NURS FPX 6109 Assessment 2 Vila Health: The Impact of Educational Technology

NURS FPX 6109 Assessment 2 Vila Health: The Impact of Educational Technology

The Impact of Educational Technology

The adaptation and use of technology in nursing education give comprehensiveness to learning methods and techniques. Nursing education is a complicated yet vast field and always has various opportunities and requirements for new advancements. Technology helps students to get a fast grip on the topic, in understanding the technique, and they will be able to apply it more efficiently in their professional life. Advanced learning tools develop advanced cognitive skills, critical thinking abilities, and structural behavior in students toward a medical problem. Nursing educators also improve their teaching methods by restructuring the student curriculum and practice techniques (Hopkins et al., 2018).

Description of New Technology

Johns Hopkins School of Nursing is using Artificial Intelligence as a modern teaching tool for students. It facilitates nursing students to study and analyze modern world health challenges and become familiar with the forecast situations and remote health services. Machine Learning (ML) brought huge advancements in nursing education through the implementation of AI-based robotic modules. The addition of ML and robotics gives nurses exposure to the technical and statistical association of data processing with AI learning tools. AI-based prototype 3-D frameworks will give them an edge in learning technological interventions and being capable of handling complex situations, and being competent against viral diseases, and global pandemics in their careers in medical hospitals (Lee & Yoon, 2021).

NURS FPX 6109 Assessment 2 Vila Health: The Impact of Educational Technology

As machine-based learning and technical training will broaden the vision of nursing graduates in applying artificial intelligence in clinics and hospitals, however, the nursing school has also improved their mode of access to simulation learning. Collaboration between the teaching department and Information Technology has digitized the organization and facilitated students in remote learning. Education faculty with the help of Information and Communication Technology (ICT) has introduced virtual classroom tours and separate IT services for students. Online chat sessions are recommended on the school website for advanced MSN, DNP, and Ph.D. programs as well as for the Entry into Nursing program.  Online tours give ideas to new students for the implementation of machine learning and robotic modules through coursework. Software and computer-based virtual models and 3-D modules will help students to analyze and process data through automation. Bringing advancement in nursing education through AI and technology aims at the development of human-like intelligence and using it to promote better diagnostic and treatment strategies in nursing practice (Ross et al., 2019).

Impact of AI Technology Changes on an Organization’s Mission

Johns Hopkins University as a research organization is focusing on its mission of improving public health through nursing education with the help of technology. The organization’s mission is to work out certainty with Explainable mode. Required changes are implemented to meet the research gaps in modern teaching strategies and evidence-based interventions. The Johns Hopkins Hospital has created a command center through AI which will help the teaching faculty in a smooth workflow. The Command Center assists hundreds of queries by students and faculty on a daily basis.  Engineers and technicians with ML technology are developing advanced tools for manufacturing more accurate, detailed learning modules, and medical imaging which provides a broad view of human anatomy (Carrasco, 2019). To develop a better understanding of the course and practical approach, machine translation is required. Expert translators and software developers help in developing a brief course outline and easy access to online tools for nursing students. Nurses will become more educated regarding the utilization of AI tools from the theoretical assessments. These advanced learning tools and techniques will make students able to better understand the situation, quickly diagnose, and develop professional skills which support the organization’s mission and achievement of public health safety goals assisted by educated nurses (Maier et al., 2019).

Impact of Changes on Organization

Artificial intelligence and its implementation in learning methods at the nursing school have helped the nurses at Johns Hopkins Hospital in developing more efficient interventions and treatment strategies. Machine-based learning has put practical influence on nursing education. It made them more confident in their research surveys and findings. Students better understand human anatomy through 3-D models and prototype modules, the accuracy of diagnosis through medical imaging, and a systematic approach toward treatment through AI (Henry et al., 2022). Nursing graduates work on a specific pattern and evaluate the strategy through automated decision-making approaches suggested by the system. Students learn to follow a neurotic framework with the help of neural networking in which even a single neuron interprets itself as a whole. The neural framework facilitates them to capture critical information using traceable technology and maximizes the possibility of a positive outcome. The evidence-based working strategy will help students in creating potential and clinically supportive treatment strategies with the possibility of fewer errors. Technology-based learning and its practical implementation sure have a positive impact on patient safety and care (Bakator & Radosav, 2018).

