Bibliographic record
Abstract
Background: Current barriers to effective student evaluations in the clinical area are numerous and growing and new pedagogies need to be developed. We developed an educational pedagogy to aid in critical thinking for graduate and undergraduate nursing students in clinical areas that can replace or augment written care plans. Methods: Evaluate the effectiveness of the new ABC’s pedagogy (A=Anatomy/physiology, B=Best care, C=Complications, D=Drugs, E=Evidence based practice) for clinical teaching, using a 5 point Likert scale, for both graduate and undergraduate students and faculty through course evaluations. Results: Total undergraduate students (N = 37) evaluated the ABC’s pedagogy as follows; 98% rated as excellent and 2% very good. For graduate students (N= 8) 88% rated the ABC’s as excellent and 12% very good. Staff nurses and advanced practice nurse preceptors (N =17) rated the pedagogy as 88% excellent, 6% very good, and 6% neither good nor bad. Conclusions: The use of the ABC’s pedagogy in clinical care is a way to evaluate undergraduate and graduate students’ critical thinking, and to facilitate learning during practicum. It offers a systematic approach to replace written care plans includes the major benefit of real-time questions/answers between the professor/preceptor and students and incorporates evidence-based practice into individualized patient care. The ABC’s are one way to better prepare nursing students in areas of communication, critical thinking, providing care in clinical experiences, discussion of ethical and professional issues, as well as affording one-on-one time with the clinical preceptor/professor and promoting exponential learning in a pre- and post-conference environment.
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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 | 0.047 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".