Unknown

Dataset Information

0

Capturing the Heterogeneity of Word Learners by Analyzing Persons.


ABSTRACT: Accurately capturing children's word learning abilities is critical for advancing our understanding of language development. Researchers have demonstrated that utilizing more complex statistical methods, such as mixed-effects regression and hierarchical linear modeling, can lead to a more complete understanding of the variability observed within children's word learning abilities. In the current paper, we demonstrate how a person-centered approach to data analysis can provide additional insights into the heterogeneity of word learning ability among children while also aiding researchers' efforts to draw individual-level conclusions. Using previously published data with 32 typically developing and 32 late-talking infants who completed a novel noun generalization (NNG) task to assess word learning biases (i.e., shape and material biases), we compare this person-centered method to three traditional statistical approaches: (1) a t-test against chance, (2) an analysis of variance (ANOVA), and (3) a mixed-effects regression. With each comparison, we present a novel question raised by the person-centered approach and show how results from the corresponding analyses can lead to greater nuance in our understanding of children's word learning capabilities. Person-centered methods, then, are shown to be valuable tools that should be added to the growing body of sophisticated statistical procedures used by modern researchers.

SUBMITTER: Jones IT 

PROVIDER: S-EPMC11351650 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

Capturing the Heterogeneity of Word Learners by Analyzing Persons.

Jones Ian T IT   Kucker Sarah C SC   Perry Lynn K LK   Grice James W JW  

Behavioral sciences (Basel, Switzerland) 20240813 8


Accurately capturing children's word learning abilities is critical for advancing our understanding of language development. Researchers have demonstrated that utilizing more complex statistical methods, such as mixed-effects regression and hierarchical linear modeling, can lead to a more complete understanding of the variability observed within children's word learning abilities. In the current paper, we demonstrate how a person-centered approach to data analysis can provide additional insights  ...[more]

Similar Datasets

| S-EPMC10623303 | biostudies-literature
| PRJEB52191 | ENA
| S-EPMC4146386 | biostudies-literature
| S-EPMC7872330 | biostudies-literature
| S-EPMC6839140 | biostudies-literature
| S-EPMC9335955 | biostudies-literature
| S-EPMC10203786 | biostudies-literature
| S-EPMC9371105 | biostudies-literature
| S-EPMC6215657 | biostudies-literature
| S-EPMC1994707 | biostudies-literature