Developing future nurse educators through peer mentoring
Bibliographic record
Abstract
Patricia A Rosenau, Rita F Lisella, Tracey L Clancy, Lorelli S NowellFaculty of Nursing, University of Calgary, Calgary, AB, CanadaBackground: The nursing workforce and nursing education demographic trends reinforce the urgency to cultivate future nursing leaders, educators, and mentors. The changing realities of health care environments, involving crowded student placements, overtaxed clinical mentors and preceptors, and inexperienced staff, hamper student learning and professional development. Peer mentoring has been used successfully in nursing education to enhance student engagement and the quality of the student learning experience. Although various terms like peer mentor have been used to describe the role of senior students facilitating junior student learning, the literature is silent about how peer mentoring fosters the development of future nursing education leaders.Objectives: The aim of this study was to understand how peer mentorship fosters the development of nursing education leadership in senior undergraduate nursing students enrolled in an elective undergraduate peer-mentoring credit course, Introductory Concepts in Nursing Education and Leadership Through Peer-Led Learning.Design and method: This phenomenological study explored the development of nursing education leadership in senior undergraduate students through the analysis of critical reflections of individual senior students and online discussions between triads of senior students teaching/learning across diverse junior-level theory and practice courses.Participants: Seventeen senior undergraduate nursing students enrolled in the elective course participated in the study.Results: From the critical reflections and online discussions, four themes emerged: "developing teaching philosophies and pedagogies", "learning teaching strategies", "supportive peer relationship", and "benefits of the peer mentorship program".Conclusion: The creation and promotion of peer leadership opportunities provide peer-to-peer learning opportunities and increase leadership and teaching skills of senior nursing students. In the long term, successful peer leadership programs have the potential to benefit individuals outside of the mentorship relationship including peer leaders' future peers and coworkers, their clients or patients, and eventually their own students as they become nurse educators of the future.Keywords: nursing education, peer mentorship, qualitative study, nursing students
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".