C 922 Task 1 Curriculum Technology Proposal Template

Student Name

University Name

C922 Emerging Trends and Challenges in 21st Century Nursing Education

Instructor’s Name

June, 2026

• C922 Task 1 Integration of AI-Enhanced Virtual Simulation in Community Health Nursing Education

Executive Summary

The proposed solution is to integrate AI to enhance virtual simulation for the course, “BSN Nurse in Promoting Community Health.” This will address the interactivity, adaptive feedback, and learning experience concerns in the course. Within an environment of community health nursing, the shortcomings of using the current technologies (such as the existing LMS materials and current simulation laboratories) to gain experiential learning and to think at a higher level become apparent.

An inclusive curricular technology needs assessment conducted with the input of the faculty and students and information technology personnel pointed to AI-advanced virtual simulation as the best option. It is a scenario-based learning technology that is immersive, provides adaptive AI feedback, performance insights and personalized learning journeys. AI simulation also has more opportunities for scaling, tangible results and it also fits into the goals and objectives of competency-based learning, when compared to other emerging resources, like Augmented Reality modules.

The literature review (using five recent (within the last five years) peer-reviewed articles regarding AI simulation) shows that research regarding AI simulation is persuasive and supports the use of AI simulation to enhance student engagement, clinical reasoning, decision-making, and preparedness to practice. The findings most relevant for nursing indicate that digital simulation can lead to improved learning outcomes and a greater level of satisfaction with the completion of digital requirements.

The Change Theory of Lewin is followed for the implementation step: awareness building, step-by-step implementation, faculty training, and course integration. This proposal will enhance the gap between theory and practice, foster critical perspective, and prepare future nursing professionals for practice in a highly developed technological community health arena. The proposal will enhance the nursing educational process and create better health outcomes.

AI Powered Virtual Simulation is used to support the use of Virtual Simulations in Community Health Nursing Education. The use of AI Virtual Simulation in Community Health Nursing Education is being proposed.

Integration of AI-Enhanced Virtual Simulation in Community Health Nursing Education

Literature Review

Research Findings and Support of the Proposal

The majority of the literature supports the use of AI-based adaptive learning software and simulation-based learning tools for nursing education. Specifically, most literature advocates using these learning tools in a course titled, Role of the BSN Nurse in Promoting Community Health. The commonalities in the five peer-reviewed articles (Table 1) suggest AI-based technologies can assist in the preparation of nurses by providing a platform for learning which is tailored to the individual, incorporates simulation for the training of skills, as well as augmented support for clinical decision-making and increased engagement for learners.

Khlaif et al. (2025) were the first to provide evidence that generative AI, when incorporated into a curriculum, significantly improves the perceptions of usefulness and trust while improving the academic performance of nursing students. This was further supported by Labrague et al. (2025), who reported evidence on the use of AI in the classroom and stated that AI-based simulations and teaching tools of AI-based generation create an immersive learning environment and promote critical thinking and preparedness for clinical practice. Ma et al. (2025) further complemented this by conducting a higher-order systematic review and demonstrated that the use of AI, particularly the use of virtual patients, chatbots, and adaptive learning, has positive effects on clinical skills, mental engagement, and learning efficiency.

From a broader view and within the scope of health education, Mir et al. (2023) examined the ability of AI to greatly change curriculum creation, instruction, assessment, and distance teaching. Within the field of nursing, Wei et al. (2025) cited these findings specifically to address how changes in the AI landscape can positively affect workflow and clinical decision-making through technologies such as decision support, predictive analytics, and simulation training.

Based on the literature reviewed, the following potential benefits of using AI-assisted virtual simulation in the field of nursing studies can be clearly seen in the literature: Personalization of learning – the ability to adapt the content of learning to the needs of each person using these adaptive algorithms, so that each person can learn at the optimum rate for them. Skills’ enhancement based on the simulation. For critical thinking and decision-making skills, simulations which are complex in clinical scenarios offer a suitable and safe environment for practice without compromising patient outcomes (Stenseth et al., 2025).

The work is personalized and immediately provided using AI-based assessment centres, which enhances the quality of accurate assessment – the learner can take corrective measures if the work is not satisfactory. In addition, operations become more efficient, and administrative aspects of grading, monitoring, and checking the results can be automated, leaving more time for faculty to try their hand at teaching and supervision.

