Abstract

Ongoing advancements in technology and knowledge, alongside systemic challenges like social marginalisation (Fluit et al., 2024), call for adaptive educational strategies in healthcare. This chapter explores the potential of generative artificial intelligence (genAI) as a complementary tool within a Problem-Based Learning (PBL) educational approach, a cornerstone of Student-Centred Learning (SCL), to enhance healthcare education.

Grounded in constructivist, humanist, and behaviourist principles (Mukhalalati & Taylor, 2019), PBL facilitates critical thinking, collaboration, and authentic engagement with complex, real-world problems. Thoughtfully integrated, genAI tools can benefit both students and academic staff by generating tailored learning materials, fostering critical reflection through Socratic questioning (Ho et al., 2023; Overholser & Beale, 2023), and aiding personalised learning. Through coaching (Coumans & Wark, 2024; Hurlow, 2022), positive psychology (Passmore & Lai, 2019; Peláez Zuberbuhler et al., 2024; Seligman, 2011) and neuroeducational principles (Coumans & Wark, 2024), these can create inclusive, emotionally supportive learning environments that nurture growth mindsets, reduce stress, and promote neuroplasticity – elements crucial for effective, student-centred learning (Immordino-Yang et al., 2019; Voss et al., 2017).

To address persistent systemic challenges, including entrenched inequities and ongoing practitioner shortages (Mukhalalati & Taylor, 2019), broader strategies are also proposed. These include service learning (SL) and alignment with the United Nations (UN) Sustainable Development Goals (SDGs), all designed to cultivate socially responsible and adaptive healthcare practitioners. Ethical risks, such as passive learning or diminished critical thinking, are also discussed (Michel-Villarreal et al., 2023). These underscore the need for skilled facilitation, ensuring AI remains a reflective, supplementary aid, rather than a substitute for human judgment. By implementing genAI within current pedagogical frameworks, this chapter envisions a future-ready educational ecosystem. This system will equip healthcare professionals to navigate complex, technology-driven environments while contributing to the sustainability of society.

Keywords

Problem-Based Learning (PBL), generative Artificial Intelligence (genAI), healthcare education, coaching psychology, neuroeducation, health equity, Sustainable Development Goals (SDGs), curriculum innovation

Introduction: Transforming education

Healthcare education in the 21st century continues a shift from static teacher-centred methods towards dynamic student-centred approaches that emphasise active learning and personalisation (Spencer & Jordan, 1999). This reflects an evolving understanding of adult learners’ active role in acquiring, retaining, and applying knowledge. Student-Centred Learning (SCL), grounded in educational psychology theories of constructivism, humanism, and behaviourism (Mukhalalati & Taylor, 2019), places students at the heart of education. It emphasises critical thinking, collaboration, and personalised learning experiences tailored to diverse needs, including differences in prior knowledge, personal experiences, and learning preferences (Dewey, 1938; Rogers, 1969; Schön, 1992; Weimer, 2013).

Historically, healthcare has been seen as both an art and a science. Embracing generative artificial intelligence (genAI) within the tri-modal creativity framework – visceral, ideational, and observational – mirrors core aspects of healthcare education: clinical skills, diagnostic reasoning, and reflective practice. This supports future professionals’ capacity to adapt and innovate (Creely et al., 2020). Achieving this requires a shift in educational priorities toward data analysis, innovative problem-solving, effective teamwork, and digital literacy; all competencies essential for preparing graduates for a complex world and global challenges (Xu et al., 2024).

