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Record W7029961297

Medical student curiosity and medical education: A descriptive study

2015· dissertation· en· W7029961297 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2015
Typedissertation
Languageen
FieldPsychology
TopicPsychological and Educational Research Studies
Canadian institutionsnot available
FundersMcGill University
KeywordsCuriosityConstruct (python library)TraitSample (material)Medical scienceState (computer science)Medical schoolConstruct validity
DOInot available

Abstract

fetched live from OpenAlex

It has been suggested that intellectual curiosity is important to the practice of medicine and to medical student learning. It has also been proposed that medical education may suppress rather than promote the curiosity of medical learners. Despite these claims, curiosity has not been empirically investigated in medical education. The purpose of this study was to explore the concept of curiosity, as it is manifested in medical students across undergraduate medical education. A cross-sectional design was employed in which medical students, in all four years of undergraduate training, completed the Melbourne Curiosity Inventory (MCI) as a measure of their state-trait epistemic (i.e., intellectual) curiosity. The psychometric properties of the MCI were monitored to ensure validity of use in this study context. State and trait epistemic curiosity were described, and a repeated measures ANOVA was used to compare students across year of training. The state-trait curiosity construct was found to be valid in this study context, and was reliably measured by the MCI. Four hundred and two out of 751 students completed the inventory (53.5%). Trait curiosity was significantly higher than state curiosity overall (M = 64.5, SD = 8.5 vs. M = 58.5, SD = 11.6, respectively) and within each year of training. Moreover, state curiosity was found to be particularly low in the sample of year-2 students. This study is the first to empirically investigate intellectual curiosity in medical education. The findings suggest the possibility that medical education may be suppressing rather than promoting the curiosity of medical students.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.825
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.059
GPT teacher head0.421
Teacher spread0.362 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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