducado, 2021). Studies have highlighted the positive impact of mobile learning applications on health professionals and undergraduate clinical students, noting their potential to improve and enhance learning and clinical experiences (Fuller & Joynes, 2015). The COVID-19 pandemic in 2020 further accelerated the adoption and usage of mobile learning applications in the education sector, leading to a significant transformation in delivery methods (Treceñe, 2022).

The use of mobile learning applications can provide several key benefits that enhance the educational experience for health professionals. Two critical strategies in mobile learning applications are personalized learning and microlearning. Personalized learning tailors educational experiences to meet learners' needs, preferences, and learning styles. It promotes self-directed learning, allowing students to progress at their own pace and focus on areas needing improvement. This individualized approach has been shown to increase engagement and motivation among learners, as it caters to their specific needs and interests. Microlearning, on the other hand, focuses on small, bite-sized learning units that can be easily consumed and understood. Studies have demonstrated that microlearning is effective in knowledge acquisition, satisfaction, and retention among health professionals. This approach provides just-in-time training, repetition, and targeted learning, which are essential for continuous professional development. By breaking down complex information into smaller, manageable chunks, microlearning helps learners absorb and retain information more effectively (Yousef et al., 2023). The integration of personalized learning and microlearning into mobile learning applications makes them more appealing, effective, and engaging for users. These strategies enhance users' knowledge, confidence, and performance by providing tailored, on-demand learning experiences. For example, future dentists can use mobile apps to access up-to-date medical information, clinical guidelines, and case studies that are relevant to their practice (Figure 4). This immediate access to information helps them make informed decisions and provide better patient care.

Digital Game-Based Learning

Digital Game-Based Learning (DGBL) represents another transformative approach in the field of health professions education. Arif et al., (2024) and Xu et al., (2023) have noted that DGBL is particularly effective for simulating complex clinical environments (e.g., surgical procedures and patient care scenarios) that require high levels of skill and precision. These immersive environments allow students to engage in realistic simulations and provide a safe space to refine their skills without the pressures and risks associated with real-life practice. The evolution of DGBL has been marked by significant technological advancements over the decades. Initially focused on basic knowledge and skill acquisition through relatively simple video games (e.g., Arayata et al., 2022; Cortez et al., 2022; Parel et al., 2022), the field has expanded to incorporate sophisticated technologies such as VR, AR, and AI. These technologies enhance the realism and interactivity of educational simulations, which consequently offer more engaging learning experiences (Arif et al., 2023; Arif et al., 2023). For instance, VR can transport students into a three-dimensional world where they can explore human anatomy in detail, while AR provides real-time procedural guidance that can be overlaid in physical environments – both enhancing the depth and applicability of learning experiences.

Implementing DGBL in health professions education requires thoughtful integration and collaboration between educators and technology developers. To maximize the effectiveness of DGBL, educational institutions should ensure that these technologies are seamlessly integrated into the curricula. This might involve incorporating DGBL into existing courses or developing new modules specifically leveraging digital gaming technologies. Additionally, educators need to be adequately trained to utilize these technologies effectively, which involves understanding their capabilities and limitations (Volejnikova-Wenger et al., 2021). However, integrating DGBL also presents several challenges, including the high costs associated with technological setups and potential resistance from faculty accustomed to traditional teaching methods. Institutions can overcome these barriers by seeking external funding and demonstrating the tangible benefits of DGBL through pilot programs and success stories. Moreover, developing mobile-friendly DGBL solutions (see Figure 5) can improve accessibility, ensuring all students benefit from these learning tools (Aksoy & Sayali, 2019; Arif et al., 2024). Robust assessment frameworks are necessary to assess the impact and effectiveness of DGBL. These might include objective structured clinical examinations, pre-and post-tests, and detailed student feedback surveys, which can provide valuable insights into how DGBL enhances learning outcomes (Fortepiani, 2023). By tracking student performance and comparing it with traditional teaching methods, educators can better understand its effectiveness and refine their approaches accordingly.

