Tracking Clinical Judgment Development in Clinical Education With the Lasater Clinical Judgment Rubric
Bibliographic record
Abstract
BACKGROUND: Clinical judgment is essential to safe nursing practice, yet limited research has examined how it can be consistently assessed in clinical education. PURPOSE: This study explored the use of the Lasater Clinical Judgment Rubric (LCJR) to assess clinical judgment in prelicensure nursing students during clinical experiences, with simulation data included as a comparator. METHODS: A longitudinal cohort study followed 53 students across 4 semesters. Students were evaluated 35 times in clinical and simulation using the LCJR. RESULTS: Correlations between clinical and simulation scores were strong in Semester 1 but weak thereafter. LCJR scores in clinical experiences increased significantly across semesters, with the largest gains between Semesters 2 and 3. CONCLUSION: The LCJR demonstrated sensitivity to developmental change in clinical experiences, supporting its potential as a standardized tool for longitudinal evaluation. Simulation provided a useful point of comparison, highlighting differences in how judgment is expressed and assessed across learning environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".