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Updated: Nov 29, 2025

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Learning vocabulary and grammar from cross-situational statistics
Patrick Rebuschat1, Padraic Monaghan2, Christine Schoetensack3
1Lancaster University, UK; University of Tübingen, Germany.
Abstract:
Across multiple situations, child and adult learners are sensitive to co-occurrences between individual words and their referents in the environment, which provide a means by which the ambiguity of word-world mappings may be resolved (Monaghan & Mattock, 2012; Scott & Fisher, 2012; Smith & Yu, 2008; Yu & Smith, 2007). In three studies, we tested whether cross-situational learning is sufficiently powerful to support simultaneous learning the referents for words from multiple grammatical categories, a more realistic reflection of more complex natural language learning situations. In Experiment 1, adult learners heard sentences comprising nouns, verbs, adjectives, and grammatical markers indicating subject and object roles, and viewed a dynamic scene to which the sentence referred. In Experiments 2 and 3, we further increased the uncertainty of the referents by presenting two scenes alongside each sentence. In all studies, we found that cross-situational statistical learning was sufficiently powerful to facilitate acquisition of both vocabulary and grammar from complex sentence-to-scene correspondences, simulating the situations that more closely resemble the challenge facing the language learner.
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