Effectiveness of Problem-Based Learning on Development of Nursing Students’ Critical Thinking Skills
Bibliographic record
Abstract
BACKGROUND: Problem-based learning (PBL) is a student-centered approach to teaching that has been applied in medical and nursing education. The effectiveness of PBL in promoting critical thinking in nursing students has been studied extensively with mixed results. PURPOSE: The meta-analysis aimed to investigate the impact of PBL interventions on critical thinking skills of nursing students. METHODS: PubMed, Embase, Cochrane, and CINAHL databases were electronically searched. Methodological quality was examined using the Newcastle-Ottawa Scale and version 2 of the Cochrane risk-of-bias tool. Data were analyzed with 95% confidence intervals based on random-effect models. RESULTS: Nineteen studies involving 1996 nursing students were included in the analysis. The results of the analysis demonstrated greater improvement in critical thinking skills compared with the control group (overall critical thinking scores: standardized mean difference [SMD] = 0.47, 95% CI = 0.33-0.61, P < .01). CONCLUSIONS: The meta-analysis indicates that PBL can help nursing students to improve their critical thinking.
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 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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.012 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".