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Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

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Ambient Listening Devices as a Feedback Tool in the Simulated Learning Environment.

Robert Snedegar¹, Kendra Unger¹, Jason F Craig²

¹Department of Family Medicine, West Virginia University School of Medicine, Morgantown, USA.

|February 12, 2026

Summary

Artificial intelligence (AI) ambient listening (AL) shows promise for providing formative feedback in medical education. This pilot study found AI-generated feedback feasible, well-accepted, and aligned with learner self-assessments in simulated patient encounters.

Keywords:

ambient listening artificial intelligence formative feedback medical education simulation in medical education

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Area of Science:

Medical Education
Artificial Intelligence
Clinical Simulation

Background:

Limited evidence exists for AI in providing formative feedback during simulated clinical encounters.
Ambient listening (AL) technology, while useful for documentation, is underexplored for educational feedback.
This study addresses the need to evaluate AI-generated feedback in undergraduate medical education.

Purpose of the Study:

To assess the feasibility of AI-generated feedback using AL technology.
To evaluate the perceived quality and learner acceptance of this feedback.
To explore AI's role in supplementing formative feedback in simulated patient encounters.

Main Methods:

First- and second-year medical students participated in simulated patient encounters.
Encounters were recorded using an AI-powered AL application.
Automated feedback and SMART goals were generated; learners completed a validated survey on feedback quality.

Main Results:

All participants found AI feedback sufficient, actionable, and behavior-linked.
Qualitative feedback described AI-generated comments as accurate and aligned with other assessments.
Learners suggested improvements for greater context and specific examples.

Conclusions:

AI-powered AL is a feasible and well-accepted method for supplementing formative feedback in simulated clinical settings.
It may offer a scalable alternative to direct observation, especially with limited faculty.
Further multi-institutional studies are needed to confirm generalizability and educational impact.