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Session Design Submission Review

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AI-powered Avatars: Making Feedback Delivery Accessible and Individualizable

Session TypeWorkshop

Ahmad Hider MD,MPhil
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AI-powered Avatars: Making Feedback Delivery Accessible and Individualizable
Is this submission from an ASE Committee, Task Force, or Working Group?

No

Are you a member of ASE?

Yes

Session Information

Session Description

Feedback is one of the most powerful tools in medical education. When delivered effectively, it enhances learning, sustains motivation, and drives performance improvement. When delivered poorly, however, it can erode psychological safety. Yet feedback delivery remains a challenge for many educators, often due to timing, discomfort, or limited structured training.

Traditional faculty development uses lectures, small-group role play, and mock learners. These methods are limited by low fidelity, massed rather than deliberate practice, high cost, and labor intensity. In recent years, artificial intelligence (AI) has emerged as a scalable, customizable solution to enhance teaching skills. AI-powered avatars represent a novel advancement that directly addresses many challenges. By simulating learners in immersive, interactive environments—complete with character history, emotions, and clinical context—avatars allow faculty to practice delivering feedback in scenarios that mirror real teaching. Participants can rehearse particularly difficult situations, such as addressing professionalism concerns, underperformance, or peer complaints. Avatars also use structured rubrics to give immediate, standardized feedback on the educator’s performance.

Pilot work demonstrates the feasibility and promise of this approach: faculty describe avatar sessions as engaging, realistic, and directly applicable to daily teaching. Participants report improved comfort and skill in giving constructive feedback. This workshop introduces an evidence-based, technology-enabled method for strengthening feedback delivery skills and shows how to integrate it within departments and institutions. In doing so, it advances the ASE mission to foster surgical education innovation and prepares faculty to deliver the high-quality feedback essential to training the next generation of surgeons.

Learning Objectives

  • Recognize the importance of effective feedback and evidence-based strategies such as the Ask–Tell–Ask (ATA) model.
  • Identify challenging feedback scenarios common to educators and program directors that benefit from rehearsal.
  • Practice delivering feedback in avatar-simulated encounters to build skill and confidence using this novel technology.
  • Explore opportunities to integrate AI-driven avatars into faculty development for scalable, real-time coaching.

Session Methods & Format

  • 0–5 min: Introduction to session goals and the impact of feedback (all facilitators)
  • 5–15 min: Interactive mini-didactic on feedback principles and pitfalls (Gardner)
  • 15–20 min: Participants identify difficult feedback scenarios from their own teaching
  • 20–40 min: Small-group breakouts (5 groups, each led by a facilitator):
    • Faculty interact with AI avatars portraying medical students in challenging scenarios (e.g., poor presentations, professionalism concerns).
    • Participants deliver feedback using the ATA model.
    • Avatars provide rubric-based feedback; participants reflect on approach.
  • 40–60 min: Large-group debrief on integrating AI avatars into curricula and faculty development.

Educational Strategies

  • Experiential learning with avatars
  • Immediate, rubric-based feedback
  • Peer discussion and reflection
  • Emphasis on scalability, realism, and application to clinical teaching

Experience of Presenters

  • Aimee Gardner, PhD: Associate Dean for Faculty Development, widely published on feedback and faculty development interventions.
  • Ahmad M. Hider, MD, MPhil: Surgical resident and health policy researcher focused on medical education innovation.
  • Nicole Christian, MD: Breast Surgical Oncology Surgeon, Associate Program Director – General Surgery Residency
  • Madhuri Nagaraj, MD: General Surgeon, Critical Care Fellow

Concise Summary:
This workshop introduces AI-powered avatars as a novel, scalable platform for practicing and improving feedback delivery. Through immersive scenarios, participants will apply evidence-based strategies, receive structured coaching, and explore AI’s potential to transform faculty development globally.

Workshop Length

45-minute workshop

If a similar workshop is submitted, would you be willing to combine workshops into one session?

Yes

Would you be open to presenting a workshop of a different duration than selected above if needed?

Yes

Course Objective 1

Recognize the importance of effective feedback and evidence-based strategies such as the Ask–Tell–Ask (ATA) model.

Course Objective 2

Identify challenging feedback scenarios common to educators and program directors that benefit from rehearsal.

Course Objective 3

Practice delivering feedback in avatar-simulated encounters to build skill and confidence using this novel technology.

Session Objective 4

Explore opportunities to integrate AI-driven avatars into faculty development for scalable, real-time coaching.

Session Outline
Activity Order Title of Presentation or Activity Presenter/Faculty Name Presenter/Faculty Email Time allotted in minutes for activity

1

Introduction to session goals and the impact of feedback (all facilitators)

Aimee Gardner

AIMEE.GARDNER@CUANSCHUTZ.EDU

10

2

Small-group breakouts (5 groups, each led by a facilitator):

Ahmad Hider

ahmad.hider@cuanschutz.edu

40