Ethical Considerations for Children Undergoing Surgery: Evaluation of Graduate Nursing Students’ Learning
Bibliographic record
Abstract
Background: To challenge dominant conceptions of children and innovate nursing education, our team created an open-access training module (https://childsxethics.net/) addressing ethical considerations for children undergoing surgery. Objective: To evaluate the level of Bloom’s Taxonomy cognitive, affective, and psychomotor learning reached by graduate nursing students after completing the training module. Methods: A qualitative descriptive study was conducted using Bloom’s Taxonomy. Data sources comprised of participants’ course assignments. Results: Participants (n=19) wrote 19 online reflections, 43 peer responses and completed two group assignments. The module and associated class assignments promoted high levels of cognitive and affective learning. The type of assignment influenced participants’ levels of learning. Cognitive and affective learning processes were enhanced when integrating reflections and fostering interactions among learners. Implications: Study findings will inform future iterations of the training module. Our innovative educational resource will facilitate the recognition of children as active moral agents and improve their surgical experiences.
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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 | 0.030 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".