B. Reimagining Nursing Education and Professional Pathways Through Collaborative Interdisciplinary Approaches: Innovations in learning, mentorship, competency assessment, and collaborative workforce development
Beyond the Bedside: Reimagining Competency Assessment through Immersive Virtual Reality Simulation and AI-Driven Insights presented by Cynthia Bradley
Preparing nursing students for complex professional practice requires diverse strategies to assess clinical competence. Traditional clinical experiences offer real-world interactions, but immersive virtual reality (IVR) simulations offer standardized, scalable environments. Tools such as the Creighton Competency Evaluation Instrument for Clinical (CCEI-C) provide structured competency assessment, yet limited evidence compares student performance across real-world and virtual settings or demonstrates how IVR-generated data can be meaningfully analyzed using artificial intelligence.
Purpose: This study examined 1) the utility and performance of the revised 28-item CCEI-C) to assess clinical competence in direct patient care and IVR and 2) artificial intelligence (AI) analysis of IVR-generated data can deepen understanding of student performance.
Method: Using a quasi-experimental, multi-site design, 1031 senior pre-licensure nursing students across one academic semester. Students were evaluated using the CCEI-C during mid-term and final direct patient care clinicals, and across a series of five multi-patient IVR scenarios. In IVR, learner actions were captured and scored automatically. IVR data were extracted and analyzed with AI to identify patterns, examine item-level performance, and evaluate how competency was demonstrated over time in increasingly complex scenarios
Results: Mean CCEI-C scores in clinical settings averaged 91.1% at midterm and 99.6% at final. IVR scores were lower and more variable, ranging from 63.5% to 72.9% across scenarios. Psychometric analyses supported strong internal consistency and interrater reliability of the CCEI-C across both environments. LLM analysis of IVR action logs revealed diverse decision-making approaches and clinical judgment behaviors not readily observable in supervised clinical settings, reflecting greater autonomy and opportunities to make and recover from errors.
Conclusions: IVR paired with AI analytics offers an innovative approach to assessing decision-making, prioritization, and clinical judgment. Limited alignment of scores across environments supports multimodal assessment. The CCEI-C performed reliably across settings, while IVR plus AI analysis provided deeper, behavior-level insights beyond checklist scores.
Peer Mentorship: Empowering Nursing Students to Support Each Other’s Success presented by Hanna Belay
Peer mentoring is a well-established strategy for promoting student success, retention, and academic achievement. It benefits both mentees and mentors by fostering professional growth, confidence, and resilience. Faculty also report a reduced need for one-on-one advising when peer mentoring programs are in place. At Saint Cloud State University, the Department of Nursing Science offers both a traditional pre-licensure program and an RN-to-Baccalaureate program. The traditional track follows a five-semester cohort model, with the first two semesters associated with high stress and the greatest risk of attrition. Early-semester students often struggle with time management, study skills, and self-care. Although tutoring support is available, the program lacked a structured support system to address students’ personal, social, and professional challenges through peers who can relate to their unique challenges and experiences. To address this gap, a peer mentoring program was launched in Fall 2020. The program’s primary goal is to support first- and second-semester nursing students in developing strong academic, social, and professional foundations. High-performing, motivated upper-level students are selected as mentors and provided with training and resources to facilitate effective mentor–mentee relationships. Mentors are recruited from the second through fifth semesters through email announcements, faculty recommendations, and an application process. Selected mentors commit to at least one semester and receive training on mentoring skills and available campus resources.
The program is promoted on welcome day, through follow-up emails, and during class visits. Students requesting a mentor complete a short form, and faculty advisors coordinate matching and introduction before mentors initiate contact. Since its launch, more than 70 mentors and 80 mentees have participated. Program outcomes are continuously measured through surveys, and new pre- and post-assessments were added to the Fall 2025 program. Funding for the program has been obtained through a grant to support its implementation.
Strengthening the Clinical Nurse Specialist (CNS) Pipeline A Collaborative Initiative Between Healthcare Systems, University of Minnesota, and MN Affiliate of NACNS presented by Sarah Pangarakis
The "Strengthen the Clinical Nurse Specialist (CNS) Pipeline" initiative represents a collaborative partnership among multiple Minnesota healthcare systems—including HealthPartners, Allina Health, Ridgeview Medical, Essentia Health, M Health Fairview, North Memorial, Children's Minnesota, and the Minnesota affiliate of the National Association of Clinical Nurse Specialists (NACNS)—and the University of Minnesota School of Nursing. This partnership seeks to resolve gaps in clinical nurse specialist education and career placement by advancing the CNS role through targeted academic initiatives, emphasizing its value to healthcare leaders, and creating robust employment pathways
Primary objectives include incentivizing practicing registered nurses (RNs) to enroll in CNS graduate programs, establishing a sustainable flow of qualified CNSs into healthcare systems statewide, ensuring job opportunities within healthcare organizations, and matching CNS students with job opportunities prior to or upon graduation. Academic collaboration is fostered by aligning healthcare system needs with university curriculum priorities, offering guest lectures and preceptorships. Healthcare systems have implemented "Grow Your Own CNS" strategies, such as intern programs, standardized job descriptions and pay grades, and tuition reimbursement for RNs pursuing advanced practice degrees. Efforts to attract future CNSs include marketing, job fairs, and undergraduate role descriptions. The initiative has also developed resources such as campaign videos and executive flyers. The partnership benefits both academic programs and employers by meeting enrollment targets and improving patient safety, quality outcomes, and nursing practice.
Thinking in the Chart: Cognitive Workload and Meaningful Learning in EHR-Based Simulation presented by Marshall K. Muehlbauer
Electronic health records (EHRs) are central to contemporary nursing practice, supporting both documentation and clinical decision-making. While prelicensure nursing students often develop basic EHR documentation skills, they frequently lack the ability to leverage EHR data to support clinical judgment. Simulation-based education offers a promising approach to addressing this gap, particularly when paired with academic EHR platforms. However, EHR-integrated simulations may impose substantial cognitive workload and usability challenges that can influence learning.
This study evaluated cognitive workload, usability, and learner satisfaction during an EHR-focused simulation experience. As part of a larger multi-method study, a descriptive cross-sectional design was used to evaluate a remote simulation conducted at a large Midwestern university. A convenience sample of 10 senior prelicensure nursing students participated in a 60-minute Zoom-based simulation using ATI EHR Tutor, focused on discharge planning for a patient with congestive heart failure. The simulation included a guided prebrief, a 20-minute individual EHR task using the Think Aloud method, and a structured debrief using Debriefing for Meaningful Learning. Informatics competency (SANICS), cognitive workload (NASA-TLX), usability (SUS), and satisfaction (SSE) were measured using validated instruments. Participants reported moderate informatics competency overall, with strong basic computer skills but lower confidence in applied clinical informatics. Cognitive workload was somewhat high, driven primarily by mental demand and effort, while temporal and physical demands remained low. Usability scores for the simulated EHR fell below the accepted benchmark, indicating navigational and interface challenges. Despite these demands, learners reported high satisfaction with the simulation, particularly the debriefing component. Findings suggest that EHR-based simulation is feasible and educationally valuable despite cognitive and usability challenges. Structured debriefing appeared to mitigate frustration and support reflection, reframing cognitive effort as productive learning. EHR-integrated simulation represents a promising strategy for developing informatics competence and clinical judgment when thoughtfully designed to balance authenticity, usability, and reflective support.