Virtual Worlds and Metaverses

Recently, virtual worlds and metaverses have gained significant interest in the health and education sectors. Their potential is dependent on offering immersive, interactive digital environments where users can interact with each other and digital objects (Arif & Nurhayati, 2022; Garcia et al., 2023). These technologies create virtual hospitals, clinics, and training environments, which allow for realistic simulations of clinical procedures, patient interactions, and collaborative medical training. The benefits of these settings are manifold, providing a safe and controlled environment for practice, which enhances the educational experience significantly (Qiu et al., 2022; Tan et al., 2022). Initially a domain dominated by entertainment and gaming industries, these technologies have made significant inroads into educational sectors, particularly in health professions. The current trend in medical education leverages immersive simulations and collaborative learning spaces that mimic real-world clinical settings, thereby making medical education more interactive and engaging. Virtual worlds and metaverses not only enhance experiential learning by allowing students to practice procedures in a risk-free environment but also improve their skills and confidence. Furthermore, these platforms facilitate interprofessional collaboration, enabling students from different healthcare fields to work together in simulated environments. This approach fosters crucial teamwork and communication skills needed in clinical practice (Bhatia & Joshi, 2023; Suh et al., 2023).

Supporting these virtual environments, core technologies like VR and AR are utilized to create realistic, interactive simulations (see Figure 6) while blockchain technology ensures the security and integrity of educational records, and AI adapts learning experiences to the needs and progress of individual students, providing tailored feedback and guidance (Hussein et al., 2019). Developing these virtual worlds for health education demands a user-centered approach that involves close collaboration with healthcare professionals. This collaboration helps ensure the relevance and effectiveness of the simulations by integrating realistic clinical scenarios and educational objectives and ensuring ease of use for educators and students alike. Integrating virtual worlds and metaverses into health education curricula involves creating virtual internships, simulation-based assessments, and modules for continuous professional development. These strategies ensure that students gain practical experience, receive immediate feedback, and enhance overall learning outcomes (Garcia et al., 2024; Zaidi et al., 2024). The integration process should be complemented by adequate training for educators and continuous evaluation to refine and improve virtual learning experiences (Kye et al., 2021). Future research in virtual worlds and metaverses should focus on enhancing the realism and interactivity of simulations. Developments in haptic feedback technology could provide more realistic touch sensations, improving the training of tactile skills (Hulsen, 2023).

Internet of Medical Things

Another significant advancement in healthcare and health education is the Internet of Medical Things (IoMT). This technology encompasses an interconnected array of medical devices and applications that gather and transmit health data via the Internet (Jagadeeswari et al., 2018). This system includes a range of devices, from simple wellness trackers to sophisticated medical devices like insulin pumps, pacemakers and electrocardiogram device (Figure 7). In health professions education, the relevance of IoMT lies in its ability to provide real-time data, offering students hands-on experiences with advanced technology and enhancing their understanding of patient care. Over the years, IoMT has evolved from its early applications in telemedicine to the integration of AI and ML algorithms in diagnostic tools, marking a significant shift in how health data is utilized and interpreted (Osama et al., 2023). IoMT devices can be integrated into an educational environment to enrich learning experiences by enabling realistic simulations of healthcare environments. Wearable health monitors, for example, allow students to engage in patient monitoring scenarios by providing real-time data on vital signs. This integration facilitates immersive learning experiences in 'smart hospital' environments where interconnected devices mimic real-life healthcare settings. The use of IoMT in simulation-based learning extends beyond the classroom, supporting remote monitoring and experiential learning that allows for immediate data analysis and personalized instruction (Khan et al., 2021). This capability is crucial in preparing students for the complexities of modern healthcare delivery.

To effectively incorporate IoMT tools into health professions education, a comprehensive approach that includes both theoretical and practical components is needed. Educators must develop guidelines that outline how IoMT devices can be integrated into existing curricula, focusing on competencies related to digital health literacy, data interpretation, and clinical application. Practical components might involve hands-on experiences with wearable monitors, simulated patient interactions, and technology-enhanced assessments, providing students with the necessary skills to operate advanced medical technology proficiently (Revano & Garcia, 2021; Tariq, 2024). Addressing the adoption barriers requires strategies such as forging collaborations with industry partners for technical support, ensuring compliance with data protection regulations, and seamlessly incorporating IoMT into curriculum frameworks. By overcoming technical challenges, privacy concerns, and curriculum integration issues, educators can maximize the benefits of IoMT in health professions education. Looking ahead, the long-term use of IoMT in health professions education holds exciting prospects for transforming educational experiences. Future advancements are expected to include enhanced sensors and biometric monitoring capabilities in wearable technology, enabling more precise and comprehensive health data collection. Additionally, the integration of AI and ML algorithms into IoMT platforms could facilitate personalized learning experiences, adaptive feedback mechanisms, and predictive analytics for early intervention and prevention strategies (Mushtaq et al., 2023). As these technologies evolve, IoMT is poised to revolutionize health professions education by equipping students to meet the challenges of a rapidly advancing healthcare landscape.