Problem-Based Learning (PBL) is a student-centred, constructivist approach where learners engage with real-world problems, such as clinical cases, to develop problem-solving, reasoning, and self-directed learning through collaborative inquiry. It is a cornerstone of SCL in healthcare (Coumans & Wark, 2024; Hartling et al., 2010). Bridging theory to practical application, PBL fosters critical thinking, teamwork, and adaptability in future healthcare practitioners who will need to navigate evolving professional environments (Barrows & Tamblyn, 1980; Mukhalalati & Taylor, 2019; Wood, 2003). A deliberate, structured integration of positive psychology principles, such as those outlined within the PERMA (positive emotion, engagement, relationships, meaning, and accomplishment) model, further enriches the PBL approach by fostering individual resilience, goal-setting, and emotional well-being (Passmore & Lai, 2019; Peláez Zuberbuhler et al., 2024; Seligman, 2011).

The emergence of new technologies, particularly genAI, is reshaping healthcare education. GenAI can ameliorate PBL facilitation through enabling real-time production of realistic patient scenarios, identifying learning issues, developing practice questions, and enhancing productivity (Kasula, 2024; Kitsios et al., 2023; Wu, Zerner, et al., 2024; Wu, Zheng, et al., 2024). Tutors’ proactive use of genAI to develop patient scenarios, address knowledge gaps, suggest responses to medical enquiries, and generate exam questions, assists in scaffolding student inquiry and problem-solving (Divito et al., 2024; Sauder et al., 2024; Wu, Zerner, et al., 2024). This requires mastering ‘promptgramming’, a structured approach to crafting prompts that optimise AI outputs to foster critical thinking (Gattupalli, 2024). However, widespread integration of genAI requires consideration of ethical challenges, including potential over-reliance leading to passive learning, diminished critical thinking, and secure data handling practices (Kasneci et al., 2023; Michel-Villarreal et al., 2023).

As healthcare education evolves to meet the demands of a rapidly changing environment, it must equip learners with technical and cognitive skills to address systemic challenges, including healthcare disparities, practitioner shortages, and societal marginalisation (Fluit et al., 2024). By considering individual growth with societal impact and leveraging insights from neuroeducation and innovative technologies, educators can cultivate adaptive, future-ready professionals for complex, technology-driven settings (Hurlow, 2022; Pavlović, 2021; Stănciulescu, 2024). AI is increasingly embedded into healthcare services, supporting diagnostic decision-making and efficiency while reducing error and cost (Alowais et al., 2023). However, healthcare professionals require foundational AI literacy and critical reflection skills to use AI tools effectively. This shift calls for new educational strategies integrating technical competencies, ethical awareness, and pedagogical adaptability from undergraduate to ongoing professional development.

This chapter examines the transformative shift in healthcare education through student-centred methodologies, emphasising how tertiary-level academics can integrate genAI within PBL facilitation. It proposes complementary approaches, grounded in evidence-based frameworks, to prepare healthcare professionals to meet individual and systemic challenges, supporting a more inclusive and impactful future.

Foundations of Student-Centred Learning (SCL)

SCL focuses on students’ development by recognising unique strengths and growth areas (Martin-Alguacil et al., 2024). In healthcare education, this requires scaffolding to transition from teacher-led instruction to autonomous learning by building confidence, agency, and ownership (Bhardwaj et al., 2025). Lectures and similar relevant expert inputs provide foundational knowledge that PBL facilitators use to implicitly guide inquiry, reflection, and collaboration in line with SCL. However, many facilitators trained in teacher-centred systems face challenges in making this transition. Much of the literature still emphasises teacher-controlled strategies over deeper shifts in epistemology or classroom power dynamics (Bhardwaj et al., 2025; Bremner, 2021). This is evident in healthcare education, where high-stakes curricula limit the sharing of power. SCL, supported by constructivist, humanist, and behaviourist theories, emphasises active engagement, collaboration, and personalisation. These are all applicable in PBL to develop critical thinking, teamwork, and adaptability. Positive psychology and neuroeducation concepts further enrich PBL by fostering emotional well-being and cognitive development (Coumans & Wark, 2024). The following section outlines these pedagogical approaches’ historical development and theoretical foundations.

