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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.
Cureus
|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.
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.
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