A Comprehensive Examination of Prediction-Based Error as a Mechanism for Syntactic Development: Evidence From Syntactic Priming.
Cogn Sci
; 48(4): e13431, 2024 04.
Article
en En
| MEDLINE
| ID: mdl-38622981
ABSTRACT
Prediction-based accounts of language acquisition have the potential to explain several different effects in child language acquisition and adult language processing. However, evidence regarding the developmental predictions of such accounts is mixed. Here, we consider several predictions of these accounts in two large-scale developmental studies of syntactic priming of the English dative alternation. Study 1 was a cross-sectional study (N = 140) of children aged 3-9 years, in which we found strong evidence of abstract priming and the lexical boost, but little evidence that either effect was moderated by age. We found weak evidence for a prime surprisal effect; however, exploratory analyses revealed a protracted developmental trajectory for verb-structure biases, providing an explanation as for why prime surprisal effects are more elusive in developmental populations. In a longitudinal study (N = 102) of children in tightly controlled age bands at 42, 48, and 54 months, we found priming effects emerged on trials with verb overlap early but did not observe clear evidence of priming on trials without verb overlap until 54 months. There was no evidence of a prime surprisal effect at any time point and none of the effects were moderated by age. The results relating to the emergence of the abstract priming and lexical boost effects are consistent with prediction-based models, while the absence of age-related effects appears to reflect the structure-specific challenges the dative presents to English-acquiring children. Overall, our complex pattern of findings demonstrates the value of developmental data sets in testing psycholinguistic theory.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Psicolingüística
/
Lenguaje
Límite:
Adult
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Child
/
Humans
Idioma:
En
Revista:
Cogn Sci
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Estados Unidos