Faculty mentor/PI email address

jim010@aol.com

Is your research Teaching and Learning based?

1

Keywords

Appreciative Inquiry; Emergency Medicine Education; Attending Teaching; Graduate Medical Education; Positive Deviance; Positive Sentinel Events; Complex Adaptive Systems; Resident Education; Clinical Teaching; Educational Culture

Date of Presentation

5-6-2026 12:00 AM

Poster Abstract

Background

Teaching in the Emergency Department (ED) occurs within a complex adaptive system characterized by time pressure, interruptions, and high cognitive load. Studying what works well in clinical teaching , even in such a challenging  environment for  teaching, may reveal reproducible patterns that strengthen educational culture, enhance resident learning, and accelerate the development of teaching expertise. In complex clinical environments, excellence is often present but under-recognized; An approach called Appreciative Inquiry provides a structured method for making it visible.

Conceptual Framework

Appreciative Inquiry (AI) offers an alternative approach by systematically studying successful practices rather than failures. AI explores how and why positive outcomes occur so they can be understood and replicated. Within healthcare systems, this approach aligns with right-tail performance analysis, in order identify and learn from exceptional system functioning.

Application to Emergency Medicine Teaching

In the context of attending–resident teaching, Appreciative Inquiry can help identify moments when educational interactions are particularly effective and explore the conditions that produced them. These moments may emerge from the interaction of clinical complexity, cognitive apprenticeship, timing, and interpersonal dynamics, reflecting the emergent properties of a complex adaptive learning environment.

Educational Strategy

This conceptual model illustrates how AI can be applied to attending teaching using the Discover–Dream–Design–Destiny model, with reflective questions that guide faculty and resident discussion. The goal is not to prescribe a fixed teaching method, but to identify reproducible patterns of effective teaching behavior already present within the system.

Implications

By focusing on high-functioning teaching moments, Appreciative Inquiry complements traditional problem-focused approaches and aligns with emerging interest in positive sentinel events and right-tail performance analysis in healthcare systems. This approach offers a non-punitive, strengths-based pathway for faculty development and educational improvement.

Conclusion

Studying what works well in clinical teaching may reveal reproducible patterns that strengthen educational culture, enhance resident learning, and accelerate the development of teaching expertise. In complex clinical environments, excellence is often present but under-recognized; Appreciative Inquiry provides a structured method for making it visible.

Disciplines

Emergency Medicine | Medical Education | Medicine and Health Sciences

Share

COinS
 
May 6th, 12:00 AM

Identifying and Generalizing Best Attending Teaching Practices: A Proposal for the Use of Appreciative Inquiry to Enhance Emergency Medicine Residency Teaching Practices

Background

Teaching in the Emergency Department (ED) occurs within a complex adaptive system characterized by time pressure, interruptions, and high cognitive load. Studying what works well in clinical teaching , even in such a challenging  environment for  teaching, may reveal reproducible patterns that strengthen educational culture, enhance resident learning, and accelerate the development of teaching expertise. In complex clinical environments, excellence is often present but under-recognized; An approach called Appreciative Inquiry provides a structured method for making it visible.

Conceptual Framework

Appreciative Inquiry (AI) offers an alternative approach by systematically studying successful practices rather than failures. AI explores how and why positive outcomes occur so they can be understood and replicated. Within healthcare systems, this approach aligns with right-tail performance analysis, in order identify and learn from exceptional system functioning.

Application to Emergency Medicine Teaching

In the context of attending–resident teaching, Appreciative Inquiry can help identify moments when educational interactions are particularly effective and explore the conditions that produced them. These moments may emerge from the interaction of clinical complexity, cognitive apprenticeship, timing, and interpersonal dynamics, reflecting the emergent properties of a complex adaptive learning environment.

Educational Strategy

This conceptual model illustrates how AI can be applied to attending teaching using the Discover–Dream–Design–Destiny model, with reflective questions that guide faculty and resident discussion. The goal is not to prescribe a fixed teaching method, but to identify reproducible patterns of effective teaching behavior already present within the system.

Implications

By focusing on high-functioning teaching moments, Appreciative Inquiry complements traditional problem-focused approaches and aligns with emerging interest in positive sentinel events and right-tail performance analysis in healthcare systems. This approach offers a non-punitive, strengths-based pathway for faculty development and educational improvement.

Conclusion

Studying what works well in clinical teaching may reveal reproducible patterns that strengthen educational culture, enhance resident learning, and accelerate the development of teaching expertise. In complex clinical environments, excellence is often present but under-recognized; Appreciative Inquiry provides a structured method for making it visible.

 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.