Developing critical reflection for professional practice through problem‐based learning
Bibliographic record
Abstract
AIMS: To explore the influence of current learning traditions in nursing on the development of reflection and critical reflection as professional practice skills and to offer suggestions for nursing education that will specifically facilitate the development of critical reflection. ORGANIZATIONAL CONSTRUCTS: Mezirow's transformative learning theory, Barrows conceptualization of problem-based learning (PBL). METHODS: Integrative literature review of published literature related to nursing, health science education and professional education from 1983-2000. FINDINGS: Professional education scholars concur that specialized knowledge is clearly essential for professional practice, however, they also suggest that self-consciousness (reflection) and continual self-critique (critical reflection) are crucial to continued competence. While strategies to facilitate reflection have been outlined in the literature, specific strategies to facilitate the development of critical reflection and implications for nursing education are much less clear. Advocates of reflective and critically reflective practice suggest that the development of these abilities should be inextricably linked to professional development and can be developed through active repeated guided practice. In health care, PBL based on constructivism, has been identified as one way to facilitate the development of these skills. CONCLUSIONS: Nursing learners exposed to PBL develop the ability to be reflective and critically reflective in their learning and acquire the knowledge and skill within the discipline of nursing by encountering key professional practice situations as the stimulus and focus of their classroom learning. The learners' ability to be both reflective and critically reflective in their learning is developed by critical questioning of the faculty tutor during situational analysis, learning need determination, application of knowledge, critique of resources and personal problem-solving processes, and summarization of what was learned.
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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 | 0.026 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".