Disposición, habilidades del pensamiento crítico y éxito académico en estudiantes universitarios: metaanálisis
Bibliographic record
Abstract
Introduction: critical thinking is among the main soft skills related to academic success and highly demanded in the workplace. The objective was to make a meta-analysis of observational studies on the relationship between disposition, critical thinking skills and academic success in university students. Methods: a systematic review with meta-analysis of random effects following the guidelines for observational studies. Searches were conducted using MEDLINE, EMBASE, Scopus and Cochrane Library. The methodological quality was evaluated with the Newcastle-Ottawa Scale version. Heterogeneity was estimated, Cochran's Q test was used, the publication bias with the funnel plot and Begg’s test. Were performed sensitivity analyzes and forest plot diagrams. Results: 6756 studies were identified, 32 corresponded to the inclusion criteria with 4962 participants, 30 were meta-analyzed. Critical thinking and academic success were positively correlated: r=.26 (CI: 95%; .18-.34) (p=.00), with a high statistical heterogeneity (I2=86.5%). In the subgroup analysis, significant differences were observed for the following moderators: specialty Q=42.86 (p=.00), number of dimensions Q=31.83 (p=.00), instruments Q=56.01 (p=.00), dimensions evaluated Q=25.09 (p=.00). Discussion: the magnitude of the correlation was weak and affected by moderators such as the study specialty, the instrument used, the evaluation of skills versus dispositions and the number of dimensions evaluated.
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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 | 0.061 | 0.139 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.032 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".