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 age group benefits from a prediction error boost. Moreover, we also failed to replicate previous evidence for such an effect in adults. Based on a detailed task analysis, we suggest the variation in adult findings may be partly explained by differences in encoding strategies and that, relatedly, the protracted development of the episodic memory system might explain why children do not experience robust benefits from having stronger (rather than weaker) predictions disconfirmed.
Reference54 articles.
1. Learning to predict and predicting to learn: Before and beyond the syntactic bootstrapper;Language acquisition,2022
2. Fitting linear mixed-effects models using lme4;Journal of Statistical Software,2015
3. Learning to use words: Event-related potentials index single-shot contextual word learning;Cognition,2010
4. Being proven wrong elicits learning in children–but only in those with higher executive function skills;Developmental science,2019
5. The effect of unsuccessful retrieval on children’s subsequent learning;Journal of Experimental Child Psychology,2018