Timing's not everything: Immediate and delayed feedback are equally beneficial for performance in formative multiple‐choice testing
Bibliographic record
Abstract
INTRODUCTION: Test-enhanced learning (TEL) is an impactful teaching and learning strategy that prioritises active learner engagement through the process of regular testing and reviewing. While it is clear that meaningful feedback optimises the effects of TEL, the ideal timing of this feedback (i.e. immediate or delayed) in a medical education setting is unclear. METHOD: Forty-one second-year medical students were recruited from the University of Melbourne. Participants were given a multiple-choice question test with a mix of immediate (i.e. post-item) and delayed (i.e. post-item-block) conceptual feedback. Students were then tested on near and far transfer items during an immediate post-test, and at a one-week follow-up. RESULTS: A logistic mixed effects model was used to predict the probability of successful near and far transfer. As expected, participants in our study tended to score lower on far transfer items than they did on near transfer items. In addition, correct initial response on a parent question predicted subsequent correct responding. Contrary to our hypotheses, the feedback timing effect was non-significant-there was no discernible difference between feedback delivered immediately versus delayed feedback. DISCUSSION: The findings of this study suggest that the timing of feedback delivery (post-item versus post-item-block) does not influence the efficacy of TEL in this medical education setting. We therefore suggest that educators may consider practical factors when determining appropriate TEL feedback timing in their setting.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".