The received benefits align with the contemporary educational objectives of constructing a stimulating and engaging learning environment, while simultaneously equipping college students with the essential knowledge and skills to enter community healthcare.

There is broad support in the literature for using AI and virtual simulations in nursing education; however, some gaps need to be addressed. Khlaif et al. (2025) argued that generative AI positively affects performance and trust; however, to what extent this is true for various nursing programs and curricula is uncertain, and more studies need to be performed. In the same vein, AI-pedagogies described by Labrague et al. (2025) positively affect engagement and readiness, but the author did not cite studies describing the long-term impacts on preparedness.

Ma et al. (2025) presented a systematic review that provided excellent evidence and described a lack of longitudinal studies on the transfer of AI simulation skills to actual practice. Mir et al. (2023) looked at the gaps in the literature on the adoption of AI and suggested that the adoption of AI in nursing education should have more rigorous ethical consideration such as privacy and bias, and the consideration of faculty attitudes toward adoption. Lastly, Wei et al. (2025) described the gaps on AI platforms, including interoperability, data transparency, and access equity. These gaps, particularly professional education and ethics, should be addressed if AI virtual simulations in nursing education are to be adopted sustainably.

Need for Further Research or Development

While the implementation of Al for the advancement of Virtual Simulation in nursing education does provide some original avenues for its application and integration in an ethical and sustainable manner, there is still considerable room for improvement (Alharbi et al., 2024). There is still a strong demand for research to study the effects that this simulation has on the retention of information, clinical competence, and the ability to transfer the learning that has taken place in the simulation to the real world, particularly in relation to the community. This is because the majority of research to date has concentrated on a short-term evaluation of results.

Additionally, there exists a considerable gap in the preparedness of faculty, which calls for research to address the sophisticated, scalable models of professional growth that empower educators to design, implement, and evaluate AI-integrated simulation activities (Mahmoud, 2025). Research addressing the ethics of mitigating algorithmic bias, protecting student data, and ensuring ethical AI-in-Nursing education is critically needed.

Equity is another concern that must be addressed, as students must be able to utilize and appreciate these technologies regardless of their geographical location. Furthermore, research is needed on the ease of incorporating AI systems into existing curricula in a way that does not overwhelm faculty and students (Mahmoud, 2025). More focused research in these areas will allow the establishment of meaningful, effective frameworks for the use of AI-integrated Virtual Simulation in nursing education for the benefit of the profession.

Needs Assessment

Need-Gap Analysis

A gap analysis was performed for The Role of the BSN Nurse in Promoting Community Health to assess how current curriculum technology is used (Table 2). Data were collected through faculty interviews, student surveys, course evaluations, and through direct observation. The comparison was drawn between the technology currently employed (Traditional LMS, minimal content, and a limited number of simulations; Baig et al., 2025) and an instructional model with AI-based adaptive learning and virtual simulations. The gap analysis revealed that the learning and teaching within the course are static.

Attention is lacking with regard to interactive learning, personalization, and the use of experiential case studies. Without having the opportunity to practice within a safe learning environment, the students are unable to transfer theoretical concepts into practice. The gap shows the need for an AI-based virtual simulation, which will be flexible, scenario-based, and support augmented clinical reasoning and community health. Action steps will be taken to fill this gap, such as selecting and preparing an AI simulation platform and finding an appropriate institutional fund, which will be on a smaller scale before implementation on a large scale to be tested.

Course objectives will be used as a basis for refinements, based on students’ and faculty feedback, to make sure the tool is within the course goals. The adoption will be based on long-term continuous assessment and continuous improvement, as well as introducing simulation in teaching. Adopting this systematic approach will make sure that the technology transition will not only impact the outcomes of learning but also will be viable, sustainable, and relevant to the accreditation criterion.

Three Primary Academic Stakeholders

The three independently and collectively active academic stakeholders engaged in the assessment of the curricular technology needs in a variety of ways and from their respective vantage points. The faculty played a crucial part in evaluating the course objectives to determine the feasible incorporation of AI-based virtual simulation into existing learning objectives (Hong et al., 2025). They emphasized the importance of innovating the present pedagogical practices, including interactive learning scenarios and the support offered by the utilization of AI tools in learning competencies, specifically in critical thinking, decision making, and community health skills.