Robotic Telepresence

Robotic telepresence involves using robotic systems equipped with audiovisual communication capabilities to facilitate remote interaction in various settings, including healthcare. These systems allow individuals to participate in activities, consultations, and procedures from a distance. In health professions education, robotic telepresence is invaluable for enriching learning experiences by providing immersive, interactive opportunities for clinical training and skill development (Lei et al., 2022; Tota & Vaida, 2021). The evolution of robotic telepresence technology has been driven by advancements in robotics, telecommunications, and AI. Initially, telepresence robots were primarily used for remote communication and teleconferencing. However, with the integration of advanced features such as mobility, dexterity, and high-definition cameras, modern telepresence robots have found extensive applications in healthcare settings (Leoste et al., 2024). These robots are now used for various purposes, including remote clinical consultations, surgical assistance, medical education, and the supervision of healthcare professionals. They can be deployed in hospitals, clinics, and academic institutions to facilitate remote patient care, medical training, and interprofessional collaboration. Medical students can use telepresence robots to observe surgeries, participate in virtual consultations, and receive real-time feedback from supervising clinicians (Kasuk & Virkus, 2024).

One significant application of robotic telepresence in clinical training is in remote surgery (see Figure 8), where telepresence robots allow expert surgeons to mentor and instruct surgical procedures in real time (Barua, 2024). Through high-definition cameras and audio communication, surgeons can provide detailed instructions and feedback to learners regardless of geographical distance, thereby enhancing the quality of surgical training (Picozzi et al., 2024). This capability is crucial for developing critical skills among healthcare professionals, ensuring continuous and high-quality mentorship. Furthermore, telepresence robots facilitate virtual patient consultations, enabling medical students to engage in clinical encounters and interact with patients under the supervision of experienced clinicians. This immersive learning environment helps develop communication skills, clinical reasoning, and empathy while exposing students to diverse patient populations and medical conditions. Additionally, telepresence technology allows healthcare professionals to monitor and guide learners during clinical rotations remotely, ensuring consistent supervision and support. The benefits of using robotic telepresence in clinical training are multifaceted. Notably, it increases access to expert education by enabling renowned specialists to share their expertise with learners worldwide. This democratization of medical education enhances the quality and standardization of training, particularly in underserved or remote areas where expert mentors may be scarce. Moreover, telepresence technology offers expanded opportunities for remote clinical practice, allowing future healthcare professionals to practice delivering care in geographically distant or resource-limited settings without compromising quality. This extension of healthcare services improves patient outcomes and fosters a global network of knowledge exchange in healthcare education and practice.

Telemedicine Training

Following recent global health events like the COVID-19 pandemic, telemedicine has become a cornerstone of modern healthcare. The main idea behind this method is to provide medical care remotely through telecommunications technology. During the crisis, it allowed healthcare providers to maintain continuity of care while minimizing the risk of virus transmission (Jumreornvong et al., 2020). The integration of digital tools has transformed traditional healthcare approaches, which made medical services more accessible and efficient (Herrera et al., 2022). Training in telemedicine is crucial for health professionals to effectively utilize these tools. Key technologies include video conferencing for synchronous visual and auditory communication and mobile health applications that enable patients to track their health conditions and communicate with providers via smartphones. Training programs often incorporate simulations and role-playing exercises to develop proficiency in telehealth consultations, ensuring data security, and practicing online communication etiquette (Cruz-Panesso et al., 2023). Medical educators emphasize training in five major telemedicine domains: access to care, cost, cost-effectiveness, patient experience, and clinician experience, which encompass understanding financial implications, enhancing patient satisfaction, and integrating workflows.

