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Record W2115997868 · doi:10.1002/chp.1340220202

Thinking about learning: Implications for principle-based professional education

2002· review· en· W2115997868 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Continuing Education in the Health Professions · 2002
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsObservational learningFacilitationExperiential learningLearning sciencesPerspective (graphical)Open learningPsychologyCognitionContext (archaeology)Situated cognitionActive learning (machine learning)Collaborative learningProfessional learning communityLearning environmentCooperative learningKnowledge managementPedagogyTeaching methodComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The understanding of teaching and learning in medical education has increased to improve medical education at all levels. Selected approaches to understanding learning provide a basis for eliciting principles that may inform and guide educational practice. In this article, these approaches are discussed from two perspectives: the cognitive and the environmental. The cognitive perspective includes activation of prior knowledge, elaboration of new learning, learning in context, transfer of learning, and organization of knowledge. The environmental perspective includes the dynamic interaction of learners with their environment, observational learning, incentives and rewards in the environment, goal setting and self-monitoring, self-efficacy, and situated learning. Implications are presented for facilitation of effective learning and support of the learning environment throughout the continuum of medical education.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.518
Teacher spread0.439 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it