Do Children (and Adults) Benefit From a Prediction Error Boost in One-Shot Word Learning?
Chiara Gambi; Jaroslaw R. Lelonkiewicz; Davide Crepaldi · 2024 · Journal of Cognition
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Influential theories and computational models suggest error-based learning plays an important role in language acquisition: Children learn new words by generating predictions about upcoming utterances and revising those predictions when they are erroneous. Critically, revising stronger (rather than weaker) predictions should further enhance learning. Although previously demonstrated in adults, such prediction error boost has not been conclusively shown in children. To close this gap, we tested 107 participants between the ages of 5 and 10. We found little evidence that word learning in this ag
Abstract by Chiara Gambi; Jaroslaw R. Lelonkiewicz; Davide Crepaldi, Journal of Cognition (2024) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.5334/joc.342