Development of Gerontological Learning Objectives to Enhance Nursing Educational Curricula
Bibliographic record
Abstract
Background: Many nursing schools are challenged to provide adequate gerontological education to students despite the enormous benefits to students' careers and society. This project developed student learning objectives to be used by nursing faculty to facilitate enriched gerontology courses and program curricula. Method: The project team drafted a comprehensive list of nursing student learning objectives based on the 2020 Canadian Gerontological Nursing Association Standards of Practice and Competencies and included relevant supportive references. Subsequently, 20 gerontological nurse experts reviewed the learning objectives through a modified Delphi process via online Qualtrics surveys (two rounds). Results: A total of 176 learning objectives were rated in round one for importance, measurability, feasibility, and interpretability; these were amalgamated to 47 learning objectives for review in round two. Conclusion: Thirty-three learning objectives were identified and validated that can be used by nursing schools to offer increased opportunities for gerontological learning. [ J Nurs Educ . 2024;63(4):256–260.]
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".