Beyond the classroom walls: Stakeholder experiences with remote instruction in Post RN baccalaureate nursing program during the COVID-19 pandemic: A qualitative inquiry
Bibliographic record
Abstract
The COVID-19 pandemic led to the closure of educational campuses and the suspension of conventional classroom teaching globally and locally, and many switched overnight to an online modality. The change was experienced differently by varied audiences, given the availability of resources. The study aimed to examine stakeholders' experiences of emergency remote instructions in the Post-RN Baccalaureate Nursing Program during the COVID-19 pandemic. A qualitative descriptive exploratory design with a purposive sampling technique was used at a private nursing university in Karachi, Pakistan. Focus group discussions with students and faculty were conducted separately, while in-depth interviews with key informants were held using semi-structured interview guides. The focus group discussions and in-depth interviews were recorded electronically and transcribed and translated, coded, and analysed manually. Findings uncovered two major themes. (a) Remote teaching and learning-a paradigm shift; and (b) Remote learning ecosystem-a challenging team sport. The first theme denotes a major shift in pedagogical approach migrating from blended learning model to a complete online modality. Theme two uncovers the efforts and teamwork of the various stakeholders who assisted in mitigating the challenges collaboratively when migrating to virtual learning environment. Findings suggest that to continue to thrive in the post-COVID world, faculty, students, and key informants must collegially enhance the teaching, learning, and assessment strategies and student-teacher interaction, capitalising on evidence-based practices, trial and error, multi-level support mechanisms, and partnerships. The study recommends building resilience in instructional and administrative infrastructure to prepare for future events like pandemics and suggests development of evidence-informed blended and online nursing programmes in the region.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".