Students recounted their first-hand experiences of learning, feedback to them on areas that should be improved upon, interactivity, engagement, and applicability to real world of the expected learning environment. They also wanted to take into account factors of accessibility – such as device compatibility, internet connection, and access, whether the offered technologies would meet the needs of a broad range of learners, and provide better access. IT Personnel also carried out a comprehensive assessment of the readiness of the infrastructure, including technical capacity of the institution to host AI-based simulation platforms (Engíairo, 2024).

Methods of Collaboration with Stakeholders

The collaboration process included stakeholder engagement and interprofessional working, with structured processes to ensure that there was input into the proposed integration of a virtual simulation with the AI system, transparency, and shared ownership of the overall system. Using the frequent virtual planning sessions enabled faculty, students, and IT staff to share their ideas in real-time and facilitated collaboration and problem-solving (Taranto et al., 2024). Faculty and students were interviewed in focus groups to examine engagement, access, and skill application resources. Many gaps were considered, but the primary concern was the end user.

IT stakeholders were involved in the technical review to assess the infrastructural assessment, the likelihood of integration, and security issues. Shared cloud-based collaboration software (Google docs, boards, etc.) facilitated asynchronous feedback, and all stakeholders participated (Farshad, 2024). The project was a success as they “used” all three types of knowledge, and the result was a co-creation experience which fostered increased acceptance of ideas, a “healthy” political environment, and a solution that fulfilled both the educational and operational needs.

Compare Two Current or Emerging Technologies

Two innovative technologies described in The Role of the BSN Nurse in Promoting Community Health are AI-Enhanced Virtual Simulation and Augmented Reality (AR) Community Health Modules.

AI-Enhanced Virtual Simulation includes immersive, scenario-based education with performance feedback. This is an emerging technology in education that helps students develop critical thinking and clinical decision-making skills (Wei et al., 2025). This technology scales, meaning it is able to reach a sizable population. There are many downsides, such as high costs, licensing commitments, and the amount of faculty training to make this successful.

AR Community Health Modules enrich the real world with digitally augmented information to help contextualize learning. This maximizes engagement and helps link the theory to the practice. The other advantage is the ability to simulate community visit interventions with various population health scenarios (de Miguel-Diaz & Purfaut, 2025). Unfortunately, this relies on advanced technology, and inconsistent access to or use of the technology by students may be an issue.

Table 1:

Comparison of Emerging Technologies

Technology	Advantages	Disadvantages
AI-Enhanced Virtual Simulation	Adaptive feedback, immersive learning, scalable, improve reasoning and decision-making.	High upfront costs, extensive faculty training required.
AR Community Health Modules	Engaging, contextual learning in real-world settings connects theory to practice.	Requires advanced devices, dependent on internet connectivity, and access issues.

Discuss Three Challenges with The Current State of Technology

The technology currently used in the implementation of The Role of the BSN Nurse in Promoting Community Health has several issues with the students’ learning.

Limited Faculty Expertise

Most teachers are not experienced in the use of new technologies like AI simulation platforms. For example, while instructors may be comfortable with the traditional simulation lab, it can be challenging to include adaptive technologies, and therefore, less likely to implement any personalized learning. (Alamri et al., 2020). This has created a gap between the teaching and what is regarded as good teaching and practice in education.

High Implementation and Licensing Costs

The cost of the new technologies is still a significant challenge. For example, if institutions are applying AI subscription services or AR parts, they have to sustainably invest in it (especially if they are programs with minimal funding). But outdated techniques can easily set the tone for the use of outdated techniques, which may impede innovation.

Technical Reliability Issues

 As an example, in the case of an activity, students will not be able to practice some of the critical clinical situations when the virtual simulation does not function (Sam et al., 2023). It is these interruptions which result in less confidence with technology, and they block the learning of skills. All of these show why it is important that investments – and technical infrastructure – are sustainable so that students are better equipped to practice community health.

Overcome Challenges

A clear professional development plan, which will include hands-on workshops, online learning, and mentoring with peers, will be in place to address the lack of knowledge/expertise among the faculty. The faculty will be provided with ongoing support to ensure they gain confidence in using AI generated simulation learning platforms and introducing these in course goals (Lichtenstein & Phillips, 2021). The cost implications will not be a showstopper, but access to latest simulation tools won’t be lost through a phased approach of implementation, institutional grants, and possibilities to find a cost-sharing agreement with the technology vendors.