In health professions education, telemedicine offers numerous benefits. It provides students with opportunities to engage in real-time consultations and gain experience with digital health tools, which are increasingly important in modern medical practice. Telemedicine allows for remote observation of clinical procedures and patient interactions, giving students access to diverse medical scenarios without geographic limitations. This technology also supports interprofessional education by enabling collaborative learning experiences among students from different healthcare fields, fostering teamwork and communication skills essential for clinical practice (see Figure 9). Globally, the adoption of telemedicine technologies varies, and training programs are tailored to meet the specific requirements and regulations of different regions (Martin-Khan et al., 2017). As the field continues to grow with advancements in artificial intelligence and machine learning, telemedicine training programs must adapt to integrate these emerging technologies, which can enhance telemedicine services' capabilities and reach (Ohannessian et al., 2020; Tavares et al., 2023). Comprehensive training programs are essential in health professions education to equip healthcare providers to meet current demands and embrace future advancements. This approach will ensure healthcare professionals are prepared to deliver high-quality care and improve patient outcomes in an evolving global health landscape.

Virtual Simulations

Although traditional simulation (e.g., mannequin-based and human-based simulation) has remained a mainstay in healthcare education curricula, a new type of simulation has steadily influenced the field (Foronda et al., 2020). This new virtual simulation type leverages emergent technologies to create realistic and interactive learning scenarios. These simulations enhance educational processes by providing repeatable training environments where students can practice and fine-tune their skills without posing risks to actual patients (Kononowicz et al., 2019). There are various types of virtual simulations (e.g., virtual patients and surgical simulations), each tailored to specific educational needs and learning outcomes. Virtual patients are computer-generated characters representing real-life patients with various medical conditions and symptoms. As learners interact with them, they can focus on specific skills such as conducting history-taking or diagnostic reasoning. Surgical simulations use these emergent technologies to recreate surgical procedures where learners can practice techniques (e.g., incision, suturing, and instrument handling) using VR or AR headsets with haptic feedback devices that simulate the tactile sensations of surgery. Integrating immersive 3D environments and simulation software models complex clinical and surgical scenarios that develop a wide range of competencies, including technical skills, clinical decision-making, and communication and interpersonal skills.

Integrating these virtual simulations into medical curricula involves strategically embedding them at various stages of training to focus on or reinforce specific learning objectives. Virtual simulations help learners develop essential clinical skills in a controlled and repeatable way, from technical proficiency to decision-making and communication. Technical skills, such as administering injections or using medical instruments, are honed through hands-on practice in a virtual setting (see Figure 10). Clinical decision-making skills are enhanced by presenting learners with complex scenarios requiring quick, informed decisions, thus improving their problem-solving and critical-thinking abilities. Communication and interpersonal skills are refined through interactions with virtual patients, which enables students to practice patient interviews and team collaboration. Despite the many benefits, virtual simulations face challenges, such as the high cost of initial infrastructure and software investments and the need for technological literacy among users. Globally, the adoption of these technologies varies, and training programs must be tailored to meet the specific requirements and regulations of different regions. As virtual simulation technologies continue to evolve, medical education programs must integrate these advancements to ensure that learners are well-prepared to meet the demands of modern medical practice.

Future Directions and Research Needs

The future of health professions education is directly tied to an array of promising technologies that will revolutionize learning experiences. These technologies not only enhance students’ engagement but also provide a safe environment for learners to practice complex health procedures without risking patient safety (Borycki & Kushniruk, 2022). TEL in health professions education is crucial not only because it utilizes technology to aid the teaching-learning process but also because it is essential for health professionals to be familiar with these technologies as they will frequently use them in clinical assessments and interventions. Furthermore, AI is anticipated to play a critical role in personalized learning pathways, as these algorithms can analyze vast amounts of data to tailor educational content according to individual learners' needs, learning styles, and proficiency levels. Although some concerns about academic integrity persist, mainly related to the use of generative AI tools, adaptive learning platforms powered by AI are likely to become commonplace, fostering efficient and compelling learning experiences (Garcia et al., 2024). Moreover, the integration of wearable devices and IoMT technologies holds promise for monitoring learners' progress in real-time (Osama et al., 2023).

