Effect of using an audience response system on learning environment, motivation and long-term retention, during case-discussions in a large group of undergraduate veterinary clinical pharmacology students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Teaching methods that provide an opportunity for individual engagement and focussed feedback are required to create an active learning environment for case-based teaching in large groups. AIMS: A prospective observational controlled study was conducted to evaluate whether the use of an audience response system (ARS) would promote an active learning environment during case-based discussions in large groups, have an impact on student motivation and improve long-term retention. METHODS: Group A (N = 83) participated in large group case discussions where student participation was voluntary, while for group B (N = 86) an ARS was used. Data collection methods included student and teacher surveys, student focus group interviews, independent observations and 1-year post-course testing. RESULTS: Results indicated that the use of an ARS provided an active learning environment during case-based discussions in large groups by favouring engagement, observation and critical reflection and by increasing student and teacher motivation. Although final exam results were significantly improved in group B, long-term retention was not significantly different between groups. CONCLUSIONS: It was concluded that ARS use significantly improved the learning experience associated with case-based discussions in a large group of undergraduate students.
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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 | 0.023 | 0.003 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it