Do Scores on Three Commonly Used Measures of Critical Thinking Correlate With Academic Success of Health Professions Trainees? A Systematic Review and Meta-analysis
Bibliographic record
Abstract
PURPOSE: To determine whether the three commonly used measures of critical thinking correlate with academic success of medical professionals in training. METHOD: The search for English-language articles (from 1980 to 2011) used Medline, Embase, Scopus, Cochrane Library on Ovid, Proquest Dissertations, Health and Psychosocial Instruments, PsychINFO, and references of included articles. Studies comparing critical thinking with academic success among medical professionals were included. Two authors performed study selection independently, with disagreement resolved by consensus. Two authors independently abstracted data on study characteristics, quality, and outcomes, with disagreement resolved by a third author. Critical thinking tests studied were the California Critical Thinking Skills Test (CCTST), California Critical Thinking Disposition Inventory (CCTDI), and Watson-Glaser Critical Thinking Appraisal. Correlation coefficients were pooled in meta-analysis. RESULTS: The search identified 557 studies: 52 met inclusion for systematic review, 41 of which were meta-analyzed. Critical thinking was positively correlated with academic success, r=0.31 (95% confidence intervals [CI] 0.26, 0.35), with a moderate statistical heterogeneity (I=67%). In subgroup analysis, only student type had statistical significance for correlation, although bias was likely due to low numbers for some student types. In direct comparison, using studies that employed two critical thinking tests, the CCTDI (r=0.23, 95% CI 0.15, 0.30) was significantly inferior (P<.001) to the CCTST (r=0.39, 95% CI 0.33, 0.45). CONCLUSIONS: Critical thinking was moderately correlated with academic success of medical professionals in training. The CCTDI was inferior to the CCTST in correlating with academic success.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.096 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.036 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".