Exploration des facteurs influençant la mobilisation des savoirs par une pensée critique chez des étudiantes infirmières bachelières lors de stages cliniques
Bibliographic record
Abstract
To make an active contribution to human health, nurses must draw on a wide range of knowledge and skills. In view of the ever-growing complexity of care, the education of future nurses will face major issues and challenges. This study set out to characterize the knowledge mobilization process through critical thinking by undergraduate nursing students during care situations, and to better understand and support its development. A grounded theory-based qualitative approach identified certain factors that influence this process, through elucidation interviews with 16 Quebec university students. A socio-demographic questionnaire, semi-structured interviews and field notes were used to collect the data, from which two broad categories of influencing factors emerged: intrinsic and extrinsic. Intrinsic factors include the students' knowledge, caregiving experience, values, view of the nurse's role, and personality traits. However, most influencing factors seem to be extrinsic and beyond the students' control. This category includes the personal characteristics of various people with whom the students work during clinical practicum, as well as their behaviour toward the students (in particular the openness, trust, acceptance and collaboration shown to them). Factors emerged relating to the care situations themselves (i.e. assigned workload, stability of condition of the people under care, range and complexity of caregiving scenarios, etc.). In relation to the academic context, the supervisor/student ratio is another factor. Lastly, power issues also emerged, especially regarding the status of students, the expert status ascribed to supervisors and the care team, and the evaluation context. The study findings have opened up new avenues for developing education strategies to foster critical thinking among nursing students and put it to use in mobilizing their knowledge and skills. Support measures for supervisors who play a key role with students during their practicum also merit further research.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".