Complex Adaptive Competency Lab

The Complex Adaptive Competency Lab (CACL) is a collaborative effort of the College of Nursing’s Steele Innovative Learning Center (SILC) and Office of Learning and Healthcare Technology Innovations (LHTI) – blending existing expertise in nursing education and practice with talent in instructional design and technology. Working together, the team will study and develop adaptive competencies and education strategies, select and acquire equipment and software, develop custom AR/VR solutions, and conduct pilots to evaluate the efficacy of these competencies, strategies, and technologies.

The Lab supports:

• Professional development in the area of immersive learning technologies (AR/VR, etc.)
• Virtual reality software designed for nursing students, along with computers and VR headsets
• iPads, biomedical training devices, and apps for student learning opportunities
• Sponsorship of student workers with Eller Tech Core, the Department of Systems & Industrial Engineering, the Center for Digital Humanities, and more.

The Lab aligns with the University of Arizona's Strategic Plan and advances the goals of Pillar 1: The Wildcat Journey. The Lab will be used to develop adaptive learning, resiliency, critical thinking, and creative problem solving skills necessary for our nursing graduates to lead and succeed in the fourth industrial revolution (4IR).

Intelligent Simulation Environment (ISE)

Project Dates: January 2022 – June 2022

The Intelligent Simulation Environment (ISE) prototype will integrate UA SensorLab resources (e.g. eye tracking, motion tracking, heart-rate variability, electrodermal activity) with mixed reality (MR), and artificial intelligence (AI) applications to promote complex adaptive competencies (CAC) learners need to meet 4th industrial revolution challenges. CACs involve successful and efficient implementation of evidence-based solutions resulting from individual or team augmented decision making. This decision-making requires accurate situation awareness (SA), seeking, synthesizing, and adapting information from multiple sources in dynamic technology rich contexts. Additionally, the ISE will promote trapping error generating factors and mitigation strategies when errors occur. The principal project aim is to build UA SensorLab capacity and create an ISE prototype to facilitate future development of portable high-stakes domain specific XR simulations to assess and coach learner CACs. This project involves new collaborations between UA CON simulation, curriculum and technology specialists, Systems Engineering and Center for Digital Humanities (CDH), and SensorLab experts. The ISE aligns with the UAHS strategic plan by helping to prepare learners for the future and optimizing interactions between humans and technology to solve complex problems.

View ISE Poster

Simulated Clinical Time Travel and Augmented Intelligence to Prevent and Manage Patient Deterioration

Project Dates: July 2022 – June 2025

The proposed three-year CUES Fellowship project will develop and evaluate the feasibility of new clinical simulations that allow individuals and teams to travel back and forth in simulation-time (sim-time) along the trajectory of patterns of patient physiologic deterioration. Clinical simulations provide powerful immersive experiential learning environments that allow learners to develop competencies without risk of harming actual patients. Sim-time travel will support learner trialing of multiple treatment choices and opportunities to go back in sim-time to correct mistakes while compressing events that usually occur over many hours into scenarios lasting one to three hours. The principal aim of this project is to develop and evaluate the feasibility of new sim-time travel simulations that use emerging technologies to prepare interprofessional healthcare teams to identify, prevent and successfully manage patient deterioration. University of Arizona Health Sciences (UAHS) students attending the final courses of their respective programs will be invited to trial these high-risk patient-centered simulations.