Addressing the Challenges of Precepting Students Enrolled in Remote Research Advanced Pharmacy Practice Experiences
Bibliographic record
Abstract
As a result of restrictions imposed by COVID-19, many researchers have responded to the call for remote, advanced pharmacy practice experiences (APPEs) that do not involve direct patient care. The influx of materials on online pedagogy may be difficult for new preceptors to digest while familiarizing themselves with the APPE program. To complement the available guidance on remote learning for new preceptors, we describe our experiences with implementing a remote, research-focused APPE during COVID-19. Common challenges are discussed and potential solutions that may help new preceptors anticipate and overcome barriers to achieving the educational outcomes of research-focused APPE are proposed.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.012 | 0.019 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".