Technology can also act as a catalyst for interprofessional education, allowing students and educators to collaborate both synchronously and asynchronously, regardless of their location and background experiences. In health education, learners can develop a comprehensive grasp of healthcare delivery through interdisciplinary interaction fostered by virtual collaboration platforms, online discussion forums, and teleconferencing tools. This reflects the realities of teamwork in clinical settings and fosters qualities such as shared decision-making, collaboration, and leadership that are necessary in healthcare environments. These shifts are changing students' roles from being passive recipients of knowledge to active learners who direct their own education and make significant contributions to society, something indispensable for future health professionals. While technological innovations present unprecedented opportunities, they also raise specific questions that need to be addressed (Garcia et al., 2024). Rigorous data protection laws and robust security measures are required due to privacy concerns over the gathering and storing of sensitive learner data in digital learning systems. Additionally, to ensure fair access to technologically advanced educational materials, it is imperative to address the digital divide. Socioeconomic differences may exacerbate educational inequality, emphasizing the importance of implementing inclusive policies to close the gap and advance equal access to educational opportunities for all. Transparency, accountability, and the reduction of algorithmic biases are also necessary for the ethical application of AI in educational contexts. Educators should ensure that new technologies complement pedagogical knowledge, not replace it.

A scoping review by Naeem et al., (2023) discussed the functional components of an effective TEL environment in the context of undergraduate medical education. These include cognitive enhancement, content curation, digital capability, technological usability, pedagogical practices, learner characteristics, learning facilitation, social representations, and institutional support. The review presents these themes through the TELEMEd model, illustrating how these components interact within and outside the virtual learning platform. It emphasizes the importance of learner motivation, the evolving role of learning facilitators, effective pedagogical practices, content curation, and institutional support in facilitating successful online learning experiences. Additionally, it highlights the significance of digital capability, cognitive enhancement, and social representations within the virtual learning platform for fostering conducive learning environments and interactions among learners and facilitators. While this is only one example, theoretical frameworks and models must be validated to facilitate the more integrated and systemic use of technology in education since there is no one-size-fits-all approach to education, as evidenced by the deep context-dependence of both educational processes and outcomes (Dubé, 2024). Thus, it is recommended that educators begin by clearly defining the problem they aim to solve or the learning outcomes they seek to enhance before implementing technologies. Moreover, research into learning technologies should be guided by a clear pedagogical framework, explicitly stating the educational goals and discussing how the chosen technology aligns with these objectives. This transparency will facilitate critical analysis in adopting these technologies in various educational contexts, thereby unlocking the potential for learning technology to revolutionize health professionals' education.

To sum up, the dynamic interaction of educational technology characteristics, stakeholder perceptions of technology integration decisions, theoretical frameworks, models relevant to the integration of technology into pedagogical practices, and metrics to evaluate post-implementation success must all be considered when developing viable pathways to successful educational technology implementation (Chugh et al., 2023). New technologies are on the horizon; thus, researching how to implement TEL properly must continue to guarantee that students in the health field will excel as compassionate, competent, and collaborative healthcare professionals.

Conclusion

TEL has fundamentally transformed health professions education by providing innovative, immersive, and interactive training environments that significantly improve learning outcomes and patient care. The integration of advanced technologies has proven essential for preparing future healthcare professionals to meet the demands of modern medical practice. This chapter reviewed the current trends and applications, such as AI, smart classrooms, extended realities, DGBL, mobile learning applications, metaverses, IoMT, robotic telepresence, telemedicine training, and virtual simulations. Each of these technologies offers unique benefits and opportunities for enhancing health education. AI and smart classrooms facilitate personalized learning and adaptive educational experiences. Extended realities, including VR and AR, provide immersive simulations for practicing complex procedures and improving clinical skills. DGBL and mobile learning applications engage students through interactive and accessible content, fostering continuous learning. Metaverses and IoMT create interconnected environments for collaborative learning and real-time health monitoring. Robotic telepresence and telemedicine training expand access to medical expertise and enable remote consultations, bridging geographical gaps. Virtual simulations offer realistic, risk-free training scenarios that help students develop technical proficiency, clinical decision-making abilities, and effective communication skills.

The adoption and integration of these technologies in health professions education are crucial for ensuring that future healthcare professionals are well-equipped to deliver high-quality care in a rapidly evolving medical landscape. By embracing TEL, educational institutions can create more dynamic, effective, and equitable learning environments that can lead to better patient outcomes and a more robust healthcare system. As TEL continues to advance, ongoing research and innovation will be essential to fully realize its potential and address the challenges associated with its implementation. The integration of TEL in health education is not just an evolution—it is a revolution that promises to redefine the standards of healthcare excellence.