Bibliographic record
Abstract
Background: Child and adolescents growth and development knowledge is an essential part of Pediatric Nursing and it is also part of the nine essentials in Nursing Education. Although students find challenge to master this knowledge, limited literatures documented the knowledge deficit regarding child growth and development among nursing students. The purpose of this study was to assess senior nursing students’ knowledge about normal child growth and development before and after Pediatric Nursing didactic and clinical courses. Methods: A prospective, descriptive, pre-post study was conducted using a convenience sample of 125 senior nursing students who were attending Pediatric Nursing courses during the academic year of 2010-2011. Students who attended and completed both didactic and clinical courses were eligible for the study. The students were given a questionnaire that was developed by the investigators at the beginning of the semester and at the end. Results: Students’ age ranged from 21 to 24 years old with mean 22.00 (SD=0.8). The mean knowledge score of the pre-test was 17.6 (SD=3.29) (total is 28), while the mean knowledge score for the post-test was 19.00 (SD=2.76) at the end of the semester. Although there was a significant difference in the mean scores between the pre and post testing ( t = -3.04, p = 0.003), the students failed to achieve the 80% achievement rate in the post test. Conclusions: Students had weak knowledge scores regarding main concepts of child growth and development after the Pediatrics Courses. Creative strategies that improve students’ growth and development knowledge retention and demon- stration are needed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".