Key principles of SCL

Three key principles underpinning SCL in tertiary education include:

Constructivism

Constructivism postulates that learners construct knowledge by integrating prior experiences with new information to prioritise skills essential for lifelong learning, such as deep learning, critical thinking, and navigating complex problems (Bruner, 1961; Dewey, 1938).

Humanism

Humanism emphasises autonomy, intrinsic motivation, and personal growth. These concepts empower students to take ownership of their learning, develop emotional intelligence and resilience, and thrive both personally and academically (Mukhalalati & Taylor, 2019; Rogers, 1969).

Behaviourism

Behaviourism advocates for frequent feedback, reinforcement, and clear learning objectives to support skill acquisition and autonomy through iterative feedback loops (Carlile & Jordan, 2005).

PBL: A core strategy

PBL is a core strategy of many SCL approaches, particularly within healthcare education. It engages students in solving real-world problems, blending theoretical knowledge with practice. Key aspects of effective PBL include:

• Facilitation by an academic who guides rather than instructs. This is a shift from knowledge transmitter to learning facilitator and supports the development of critical thinking, self-directed learning, teamwork, and adaptability skills to help navigate complex and dynamic workplaces (Barrows & Tamblyn, 1980; Wood, 2003).
• Promoting mastery through ongoing individualised feedback. This aids students to progressively refine their thinking and improve their problem-solving strategies, and it prepares them for professional challenges (Almusaed et al., 2023; Ellikkal & Rajamohan, 2024; Jayasinghe, 2024).
• Incorporating positive psychology and neuroscience principles which emphasise emotional safety, resilience, and engagement. Tools like the PERMA model – Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment – help prepare students for complex, high-pressure environments while fostering a well-rounded approach to learning (Immordino-Yang et al., 2019; Seligman, 2011).

Technology already supports PBL through learning management systems, virtual patients, and video-based cases, enabling interactive, collaborative clinical reasoning and flexible access to content (Jin & Bridges, 2014). Recent advances in genAI build on this foundation, enabling the creation of adaptive scenarios and Socratic questions to personalise and enrich the problem-solving process (Coumans & Wark, 2024; Kasneci et al., 2023). GenAI assists students’ progress from rote recall to analytical and synthetic reasoning and supports evidence-based practice and clinical excellence (Chang, 2023; Chen et al., 2024; Hswen & Nguyen, 2024).

To facilitate personal growth and resilience in PBL, careful and ethical use of genAI can suggest tailored feedback that promotes inclusion, psychological safety, and reflective thinking (Seligman, 2011; Xu, Weng, et al., 2024). Figure 12.1 illustrates how it ensures progress toward the relational integration of knowledge that fosters active enquiry, creativity, and critical thinking while aligning with constructivist and humanist theories. This general prompt strategy was designed to enhance comprehension through Bloom’s and the structure of observed learning outcomes (SOLO) taxonomy (Brabrand & Dahl, 2009; Krathwohl, 2010) through generating topics supporting student engagement and creative problem-solving in foundational medical education. This ensures progress toward relational integration of knowledge and scaffolds meaningful exploration of clinical concepts. An example of output from this prompt is included in Supplemental Data 1.

Figure 12.1. Enhancing student comprehension through genAI

GenAI in healthcare education

Undergraduate healthcare students often struggle with complex concepts, such as integrating knowledge across body systems in a system-based curriculum. Foundational knowledge gaps intensify these difficulties (Badenhorst et al., 2021; Weurlander et al., 2014), and are exacerbated by a reliance on less effective learning techniques (Franz et al., 2022; Lerchenfeldt & Nyland, 2016), and disruptions caused by the COVID-19 pandemic’s shift to online learning (Dost et al., 2020). These barriers can hinder academic performance, reduce learning efficacy, impact student well-being, and ultimately affect future patient-centred care (Duffy et al., 2020). However, genAI is revolutionising education by introducing innovative tools to enhance teaching and learning (Michel-Villarreal et al., 2023). Within the SCL framework, genAI can complement strategies like clinical reasoning by offering dynamic solutions that support personalised learning, critical thinking, and collaborative problem-solving.