These risks of technical reliability risks will be mitigated by performing an intensive evaluation of IT infrastructure, a high capacity network, and contingency plans in case of network failure. Systematic software updates and special attention by IT support, as well as preliminary testing of software on a smaller scale in pilot projects before rolling out, will further ensure smooth working. Together, all these strategies will provide for a sustainable, effective, and resilient integration of AI simulation into nursing education.

Summary of Curricular Technology Needs Assessment

The needs assessment shows a notable desire for learning that is adaptive and immersive — an offering that is lacking in traditional learning frameworks as described in The Role of the BSN Nurse in Promoting Community Health. Virtual Simulation with AI Enhancement was deemed to be the best option as it is the only method that has the ability to provide feedback, present realistic scenarios, and quantify improvement in competencies (Wei et al., 2025). This implementation will address the engagement, thinking, and access gaps while working within the accreditation and stakeholder priority frameworks.

Collaboration with Stakeholders

Artificial intelligence-enhanced virtual simulation technology was integrated based on evidence-based practice of inclusive design. A demonstration session, comparative analysis, and a structured survey to gather feedback from stakeholders were conducted (Wei et al., 2025). Faculty members expressed a desire to utilize the technology because it mapped to course goals, outcomes, and competency-based assessment. Students responded positively to the interactivity and adaptability of the simulation and expressed a desire for greater emphasis on interaction and the cultivation of skills. IT staff ensured the compatibility of infrastructure and described technical assistance options to enable an easy implementation process.

This was accomplished by a modified Delphi method of structured decision making, which entails narrowing down preferences based on feedback and anonymously allowing people to rank which options they prefer. So, all settled on AI-Enhanced Virtual Simulation being the best technology because it would be educational, equitable, feasible, and relevant to the curriculum.

Current Technology Challenges

The Role of the BSN Nurse in Promoting Community Health uses standard simulation labs, along with the standard online learning platform. While these technologies may enhance knowledge, they lack the capability to provide adaptive feedback. They also do not have a realistic, AI-driven simulation, nor the ability to generate multiple different community health scenarios (Wei et al., 2025). As a result, these technologies do not facilitate the use of complex decision making and community health interventions in a safe, simulated environment. Community Health Nursing students will learn using the contemporary (or emerging) technologies.

Current or Emerging Technologies

The two emerging technologies that were considered as integrated in The Role of the BSN Nurse in Promoting Community Health course were: AI-Enhanced Virtual Simulation and Augmented Reality (AR) Community Health Modules.

AI-Enhanced Virtual Simulation

Using AI-Enhanced Virtual Simulation, students can be given real-life scenarios and an immersive learning experience as they interact with real-life patients and receive varying feedback from the AI system in line with their performance. The technology encourages the student to learn individually and enables students to learn at a proper speed, focus on their strengths and weaknesses (Cui & Weng Fwuyuan, 2024). The advantages are competency based assessment, data retention for tracking performance, and a large class size. The disadvantages include the need for an initial investment in software and infrastructure, and particular training of the faculty to use it efficiently.

Augmented Reality (AR) Community Health Modules

AR Community Health Modules engage students with a real-life case study, presenting a scenario to students that uses AR overlays to enhance students’ experiences in an AR overlay of current community interventions to improve population health. During the community tours, students will gain a first-hand experience of the health information and environmental risks, as well as health intervention proposals (Faizan Siddiqui et al., 2025). These have advantages regarding engagement of pupils, real-world learning, and linking classroom learning to community health practice.

Technology Challenges

Two main problems arise with the use of AI to create a BSN nurse’s role virtual simulation aimed at augmenting community health. Faculty knowledge is the first of these problems, as many faculty members lack the ability to appropriately use advanced simulation software due to their lack of experience with it (Faizan Siddiqui et al., 2025). If there is insufficient coaching, the faculty members may not be able to understand the latent opportunity cost. The second of these problems is the cost, including the licensing, the cost of equipment, and the cost of implementation. If not managed, the cost can halt development. Finally, the reliability of the system is a concern – when the software or hardware fails, the regular teaching and learning process is disrupted, and the students are prevented from engaging in learning.

Overcoming Challenges

To overcome these barriers, several recommendations are made: The first one is Faculty Development workshops to enhance their pedagogical and technical capability, so that the faculty members would have no hindrances in conducting the AI-based simulations. Each of these workshops will involve a balance of practical activities, coaching, and support.

