Developing Leadership Practices in Hospital-Based Nurse Educators in an Online Learning Community
Bibliographic record
Abstract
Hospital-based nurse educators are in a prime position to mentor future nurse leaders; however, they need to first develop their own leadership practices. The goal was to establish a learning community where hospital-based nurse educators could develop their own nursing leadership practices within an online environment that included teaching, cognitive, and social presence. Using a pretest/posttest-only nonexperimental design, 35 nurse educators from three Canadian provinces engaged in a 12-week online learning community via a wiki where they learned about exemplary leadership practices and then shared stories about their own leadership practices. Nurse educators significantly increased their own perceived leadership practices after participation in the online community, and teaching, cognitive, and social presence was determined to be present in the online community. It was concluded that leadership development can be enhanced in an online learning community using a structured curriculum, multimedia presentations, and the sharing and analysis of leadership stories. Educators who participated should now be better equipped to role model exemplary leadership practices and mentor our nurse leaders of the future.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".