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Experiential learning: AMEE Guide No. 63
Open accessAbstract
This Guide provides an overview of educational theory relevant to learning from experience. It considers experience gained in clinical workplaces from early medical student days through qualification to continuing professional development. Three key assumptions underpin the Guide: learning is 'situated'; it can be viewed either as an individual or a collective process; and the learning relevant to this Guide is triggered by authentic practice-based experiences. We first provide an overview of the guiding principles of experiential learning and significant historical contributions to its development as a theoretical perspective. We then discuss socio-cultural perspectives on experiential learning, highlighting their key tenets and drawing together common threads between theories. The second part of the Guide provides examples of learning from experience in practice to show how theoretical stances apply to clinical workplaces. Early experience, student clerkships and residency training are discussed in turn. We end with a summary of the current state of understanding.
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“Clinical reasoning, situational awareness, and tacit professional knowledge, which are central to clerkship learning [55], are difficult to articulate in written form [56] and largely inaccessible to AI systems that operate solely on the written log text.”
From AI-Generated Versus Human Supervisor Feedback on Medical Students’ Clinical Clerkship Logs: Cross-Sectional Convergent Mixed Methods Study (2026) · cites this paper as [56]
In the citing paper
“Its application in medical education is relevant because it focuses on developing competences and practising skills in specific context (behaviour in practice: Yardley et al. 2012).”
From Adult learning theories: Implications for learning and teaching in medical education: AMEE Guide No. 83 (2013) · cites this paper as Yardley et al. 2012
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“Learning and teaching approaches at the bedside are different from the operating room, emergency department or in the community (Durning & Artino 2011;Yardley et al. 2012).”
From Adult learning theories: Implications for learning and teaching in medical education: AMEE Guide No. 83 (2013) · cites this paper as Yardley et al. 2012
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Metadata
- Authors
- Yardley, S., Teunissen, P. W., & Dornan, T.
- Affiliations
- Keele University (GB)
- Maastricht University (NL)
- University of Manchester (GB)
- Corresponding author
- Yardley, Sarah
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2012-01-30
- Volume
- 34
- Issue
- 2
- Pages
- e102-e115
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W2114732155
- Cited by
- 639
- References
- 87
- Citations by year
- 2026: 83 · 2025: 65 · 2024: 58 · 2023: 57 · 2022: 72 · 2021: 55 · 2020: 52 · 2019: 44 · 2018: 35 · 2017: 23 · 2016: 24 · 2015: 22 · 2014: 27 · 2013: 17 · 2012: 4
- FWCI
- 3.49
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Medical Teacher (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Social Sciences › Education › Innovations in Medical Education
- Social Sciences › Education › Innovative Education and Learning Practices
- Social Sciences › Education › Adult and Continuing Education Topics
- Keywords
- experiential learning, situated learning, clinical teaching, medical students, residency training, continuing professional development, hands-on learning
- MeSH terms
- Clinical Clerkship, Clinical Competence, Humans, Internship and Residency, Psychology, Educational, Students, Medical, Models, Educational, Problem-Based Learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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