GenAI as a transformative tool

Applications in clinical scenarios and personalised learning

GenAI can enhance PBL by generating realistic, context-specific clinical cases incorporating diverse patient demographics, cultural and socioeconomic factors, and systemic considerations. These tailored cases challenge students to explore differential diagnoses, appropriate investigations, and provisional treatment plans that consider both clinical and broader social determinants of health (Barrows & Tamblyn, 1980; Mukhalalati & Taylor, 2019; Sauder et al., 2024).

GenAI supports personalised learning by adapting content to students’ prior knowledge and cognitive style. It enables interactive dialogue that supports learners to explore clinical scenarios, receive real-time feedback, and refine their reasoning (Gordon et al., 2024). This assists self-directed and collaborative learning through customised materials including investigative pathways, structured objectives, and peer interaction strategies. By considering both correct and incorrect responses, genAI fosters curiosity, creativity, and analytical thinking while promoting effective teamwork (Kasneci et al., 2023; Xu et al., 2024). Figure 12.2 provides a more detailed AI-generated prompt than Figure 12.1. It suggests clinically important topics, learning objectives, and peer interaction strategies aligned with PBL frameworks and the PERMA model. An example output is included in Supplemental Data 2.

Figure 12.2. Structuring clinical learning objectives with genAI

Socratic questioning

Socratic questioning challenges students to deepen their understanding by asking questions that clarify ideas, test assumptions, request evidence, and examine reasoning behind a choice (Overholser & Beale, 2023). It is critical in developing clinical reasoning and helps students to reflect and engage in analytical discussions (Ho et al., 2023). GenAI can support facilitators by generating tailored questions that explore complex ideas and connections.

These may range from conceptual queries (e.g. ‘What are the underlying physiological mechanisms of this condition?’) to integrative ones (e.g. ‘How might cultural factors influence healthcare outcomes for this patient?’). Facilitators refine and scaffold these questions to match students’ developmental level. SCL environments support students to generate and explore such inquiries independently, and genAI can assist by offering general considerations to prompt deeper reflection (Coumans & Wark, 2024; Xu et al., 2024). Figure 12.3 illustrates a general prompt for generating Socratic questions. It illustrates how genAI can assist facilitators in crafting Socratic questions tailored to clinical and cultural contexts. Supplemental Data 3 includes an example of an output.

Figure 12.3. Generating Socratic questions for PBL

Ethical and practical considerations

While genAI offers immense potential, its integration into education raises ethical and practical challenges that require careful consideration:

Risks of over-reliance and misinformation

Over-reliance on genAI can reduce students’ engagement and critical thinking by encouraging passive learning habits. Additionally, inaccuracies or biases in AI-generated content pose risks of misinformation, compromising educational quality and trust by the learner (Kasneci et al., 2023; Michel-Villarreal et al., 2023).

Guidelines for secure data handling and AI-generated content verification

Ethical use of genAI requires robust data protection protocols and validation of AI outputs. Facilitators must ensure the content accuracy and curricular alignment through human oversight, peer review, and iterative validation (Wu, Zheng, et al., 2024).

Facilitators’ roles in balancing genAI use with reflective practices

Facilitators play a pivotal role in integrating genAI as a supportive tool rather than a substitute for active learning. By curating and reviewing AI-generated content, they can encourage more profound understanding and foster reflective practices that reinforce critical thinking (Anggraeni et al., 2023; Coumans & Wark, 2024). However, they must actively support ongoing student engagement in the PBL process to minimise the potential for students to revert to passive learning.

Coaching and neuroeducation for holistic SCL

Integrating coaching and neuroeducation into SCL provides a transformative approach to holistic learning as healthcare education evolves to meet the demands of professionals. They prioritise emotional well-being, resilience, and personal growth, aligning with SCL frameworks such as PBL, and are grounded in the principles of positive psychology and neuroscience. The following section summarises some key concepts within these fields.

