Second‐Year Nursing Students’ Retention of Gross Anatomical Knowledge
Bibliographic record
Abstract
Human anatomy is a foundational course in nursing education, however, there is growing concern that students do not retain enough anatomical knowledge to successfully apply it in clinical settings. The aim of this study was to determine retention level of anatomy knowledge among second-year nursing students from their first-year anatomy class, and to determine if there is a difference in level of retention based on organ system. For each system, second-year students were asked to answer 9 to 11 multiple-choice questions (MCQs), and the scores from these quizzes were compared to matched test items from their first-year anatomy examinations. There was a significant decrease in the overall mean score from 83.05 ± 8.34 (±SD) in first year to 54.36 ±12.9 in second year (P = 0.0001). Retention levels were system specific. System-specific knowledge retention was highest for the gastrointestinal system (89.7%), respiratory system (88.5%), and genitourinary system (83.6%). This was followed by the integumentary system (80.1%), special senses (79.4%), nervous system (74.9%), and musculoskeletal system (69.3%). Retention was lowest for the lymphatic system (64.3%), cranial nerves (58.8%), vascular system (53.9%), and head and neck (42.6%). The present study shows that nursing students' anatomy knowledge retention was comparatively higher than rates reported by others in medical and allied-health students. The researchers are now investigating knowledge retention in third- and fourth-year nursing students. Further investigation into why retention is higher for specific systems and intervention strategies to improve knowledge acquisition and retention in nursing students is recommended.
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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 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".