Student Perspectives on Challenges and Success in Experiential Pharmacy Education
Bibliographic record
Abstract
OBJECTIVE: Experiential education can be challenging, and academic and well-being difficulties may arise if students are not adequately supported. There is limited evidence that elucidates the depth and complexity of students' experiences during practicum. This study aims to understand students' challenges and support needs during the experiential education component of an Entry-to-Practice PharmD program. METHODS: Questionnaires with open- and close-ended questions were used in this cross-sectional study. Descriptive statistics were used to summarize quantitative data, while qualitative responses were analyzed using content analysis. RESULTS: Fifty-six students from program years 1 to 4 participated, with 23 (41%) experiencing challenges or a practicum course failure. Academic challenges were more common than health and well-being challenges during practicum, with difficulties in knowledge application and communication skills being the most common. Twenty-two students (39%) accessed at least 1 support resource, most frequently their preceptors for academic-related issues. Students wanted more help from the Faculty with synthesizing therapeutic and clinical knowledge, favoring virtual, asynchronous, and clinically relevant resources. Content analysis highlighted the need to enhance practicum resources and foster supportive learning environments, particularly in preceptor interactions. For health and well-being challenges, students most frequently relied on friends, family, and pharmacy peers for support. CONCLUSION: These findings underscore the need for a structured, student-centered approach to addressing challenges during practicum and provide recommendations and strategies to better support student satisfaction, performance, and well-being within the experiential component of an Entry-to-Practice PharmD program.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".