Positive psychology

Positive psychology can inform educational practices that promote well-being and resilience. The PERMA model provides a framework for PBL facilitators to strengthen students’ emotional and cognitive resilience. It aligns with PBL goals by creating a psychologically safe environment conducive to curiosity, critical thinking, collaboration, and innovation (Peláez Zuberbuhler et al., 2024; Seligman, 2011).

Coaching frameworks

In tertiary education, coaching develops student self-awareness through structured goal setting and adaptive problem-solving skills. Coaching models like GROW (Goal, Reality, Options, Will) and ISMART (Important, Specific, Measurable, Achievable, Realistic, Time-bound) help students define their objectives, assess challenges, and implement actionable strategies. These models promote reflective practices, emotional intelligence, and accountability. In PBL, coaching can support students in navigating patient-specific contexts while addressing systemic challenges like healthcare disparities and practitioner shortages (Coumans & Wark, 2024; Hurlow, 2022).

Expectations

Establishing clear expectations is essential in fostering an empowering learning environment, especially in tertiary education, where the ‘hidden curriculum’ – the informal, often unintended lessons, values, and behaviours – shapes how students perceive their roles and responsibilities (Koutsouris et al., 2021). In healthcare education it encompasses social dynamics, cultural norms, and unspoken expectations that influence students’ understanding of professionalism and identity. When educators fail to set clear expectations, provide unequal or inequitable access to resources, or ignore unproductive behaviours, students may experience confusion, emotional dissonance, and a diminished sense of purpose and well-being (Brown et al., 2020).

GenAI can influence the hidden curriculum through its language patterns and embedded assumptions, which may unintentionally reflect dominant norms or systemic biases. This reinforces standardised narratives and may discourage critical reflection (Kasneci et al., 2023; Xu et al., 2024). These assumptions risk reinforcing what constitutes ‘normal’ or ‘ideal’ knowledge and behaviour. However, when critically facilitated, genAI can also expose these assumptions, prompting reflective dialogue and encouraging students to question both human and algorithmic biases. Recognising and addressing the hidden curriculum, whether from educators, institutions, or digital tools, is essential for creating inclusive, ethically aware learning environments that support students’ professional identity formation and critical engagement (Gupta et al., 2024).

Insights from neuroscience for SCL

Chronic stress undermines both effective learning and cognitive performance (Schneider & Preckel, 2017). Neuroscience highlights the value of emotional safety, which can enhance memory, attention, and problem-solving through non-judgmental feedback and positive reinforcement (Immordino-Yang et al., 2019; Mendl, 1999). Neuroplasticity, the brain’s ability to reorganise and form new connections, facilitates lifelong learning. Emotionally supportive and engaging environments enhance cognitive flexibility and adaptability, key skills for future healthcare practitioners who will navigate evolving clinical landscapes with innovation (Bhargava & Ramadas, 2022; Voss et al., 2017). In the SCL setting, genAI can assist PBL facilitators in addressing emotional and behavioural issues by tailoring feedback to individual factors, such as cultural background, personality, and age. Figure 12.4 provides a prompt to help students evaluate their behaviours. It demonstrates how facilitators can use frameworks to guide constructive changes. An example of the output is provided in Supplemental Data 4.

Figure 12.4. Supporting positive behavioural changes

Addressing systemic challenges in education

Healthcare education is uniquely positioned to address systemic challenges, including societal inequities, workforce shortages, and sustainability issues. Integrating genAI, Service Learning (SL), and the United Nations (UN) Sustainable Development Goals (SDGs), into SCL/PBL frameworks can cultivate socially responsible, adaptable learners equipped for multifaceted issues (Rodríguez-Zurita et al., 2024).

