Using Learning Styles to Evaluate First-Year Pharmacy Students' Preferences Toward Different Activities Associated with the Problem-Based Learning Approach.
Bibliographic record
Abstract
The purpose of this study was to investigate whether a relationship existed between student learning styles and their preferences toward the various activities associated with the Problem-Based Learning (PBL) approach in the first-year pharmacy curriculum at the University of British Columbia. These PBL activities comprise group discussions, independent research, in-class critical-thinking and group report writing. In the fall semester of the 2000-2001 academic year, first-year pharmacy students completed Kolb's Learning Styles Inventory. Student preferences toward the various activities associated with the PBL tutorials were evaluated based upon the results of student surveys. Results from these surveys revealed that Divergers indicated the lowest preference overall for the activities associated with the PBL program in the first-year pharmacy curriculum compared to the other three learning style groups. Convergers showed strong preferences for these activities. While the Convergers and Divergers indicated opposing preferences overall for the activities associated with the PBL, the Assimilators and Accommodators indicated overall positive responses to the PBL activities. These findings may be used in future studies to evaluate whether student preferences for certain learning environments are correlated to their academic success as measured by grades.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".