Secondly, the implementation will be carried out step by step and will start with pilot projects conducted on a small scale. The slow rollout means that the institution can control the costs and have sufficient time to test it and apply for permanent funding to roll it out more widely. Not least of all, IT support will be required to guarantee the reliability of systems. It will have a professional team of IT support monitoring the platform, and quick troubleshooting, with little downtime, will ensure that the students/teachers’ desired learning experience will not be hindered because of technical issues.

Summary of Curricular Technology Needs Assessment

The needs assessment identified a great gap between current and future requirements for static simulation activities and those to enable engagement in higher order thinking for clinical reasoning in the context of community health, and the provision of adaptive, dynamic, and interactive activities. The AI-Enhanced Virtual Simulation provides students with incredibly realistic patient scenarios, complete with information to engage them in making health care decisions and allowing them to monitor performance to create a custom plan for improvement.

Stakeholder Consensus

A consensus was achieved with the active involvement of faculty, students, and IT staff in an organized manner. The faculty was satisfied with the training that aligned with the learning outcomes of the course, students appreciated the dynamic and flexible simulations, and IT was happy with the technical support side’s feasibility issues (Wei et al., 2025). Using demonstrations and post-demonstration surveys, stakeholders evaluated the functionality and usability of each of the technologies as well as the educational effectiveness they could potentially provide, deeming AI-Enhanced Virtual Simulation the most promising technology for integration.

Factors and Forces to Consider

Organizational Factors

The role of the BSN nurse in promoting community health will benefit from the internal and external organizational factors that support the integration of AI-enriched virtual simulations. Implementation of the project will be influenced positively by the faculty’s interest in new teaching methodologies. Faculty members are likely to adopt the simulation tools that have been proven empirically to promote active participation and higher order thinking among students (Xiong, 2025).

To reduce the burden of additional costs, the existing resources of the simulation lab will be utilized during the initial stages of implementation. Some of the internal factors will be the inadequate knowledge of faculty members on AI simulation and the lack of time caused by an inflexible curriculum.

From an external point of view, there is a noticeable effort to integrate the concept of ‘digital competency’ into the accreditation criteria of nursing education, which establishes a connection between the idea of technology and applicable regulatory standards. The integration of AI tools and expert-level simulation learning recommendations (Stenseth et al., 2025) is testimony to this. However, in an effort to control costs, a long-term budget may compromise the institution’s ability to adapt the technologies to course requirements, as there is a reliance upon vendors and a limited scope for custom simulation software.

Table 2:

Organizational Internal and External Factors

Category	Facilitators	Barriers
Internal Factors	· Strong faculty interest in innovative pedagogies that enhance engagement.· Existing simulation lab infrastructure that can support the integration of new tools.	· Limited faculty expertise in AI simulation platforms requires extensive training.· Curriculum scheduling constraints are making it difficult to allocate time for training and piloting.
External Factors	· Accreditation standards that emphasize digital competency align with proposal goals.· Professional endorsements supporting simulation-based learning in nursing education.	· Vendor dependency and limits in software customization are reducing flexibility.· Cost variability due to market trends impacts long-term financial sustainability.

Forces for Integration

This first relates to teaching faculty being supportive of innovative pedagogy directly related to competency-based outcomes of the course. Faculty members supportive of innovative pedagogy have laid the groundwork and are using AI-centered simulations to help prepare students to practice critical thinking and decision-making skills in community health practice (Wei et al., 2025).

The second relates to the expectation which involves being the provider of highly interactive and technology-based learning to the nursing students. Students are becoming increasingly comfortable with the use of technology and online learning, and an engaging and attractive learning experience must be provided to help prepare them to accept the challenge to employ artificial intelligence (AI) and leverage the technology to learn at varying degrees of pace, utilizing AI for instant and individualized learning feedback.

Lastly, there is the support of the profession and accreditation agencies of learning through simulation. Accreditation bodies and the nursing profession cite the need to incorporate digital literacy and learning through simulation in nursing education. The advice provided is in line with the immersion of students to experience practice-based community health learning using simulation and working with evidence (Birkhiem et al., 2023).

Challenges to Integration

High Initial Investment Costs

Acquisitions, upgrades to infrastructure, and the provision of long-term technical support are significant challenges (Rashid et al., 2025). An example of this is the purchase of AI simulation software and VR hardware, which may have a fixed cost, making the issue of scalability apparent. Such procurement is often justifiable as improved learning outcomes are associated with such purchases; however, it may have the drawback of consuming significant and intensive institutional resources.