Tackling societal inequities through education

Community engagement

SL connects theoretical learning with mentored, community-based practice through partnerships with non-government organisations (NGOs) or public health services. SL fosters reciprocal student-community relationships and experiential learning grounded in real-world challenges. Supporting SDG 3 (good health and well-being) and SDG 4 (quality education), SL promotes empathy, communication skills, cultural competence, and systemic awareness (Rodríguez-Zurita et al., 2024). Within an SCL/PBL framework, SL encourages co-creation of solutions, reinforcing reflective practice and social accountability.

Equity

GenAI can enhance equity-focused education by creating culturally-contextualised community-based scenarios and evidence-based interventions (Sauder et al., 2024). When embedded within SCL/PBL, this supports inclusive, responsive learning and exposes systemic biases and knowledge gaps, supporting the establishment of innovative approaches towards contributing to SDGs 3, 4, 10 (reduced inequalities), and 11 (sustainable cities and communities) (Kasula, 2024).

Marginalisation

Education prepares learners to address healthcare disparities, including practitioner shortages in regional areas. Combining coaching models with SL empowers students to contribute to structural solutions, like rural initiatives and community projects. These experiences promote adaptability, ethical awareness, and social responsibility, equipping students towards addressing SDG 3, SDG 4, and SDG 17 (partnerships for the goals) (Fluit et al., 2024; Stănciulescu, 2024).

Integrating sustainable development goals

Educating for sustainable impact

Aligning healthcare education with SDGs supports interdisciplinary learning and societal transformation (Department of Economic and Social Affairs, 2024). Embedding SDG-focused projects into the curricula supports students in considering global challenges like climate change, health inequities, and social disparities. These initiatives cultivate critical skills, collaboration, and innovation, empowering students to contribute meaningfully to societal progress (Rodríguez-Zurita et al., 2024).

The role of genAI

GenAI-generated scenario-based exercises can advance the achievement of SDGs (e.g. SDG-3, SDG-8, SDG-10, SDG-11) by encouraging students to design interventions that address public health inequities. These tasks promote evaluation of local issues, community-driven solutions, and reflection on their societal impact (Coumans & Wark, 2024).

Interdisciplinary collaboration

Meaningful interdisciplinary collaboration is key to maximising the impact of SDG-aligned education and underpins adaptability, empathy, and social responsibility to address complex societal issues. Models like Learning-to-Develop through Research (LDR) can be adapted to help students integrate research into practice, developing innovative, sustainable solutions that align personal growth with cultural, structural, and ethical aspects of healthcare delivery (Stănciulescu, 2024).

Figure 12.5 presents a more complex genAI prompt designed to generate scenarios aligned with SDGs. While the LDR model is used, other frameworks can be substituted into the prompt. An example output is provided in Supplemental Data 5.

Figure 12.5. Designing scenario-based exercises to address SDGs

Preparing students for future challenges

As society transitions to the era of ‘Society 5.0’, emphasising productivity and innovation, tertiary education must develop students’ digital competencies, critical thinking, creativity, and human-centric skills to meet these demands (Shahidi Hamedani et al., 2024). Constructivist and humanistic approaches underpin the SCL framework, promoting engagement, autonomy, and growth (Mukhalalati & Taylor, 2019). Technologies such as genAI, big data, and virtual reality present new opportunities for developing these essential skills. Unlike healthcare informatics or traditional educational technologies, genAI is not purpose-built for curriculum delivery or healthcare instruction. Instead, it is a general-purpose language model whose educational value emerges through intentional and critical adaptation. Educators must guide the use of genAI to support reflection, inquiry, and dialogue aligned with student-centred values. As demonstrated through exemplar prompts, genAI can generate clinical scenarios, Socratic questions, and tailored coursework to foster critical and problem-solving skills. It also facilitates boundary-crossing learning by enabling interdisciplinary collaboration, reflective practices, and adaptability (Oonk et al., 2022), creating dynamic, inclusive, and personalised learning environments suited to current and future professional landscapes.

