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Record W2970167379 · doi:10.1111/medu.13872

Critical thinking, biases and dual processing: The enduring myth of generalisable skills

2019· review· en· W2970167379 on OpenAlexaff
Sandra Monteiro, Jonathan Sherbino, Matthew Sibbald, Geoff Norman

Bibliographic record

VenueMedical Education · 2019
Typereview
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsPsychologyMythologyContext (archaeology)Cognitive skillPopularityCritical thinkingCognitionMedical educationPedagogySocial psychologyMedicine

Abstract

fetched live from OpenAlex

CONTEXT: The myth of generalisable thinking skills in medical education is gaining popularity once again. The implications are significant as medical educators decide on how best to use limited resources to prepare trainees for safe medical practice. This myth-busting critical review cautions against the proliferation of curricular interventions based on the acquisition of generalisable skills. STRUCTURE: This paper begins by examining the recent history of general thinking skills, as defined by research in cognitive psychology and medical education. We describe three distinct epochs: (a) the Renaissance, which marked the beginning of cognitive psychology as a discipline in the 1960s and 1970s and was paralleled by educational reforms in medical education focused on problem solving and problem-based learning; (b) the Enlightenment, when an accumulation of evidence in psychology and in medical education cast doubt on the assumption of general reasoning or problem-solving skill and shifted the focus to consideration of the role of knowledge in expert clinical performance; and (c) the Counter-Enlightenment, in the current time, when the notion of general thinking skills has reappeared under different guises, but the fundamental problems related to lack of generality of skills and centrality of knowledge remain. CONCLUSIONS: The myth of general thinking skills persists, despite the lack of evidence. Progress in medical education is more likely to arise from devising strategies to improve the breadth and depth of experiential knowledge.

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 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)0.001
metaresearch head score (Gemma)0.215
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.215
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.455
Teacher spread0.385 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations89
Published2019
Admission routes1
Has abstractyes

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