Harnessing Artificial Intelligence and Video Technology for On-Demand Microlearning in Medical-Surgical Nursing: A Novel Approach to Mentorship

Abstract

Artificial Intelligence (AI) is a new tool for medical-surgical nurses to create on-demand educational opportunities. Integrating AI and video technology to deliver on-demand microlearning sessions can help the medical-surgical nurse stay current with the latest developments in the nursing profession. For instance, AI can assist in identifying abnormalities in imaging or abnormal heart rhythms on rhythm strips, bridging the gap between learning opportunities and clinical practice needs, and enhancing patient safety and quality of care.

Transitioning from academia to clinical practice can be challenging for new nurses, particularly in developing clinical judgment. Experienced nurses play a crucial role in mentoring and guiding novice nurses. Still, traditional mentorship models can be time-consuming and may not address the individual needs of the new nurse. This abstract proposes an innovative approach to supporting new nurses in their practice through videos, AI, and short, on-demand microlearning modules.

Background

Clinical judgment is a critical component of the nursing practice, requiring the integration of knowledge, experience, and critical-thinking skills. Novice nurses often struggle to apply theoretical, evidence-based knowledge to real-world scenarios, leading to errors and poor patient outcomes. Traditional mentorship models, such as preceptorship and coaching, have their place but are often limited by time constraints, availability of experienced nurses, and acuity of the patient population on the unit.

Innovative Approach

Using videos, AI, and microlearning to provide novice nurses with personalized, on-demand support in developing clinical judgment can make a difference in retaining and developing new nurses.

• Video scenarios: Using video to create high-fidelity, realistic scenes depicting everyday clinical situations allows the new nurse to observe and learn from the experienced nurse’s decision-making process while maintaining safety for the patient and the new nurse.
• AI-powered analysis: AI algorithms assess new nurses’ responses to video scenarios, providing instant feedback on their clinical judgment and identifying areas of improvement. Some simulation centers are currently using video debriefing to help student nurses learn from their simulations. The same concept can be used in the clinical setting as long as the patient’s protected health information is not compromised when creating the microlearning video module (Ghane et al., 2024).
• Microlearning: Short learning opportunities can help individuals retain information and keep learners' short attention spans to deliver the information (Littleton et al., 2024). Bite-sized, interactive modules can focus on specific clinical judgment skills, such as prioritization, critical thinking, and communication. Modules are designed to be available on-demand, allowing new nurses to access them conveniently.
• Personalized learning plans: AI-driven recommendations for microlearning modules based on the novice nurses’ performance in video scenarios ensuring targeted support and efficient use of time. Video learning plans can be created to provide continuing education units depending on the facility and accrediting bodies.

Implementation and Evaluation

The platform for microlearning plans depends on the facilities' requirements, accreditation requirements, etc. Anyone can create and post videos on various social media sites if the creator desires. However, the content creator must ensure that evidence-based practice information is portrayed in these microlearning videos. Nurses should speak with their nursing professional development department at their facility if they are interested in creating microlearning videos that adhere to their state and institution's scope and standards of practice.

Here are some ways microlearning video modules can be created, implemented, and evaluated for competencies.

• Clinical judgment skills: Pre- and post-intervention assessments using standardized tools. One available tool is the Lasater Clinical Judgment Rubric (Lasater & Nielson, 2024).
• Confidence and self-efficacy: Surveys and focus groups to explore new nurses’ perceived confidence and self-efficacy in clinical judgement. Having new nurses talk about their feelings and expectations can be helpful in creating and implementing microlearning video subjects.
• Patient safety and quality of care: Retrospective chart reviews and incident reports to assess the impact on patient outcomes. Quality and risk management can help provide data for areas where nurses may need more training, which could be subject matter for learning videos.

Expected Outcomes

After implementing a microlearning video and AI lesson plan, the outcomes should be evaluated and documented to show the value of the microlearning modules.

• Improved clinical judgment skills in new nurses, enhancing patient safety and quality of care. AI can provide reflective practice tools, clinical decision support, and patient similarity analysis to enhance the nurse’s clinical judgment continually.
• Increased confidence and self-efficacy in new nurses, fostering a more engaged and resilient workforce.
• Efficient use of experienced nurses’ time, allowing them to focus on complex cases and high-touch mentoring.

Conclusion

Integrating AI with video technology to create a microlearning platform for medical-surgical nurses addresses several challenges associated with conventional continuing education. First, the brevity and specificity of microlearning sessions align with nurses' time constraints, making it a practical solution for ongoing professional development. Second, the AI’s adaptive learning capabilities ensure that each nurse’s unique education needs and learning pace are accommodated, which is not feasible in standard educational settings. Third, video content serves as a powerful medium for demonstrating clinical procedures and scenarios, potentially leading to better practical understanding and application.

The proposed approach to harnessing the power of video, AI, and microlearning to support novice nurses in developing clinical judgment addresses a critical need in nursing professional development and education. By providing personalized, on-demand support through microlearning video and AI tools, novice nurses can be empowered to succeed in their clinical judgment, ultimately improving patient outcomes and the nursing profession.

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