Faculty Resistance and Training Needs

Many faculty members don’t know the technology and delays in advances with AI driven simulation technologies. This may lead him or her to feel like he/she has too much to do or not technically secure (Trust & Whalen, 2021). The benefit of having faculty participate is that they get to experience innovative pedagogy; the challenge of this is the amount of professional learning that is needed and the time it takes.

Technical Reliability Issues

Across the board use of the most up-to-date digital tools can carry a risk of software failures, loss of connectivity, and potential incompatibility with the learning management system. For example, in a community health scenario, when the simulation crashes, it takes away the learning opportunity and decreases the students’ confidence in the simulation. The good thing: the advanced tools will allow exposure of the setting; the bad thing: there is a potential for interference, as well as interference to the teaching-learning process.

Change Theory

Justification of Change Theory

With this in mind, Lewin’s Change Theory will be used as a reference model to enrich the incorporation of AI enhanced virtual simulation within The Role of the BSN Nurse in Promoting Community Health. The three-stage process of unfreezing, changing, and refreezing allows for the technical and human adoption of the model to be integrated. (Charles et al. 2024). Lewin’s model will be most beneficial to schools, as this type of change involves not only the collaboration of the faculty and the students, but also the IT support staff, who will assist in the change process at the school. The focus on stakeholders is appropriate as it is important for the buy-in of the stakeholders and a means to achieve long-term sustainability after the technology has been integrated.

Potential Resistance to the Technology

Resistance

Many people have come to accept new processes, resulting in resistance. Faculty might have concerns about changing to AI-assisted virtual simulation as they are accustomed to traditional methods and might be worried about the need for additional training (Charles et al., 2024). The students may also be hesitant due to lack of access, the complexity of the high tech simulation software, and/or fairness. In addition, teachers and/or students might not regard AI feedback as reliable as human feedback.

Barriers

Barriers are barriers (either structural or logistic) that may hinder implementation. Economic, as licensing the AI simulation platforms as well as infrastructure changes requires extensive investments. Certain of these variables that can cause bad usability are technical problems, for instance, connectivity problems, being forced to stay with a particular system in LMS, or vulnerable to internet connection loss. The other problem is the lack of resources, as not every student has access to a high-speed Internet service or has up-to-date equipment, which means that they are unable to make the most of the simulations, leading to inequalities in learning.

Plans to Implement Change Theory

Lewin’s Change Theory will be used to shape the inclusion of AI-enhanced virtual simulation because it offers a systematic process of effective adoption.

Unfreezing

This step aims to ensure that people are aware that a change is required. Orientation activities and preliminary presentations will focus on the advantages of AI simulations. This includes enhancements to the decision-making process and custom feedback from the instructors, the students, and the IT support staff (Kar et al., 2022). When the misconceptions are cleared up, discussions and the general resistance to the change will be minimized.

Changing

This will be the first step towards the new technology to be implemented in stages. The teachers will be trained and mentored on their integration of AI-based simulations into specific learning units. IT will ensure that students are provided with a basic and regular set of technical support, and pilot sessions will be held for students (Vanteddu, 2024). The feedback from all the stakeholders will be utilized to take the necessary corrective actions that will lead towards “functionality and integration with learning outcomes”.

Refreezing

After adopting, the use of AI simulation will be carried out as part of the curriculum. Changes will also be made to the individual policies, continuing professional development will be provided, and systems will be established to monitor the results, which will help to normalize the change.

Conclusion

Proposal to add virtual simulation component to the course, The Role of the BSN Nurse in Promoting Community Health, to support clinical reasoning, adaptive decision making, and individual learning with the use of AI technology. The rationale for this is based on the two trends: first, the need for nurse students to be digitally competent in the curriculum, and second, the effectiveness of simulation in helping nurse students to perform better in challenging community health scenarios. All of the identified problems resulting from the needs assessment, and covered by this proposal, are directly related to the needs gap identified in the curriculum (Experiential Learning Opportunities, Feedback Mechanisms, and High-fidelity training-related resources).

Introducing AI-based adaptive simulations will instill a difference between theory and practice in the curriculum with a scalable, interactive, and evidence-based learning experience. This is a significant initiative for the entire nursing profession as it will impact the transition to new technologies in health care, innovative teaching methods, and a new generation of nurses learning about the use of AI in hospitals. The effects don’t just lie in learning skills that support critical thinking, data-based decision-making, and learning centred on the person in different community settings.

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