Impact of preferred learning style on personal resilience strategies among pharmacy students during the COVID-19 pandemic
Bibliographic record
Abstract
Introduction: Using COVID-19 as the context, this study explored how differences in individual learning styles impacted personal resilience strategies among pharmacy students. This is a uniquely stressful period of time for many learners; pharmacy education has shifted predominantly to novel online forms of teaching, learning, and assessment, and traditional psycho-social support became difficult to access due to lock-down and quarantine requirements. Methods: Data were gathered throughout May and June 2020 via participant-observer, semi-structured interviews. Data analysis was performed using deductive analysis techniques, based on existing themes in resilience research. Results: A total of 21 pharmacy students were interviewed, the majority of whom had ‘Assimilator’ or ‘Converger’ dominant learning styles as classified by Austin’s Pharmacists’ Inventory of Learning Styles (PILS). Assimilators had a stronger sense of professional identity, practiced positive psychology, and utilised journaling as resilience strategies more frequently than Convergers. Convergers were found to be more self-efficacious and adaptable than Assimilators. Conclusions: Rather than providing ‘one-size-fits-all’ advice and programming to pharmacy students, there may be potential to improve resilience by incorporating tailored and specific strategies based on the dominant learning style of each individual student.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".