Effects of speech production training on memory across short and long delays in 5- and 6-year-olds: A pre-registered study
Bibliographic record
Abstract
Abstract Studies on the role of speech production on learning have found a memory benefit from production labeled the “Production Effect.” While research with adults has generally shown a robust memory advantage for produced words, children show more mixed results, and the advantage is affected by age, cognitive, and linguistic factors. With adults, the Production Effect is not restricted to the immediate context but is also found after a delay. So far, no studies have investigated the effect of delayed recall on the Production Effect with children. Children aged 5 and 6 years old (n = 60) participated in two sessions. Children were trained on familiar words and images, which were heard (Listen) or produced aloud (Say). Children then performed a free recall task. One week later, children repeated the recall task and an additional recognition task. At immediate testing, there was a recency effect on words recalled from the different training conditions and a recall advantage for words produced over words heard; however, this no longer held after a 1-week delay in either the recall or recognition task. Exploratory analysis showed that vocabulary did not predict the Production Effect. Findings indicate that unlike adults, the Production Effect is not as robust in children after a delay.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".