Frameworks for reflective and adaptive learning

Reflective and adaptive learning frameworks are crucial for developing the skills required in the dynamic and complex environments of Society 5.0. Integrating models like the Master Adaptive Learner (MAL) framework, and leveraging genAI to create scenarios that enhance students’ critical thinking, educators can cultivate cognitive and interpersonal skills essential for success (Cutrer et al., 2017). MAL employs a structured ‘plan-do-study-act’ cycle to help learners identify knowledge gaps, engage in targeted activities, reflect on the outcomes, and adapt ongoing strategies for continuous improvement. This aligns with coaching frameworks, like the GROW model, which support structured goal-setting and actionable learning pathways (Cutrer et al., 2017; Leach, 2020). Additionally, ISMART principles can ensure that learning objectives are precise, attainable, and aligned with individual and societal needs.

Figure 12.6 illustrates a prompt that demonstrates how facilitators can integrate the MAL and GROW models with ISMART principles within a reflective and adaptive framework. This structured approach guides students through self-reflection and goal-setting exercises to address their learning needs in the context of broader societal challenges. Supplemental Data 6 shows an example of an output.

Figure 12.6. Structuring reflective conversations and goal setting

GenAI in adaptive learning

GenAI emerges as a complementary tool for adaptive learning, facilitating scenario design that promotes argumentation, collaborative problem-solving, and reflective thinking (Guettala et al., 2024). GenAI can help create clinical scenarios that challenge students to explore differential diagnoses, engage in interdisciplinary collaboration, and address ambiguous real-world problems. In collaborative healthcare, argumentation and group decision making are crucial for identifying cognitive conflicts, mitigating biases, and improving problem solving. Healthcare professionals often draw on personal experiences in teaching, which can enrich learning and introduce unconscious biases. Encouraging diverse perspectives helps uncover preconceptions and improves patient-centred care (Lu & Lajoie, 2008). Personal values influence decision making, with practitioners prioritising spirituality supporting more holistic, patient-centred approaches, while those emphasising critical thinking may promote evidence-based analysis (Moyo et al., 2019). These findings highlight the value of clinical case scenarios with inherent ambiguity in fostering debate around differential diagnoses, appropriate investigations, and context-based treatment. One specific genAI, ChatGPT, has demonstrated utility in supporting clinical workflows, achieving 71.7% accuracy in iterative clinical tasks and 78.8% accuracy in symptom-checking across 194 adult diseases (Chen et al., 2024; Rao et al., 2023). This suggests its potential to generate diagnostic challenges that encourage critical evaluation and prioritisation in clinical assessments. Figure 12.7 provides a general prompt to generate culturally and structurally relevant clinical scenarios to enhance collaborative problem-solving and critical thinking. An example output is provided in Supplemental Data 7.

Figure 12.7. Generating ambiguous clinical scenarios for argumentation

Inclusivity in education

Inclusivity is central to creating equitable and supportive educational environments, particularly in high-pressure fields such as healthcare. Increasingly, students face pressures associated with stress, perfectionism, and systemic barriers, contributing to mental health issues (Thomas & Bigatti, 2020). Addressing these concerns requires evidence-based strategies to build individual resilience, well-being, and equity.

Student challenges

Students’ mental health is a global concern, with an estimated prevalence of depressive symptoms of 27.0%, with the highest prevalence of 40.9% in Africa (Tam et al., 2019). In healthcare students, reported depression rates vary considerably from 1.4% to 73.5%, with anxiety rates ranging from 7.7% to 65.5% (Mirza et al., 2021). Contributing factors include academic pressure, financial difficulties, and a family history of mental health issues. These stressors can evolve as students progress, with first-year students struggling with workload volume and lack of feedback, while advanced students face concerns about competence, pedagogical gaps, and unsupportive environments (Mirza et al., 2021).

Socioeconomic disparities worsen these challenges, with students from low-income or rural backgrounds reporting higher depression rates than urban or higher-income peers (Mirza et al., 2021). The culture of perfectionism is ubiquitous in medical training, often intensifying these pressures and disproportionately affecting women who face heightened societal expectations and systemic biases (Thomas & Bigatti, 2020).

