Nursing education during a pandemic: Perspectives of students and faculty
Bibliographic record
Abstract
Purpose: Nurses working on the frontlines of the COVID-19 pandemic have experienced a combination of physical, psychological, logistical, professional, and personal challenges. Those nurses enrolled in baccalaureate and graduate nursing degree programs were affected significantly in their ability to remain focused on meeting course expectations while contending with pandemic-induced challenges. Nursing faculty in a public state-based university school of nursing in upstate New York responded by developing initiatives to support students and foster their success.Results: Supported by unsolicited anecdotal reports, this article describes the experiences and perspectives of nurses in clinical roles working in a pandemic epicenter, while simultaneously completing nursing degree programs. Students were confronted by professional and personal stressors that challenged their ability to manage multiple responsibilities. Faculty supported students with intensive caring and communication, and by selective strategic policy and pedagogical adaptations, while adhering to and preserving program integrity and standards. These four distinct efforts supported student retention and success, and created opportunities for faculty dialogue, assessment, and reflection upon the nature of the changes and plans for future implementation. Self-care was identified as an important coping strategy for both students and faculty.Conclusions: Faculty believe the four-pronged approach enabled students to succeed in their programs of study and feel supported as individuals and professionals. Despite the continuing global health crisis, there have been numerous positive outcomes and lessons learned by both students and faculty while learning and teaching during the pandemic, with implications for future curricular and pedagogical approaches.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".