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How do children infer the meaning of a novel verb? One prominent proposal is that children rely on syntactic information in the linguistic context, a phenomenon known as "syntactic bootstrapping". For example, given the sentence "The bunny is gorping the duck," a child could use knowledge of English syntactic roles to infer that "gorping" refers to an action where the bunny is acting in some way on a duck. Here, we examine the strength of the syntactic bootstrapping effect, its developmental trajectory and generalizability using meta-analytic methods. Across 60 experiments in the literature (N = 849 participants), we find a reliable syntactic bootstrapping effect (d = 0.24). Yet, despite its theoretical prominence, the syntactic bootstrapping effect is relatively small, comparable in size to cross-situational learning and sound symbolism, but smaller than mutual-exclusivity and gaze-following. Further, we find that the effect does not strengthen over development, and is present only for studies that use transitive sentences. An examination of a range of methodological factors suggests that the effect is not strongly influenced by methodological implementation. In the General Discussion, we consider implications of our findings for theories of verb learning and make recommendations for future research.

Previous work suggests that key factors for replicability, a necessary feature for theory building, include statistical power and appropriate research planning. These factors are examined by analyzing a collection of 12 standardized meta-analyses on language development between birth and 5 years. With a median effect size of Cohen's d = 0.45 and typical sample size of 18 participants, most research is underpowered (range = 6%-99%; median = 44%); and calculating power based on seminal publications is not a suitable strategy. Method choice can be improved, as shown in analyses on exclusion rates and effect size as a function of method. The article ends with a discussion on how to increase replicability in both language acquisition studies specifically and developmental research more generally.

Young children acquire a wide range of linguistic and cognitive skills in the first three years of life. Decades of experimental work have established a solid empirical foundation for our understanding of cognitive development. But most experimental studies are limited in statistical power and focus on specific psychological constructs, thus making them unsuitable for describing developmental growth at scale. Here, we turned to meta-analyses of experimental research. We conducted a meta-meta-analysis to consolidate and integrate 23 meta-analyses compiled on MetaLab, a community-augmented meta-analysis platform. We found that most datasets can not meaningfully distinguish different functional forms for developmental change, but in those that could, there is great diversity in the best-fitting functional forms of the age model. We also evaluated the impact of a range of methodological factors. Overall, our work sheds light on the heterogeneous nature of developmental trajectories and the subtle interactions between research methods and experimental outcomes.

The ability to rapidly recognize words and link them to referents is central to children's early language development. This ability, often called word recognition in the developmental literature, is typically studied in the looking-while-listening paradigm, which measures infants' fixation on a target object (vs. a distractor) after hearing a target label. We present a large-scale, open database of infant and toddler eye-tracking data from looking-while-listening tasks. The goal of this effort is to address theoretical and methodological challenges in measuring vocabulary development. We first present how we created the database, its features and structure, and associated tools for processing and accessing infant eye-tracking datasets. Using these tools, we then work through two illustrative examples to show how researchers can use Peekbank to interrogate theoretical and methodological questions about children's developing word recognition ability. [ABSTRACT FROM AUTHOR]

We investigated how gender is represented in children's books using a novel 200,000-word corpus comprising 247 popular, contemporary books for young children. Using adult human judgments and word co-occurrence data, we quantified gender biases of words in individual books and in the whole corpus. We found that children's books contain many words that adults judge as gendered. Semantic analyses based on co-occurrence data yielded word clusters related to gender stereotypes (e.g., feminine: emotions; masculine: tools). Co-occurrence data also indicated that many books instantiate gender stereotypes identified in other research (e.g., girls are better at reading, and boys are better at math). Finally, we used large-scale data to estimate the gender distribution of the audience for individual books, and we found that children are more often exposed to stereotypes for their own gender. Together, the data suggest that children's books may be an early source of gender associations and stereotypes. [ABSTRACT FROM AUTHOR]