Role of Nursing Educators in Technology Changes

Nursing educators have a huge responsibility of training future nursing professionals and equipping them with the necessary expertise to tackle emerging challenges in the future. Educators play an important role in the development of practical skills and problem-solving abilities in students. Educated nurses can better adapt AI learning tools for performing efficiently in hospitals and remote healthcare settings (Li et al., 2019). Technology change and its implementation in clinics are not only challenging but also very intriguing because it needs to get hands-on practice first to become able to provide appropriate care to patients in hospitals. Educated nurses will utilize their knowledge of AI tools for better diagnosis and treatment strategies. Using the advanced tools nurses will provide patients with remote service and platforms that will help them to learn self-management strategies. Nurses make changes in their professional approach towards patients according to the applied AI tools and patient-centered treatment plans that will improve the overall working of a healthcare system. Coordination of nursing educators with technical and laboratory staff is needed for them to bring technology-based learning methods to Hospitals. Improved clinical practices based on AI and ML tools will improve patients’ health care and safety. Nursing educators facilitate the patients in better implementation of the intervention and ensure patient safety and care (Fawaz et al., 2018).

NURS FPX 6109 Assessment 2 Vila Health: The Impact of Educational Technology

Incorporation of Changes in Nursing Education Program

Implementing changes in nursing education through artificial intelligence and machine learning requires a very pragmatic approach. These technological changes in teaching methods have been integrated at the right pace to successfully incorporate the outcomes in clinical practices. The University should plan practice programs for students at which these changes must be implemented on robotic modules. They need to be wary of the impact of these changes on the students, nursing educators, and patient care and safety in the future (Lattouf, 2022). Information Technology and Communication (ICT) staff should incorporate the effectiveness of specific learning tools virtually. Educators and course planners should collaborate with technical staff to account for any long-term consequences that AL-based learning and ML tools might have. The use of AI and machine learning methods in nursing education has proven to be effective in enabling students to structure positive interventions and practice remote health strategies. The incorporation of technological changes in learning methods also develops cognitive skills and will help them in gaining a professional approach toward patients (Levett-Jones et al., 2019).


Artificial intelligence and machine learning have modernized nursing education. Robotic and prototype modules help students in better exposure to clinical practice and conducting data processing and analysis. Students become able to excel in clinical practices through prototype learning modules. Virtual learning sessions and tours help nursing graduates to choose the best suitable options for specialization. Nursing schools and trainers should be able to adopt these changes as early as they are declared effective to further process the changes in the learning curriculum. All these professional strategies will help the organization in achieving its goals related to public health.

NURS FPX 6109 Assessment 2 Vila Health: The Impact of Educational Technology


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Carrasco, D. (2019, December 4). Artificial Intelligence: An Innovative Technology in a Vital Industry.

Fawaz, M. A., Hamdan-Mansour, A. M., & Tassi, A. (2018). Challenges facing nursing education in the advanced healthcare environment. International Journal of Africa Nursing Sciences, 9(1), 105–110.

Henry, K. E., Kornfield, R., Sridharan, A., Linton, R. C., Groh, C., Wang, T., Wu, A., Mutlu, B., & Saria, S. (2022). Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system. Npj Digital Medicine, 5(1).

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Lee, D., & Yoon, S. N. (2021). Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges. International Journal of Environmental Research and Public Health, 18(1), 271.

Levett-Jones, T., Cant, R., & Lapkin, S. (2019). A systematic review of the effectiveness of empathy education for undergraduate nursing students. Nurse Education Today, 75, 80–94.

Li, C., He, J., Yuan, C., Chen, B., & Sun, Z. (2019). The effects of blended learning on knowledge, skills, and satisfaction in nursing students: A meta-analysis. Nurse Education Today, 82, 51–57.

Maier, A., Syben, C., Lasser, T., & Riess, C. (2019). A gentle introduction to deep learning in medical image processing. Zeitschrift Für Medizinische Physik.

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