Evaluating student understanding of pharmacodynamics core concepts
Bibliographic record
Abstract
Pharmacodynamics is an essential subdiscipline of pharmacology that underpins safe and effective prescribing and therapeutic decision-making, as well as drug discovery and development. The exponential increase in the number of therapeutic drugs has prompted members of the pharmacology educator community to question existing pharmacology curricula focused on individual drugs and move toward a curriculum focused on conceptual understanding. A first step towards conceptual understanding is to establish what students currently know about pharmacodynamic core concepts. A total of 218 students from 10 universities were invited to complete a questionnaire that assessed their understanding of drug efficacy , drug-target interaction , drug tolerance , and structure-activity relationship . Pairs of pharmacology experts independently assessed each student’s response and flagged any misconceptions that arose. The experts then compared their evaluations, achieved a consensus decision, and grouped the misconceptions into themes. Less than 25% of students provided core concept meanings that fully aligned with those of the expert group. By contrast, more than 75% of students could apply the core concept to a novel scenario at least in part. Overall, 480 misconceptions were identified and grouped into 55 misconception themes. The concept of drug efficacy was the core concept with which students struggled most. It is unclear why students were better able to apply their knowledge than to define the core concepts, although this might reflect a focus on active learning in pharmacology courses globally. The deficits in defining and understanding pharmacodynamic core concepts, and the misconceptions revealed in student responses, can be used by educators to guide their efforts. • This study included 218 students across 6 countries and 10 universities. • Student conception and application of 4 pharmacodynamic core concepts were analysed. • Student conceptions of the core concepts varied widely from expert definitions, whilst performance on application tasks was slightly better. • Fifty-five misconception themes were coded from 480 instances. • Misconceptions relating to drug efficacy arose in questions relating to 3 concepts.
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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 | 0.006 | 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 | 0.001 | 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".