An Online, Self-directed Pharmacy Bridging Course for Incoming First-Year Students
Bibliographic record
Abstract
Objective. To evaluate the short-term effectiveness of an online bridging course to increase the knowledge of struggling incoming students’ in crucial content areas within the Doctor of Pharmacy (PharmD) curriculum. Methods. An assessment was administered to all incoming first-year pharmacy students (N=180) during orientation to determine their foundational knowledge in key areas. Students who scored <70% on the assessment (N=137) were instructed to complete a 10-module, online, self-directed bridging course focusing on physiology, biochemistry, math, and medical terminology during the first two weeks of the quarter to prepare them for first-quarter coursework. After completing the bridging course, participants completed the same assessment to determine content knowledge acquisition and retention. At the end of the quarter, the assessment was again administered to all first-year students, regardless of whether they had completed the bridging course. Results. The average assessment score of students who completed the bridging course modules improved significantly (53% vs 76%). All students demonstrated significant improvement in assessment scores between orientation and the end of the quarter; however, bridging course participants achieved a greater increase in assessment scores (53% vs 73%) than nonparticipants (76% vs 81%). Significant relationships were found between assessment scores following completion of the bridging course and pass rates in first-quarter courses. Conclusion. The online, self-directed bridging course offered at Midwestern University, Chicago College of Pharmacy proved successful as a method of knowledge acquisition and as a system for early identification (within the first two weeks of the quarter) of students in need of additional academic support.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".