Strategies to foster resilience, well-being, and equity

Addressing mental health and promoting equity in education requires inclusive environments. A comprehensive approach incorporates innovative technologies, resilience-building techniques, active engagement, and emotionally and culturally safe spaces. These strategies foster holistic well-being and empower individuals and communities to thrive (Osher & Pittman, 2024).

Emotional safety

Neuroeducation highlights the importance of emotionally and culturally safe environments for fostering a growth mindset – believing abilities can develop through effort and practice. Positive and trusting relationships enhance cognitive functions such as memory, attention, and problem-solving, allowing students to engage deeply with their learning. These conditions nurture resilience and holistic well-being, equipping students to navigate academic and personal challenges effectively (Coumans & Wark, 2024; Immordino-Yang et al., 2019).

Leveraging technology for equity

Technological innovations, like genAI, can support inclusivity and address systemic issues. By generating tailored feedback and challenging biases, these tools help students overcome perfectionist tendencies, build resilience, and enhance mental well-being. Aligning technologies with the UN’s SDGs enables institutions to tackle challenges of gender disparities, resource inequities, and other systemic challenges, and supports equity in educational opportunities (Carter et al., 2024; Murphy et al., 2021).

Encouraging active participation

Equity requires active engagement from all stakeholders. Promoting men’s participation in gender equity efforts and addressing disparities in race, socioeconomic status, and gender is vital. Institutions must cultivate environments where all students feel valued and empowered to succeed (Thomas & Bigatti, 2020; Van Laar et al., 2024).

Strength-based coaching and feedback

Strength-based coaching, rooted in positive psychology, focuses on individuals’ strengths to enhance resilience and self-confidence. It emphasises collaborative and reflective feedback that strengthens educator-learner relationships. Positive reinforcement and introspective practices equip students with adaptive skills, fostering motivation and resilience in overcoming challenges (Peláez Zuberbuhler et al., 2024; Telio et al., 2015).

Integrating strategies for inclusive education

Holistic approaches that foster resilience, well-being, and equity integrate emotionally safe spaces, technological innovations, active engagement, and strength-based coaching. These strategies address the complex interplay of mental health challenges and systemic inequities by prioritising agency, groundedness, and inclusivity, and prepare students to thrive academically and to contribute meaningfully to society (Osher & Pittman, 2024).

Conclusion: A vision for future-ready education

Transforming education into a future-ready ecosystem requires innovation, inclusivity, and adaptability. As the 21st century presents increasingly complex global challenges, integrating genAI into SCL and PBL becomes pivotal. GenAI can support the integration of theoretical knowledge with practical applications, encouraging critical thinking, self-directed learning, and collaborative knowledge creation. (Thampinathan, 2022). Coaching frameworks such as the MAL and GROW model, combined with the ISMART framework, equip students with the reflective and adaptive skills needed to thrive in dynamic environments. If coupled with ethical considerations in using genAI, these approaches create a balanced framework for nurturing academic excellence, personal growth, and professional adaptability (Cutrer et al., 2018; Kasneci et al., 2023; Leach, 2020).

Education must also rise to the task of addressing pressing global challenges, including healthcare disparities, climate change, and social inequities. By aligning curricula with the SDGs and SL, institutions empower students to become meaningful, socially responsible professionals (Department of Economic and Social Affairs, 2024; Rodríguez-Zurita et al., 2024).

Transitioning to Society 5.0 education means prioritising digital literacy, creative problem-solving, and human-centric skills to prepare students to navigate the complexities of modern life, fostering a generation of adaptive, innovative, and socially conscious professionals ready to tackle the challenges of a rapidly evolving world (Shahidi Hamedani et al., 2024). It is hoped that this chapter has provided practical examples of how genAI can support the development of our future healthcare workforce.

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