Theory and Practice in the Design and Conduct of Graduate Medical Education
Bibliographic record
Abstract
Medical education practice is more often the result of tradition, ritual, culture, and history than of any easily expressed theoretical or conceptual framework. The authors explain the importance and nature of the role of theory in the design and conduct of graduate medical education. They outline three groups of theories relevant to graduate medical education: bioscience theories, learning theories, and sociocultural theories. Bioscience theories are familiar to many medical educators but are often misperceived as truths rather than theories. Theories from such disciplines as neuroscience, kinesiology, and cognitive psychology offer insights into areas such as memory formation, motor skills acquisition, diagnostic decision making, and instructional design. Learning theories, primarily emerging from psychology and education, are also popular within medical education. Although widely employed, not all learning theories have robust evidence bases. Nonetheless, many important notions within medical education are derived from learning theories, including self-monitoring, legitimate peripheral participation, and simulation design enabling sustained deliberate practice. Sociocultural theories, which are common in the wider education literature but have been largely overlooked within medical education, are inherently concerned with contexts and systems and provide lenses that selectively highlight different aspects of medical education. They challenge educators to reconceptualize the goals of medical education, to illuminate maladaptive processes, and to untangle problems such as career choice, interprofessional communication, and the hidden curriculum.Theories make visible existing problems and enable educators to ask new and important questions. The authors encourage medical educators to gain greater understanding of theories that guide their educational practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".