Teaching in small portions dispersed over time enhances long-term knowledge retention
Bibliographic record
Abstract
BACKGROUND: A primary goal of education is to promote long-term knowledge storage and retrieval. OBJECTIVE: A prospective interventional study design was used to investigate our research question: Does a dispersed curriculum promote better short- and long-term retention over a massed course? METHODS: Participants included 20 gastroenterology residents from the University of Calgary (N = 10) and University of Toronto (N = 10). Participants completed a baseline test of nutrition knowledge. The nutrition course was imparted to University of Calgary residents for 4 h occurring 1 h weekly over 4 consecutive weeks: dispersed delivery (DD). At the University of Toronto the course was taught in one 4h academic half-day: massed delivery (MD). Post-curriculum tests were administered at 1 week and 3 months to assess knowledge retention. RESULTS: The baseline scores were 46.39 +/- 6.14% and 53.75 +/- 10.69% in the DD and MD groups, respectively. The 1 week post-test scores for the DD and MD groups were 81.67 +/- 8.57%, p < 0.001 and 78.75 +/- 4.43, p < 0.001 which was significantly higher than baseline. The 3-month score was significantly higher in the DD group, but not in the MD group (65.28 +/- 9.88%, p = 0.02 vs. 58.93 +/- 12.06%, p = 0.18). The absolute pre-test to 1-week post-test difference was significantly higher at 35.28 +/- 7.65% among participants in the DD group compared to 25.0 +/- 11.80% in the MD group, p = 0.048. Similarly, the absolute pre-test to 3-month post-test difference was significantly higher at 18.9 +/- 6.7% among the participants in the DD group, compared to 6.8 +/- 11.8% in the MD group, p = 0.021. CONCLUSIONS: Long-term nutrition knowledge is improved with DD compared with MD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 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; both teacher heads agree on what is shown here.
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".