Abstract
Everyone agrees that infants possess general mechanisms for learning about the world, but the existence and operation of more specialized mechanisms is controversial. One mechanism—rule learning—has been proposed as potentially specific to speech, based on findings that 7‐month‐olds can learn abstract repetition rules from spoken syllables (e.g. ABB patterns: wo‐fe‐fe, ga‐tu‐tu…) but not from closely matched stimuli, such as tones. Subsequent work has shown that learning of abstract patterns is not simply specific to speech. However, we still lack a parsimonious explanation to tie together the diverse, messy, and occasionally contradictory findings in that literature. We took two routes to creating a new profile of rule learning: meta‐analysis of 20 prior reports on infants’ learning of abstract repetition rules (including 1,318 infants in 63 experiments total), and an experiment on learning of such rules from a natural, non‐speech communicative signal. These complementary approaches revealed that infants were most likely to learn abstract patterns from meaningful stimuli. We argue that the ability to detect and generalize simple patterns supports learning across domains in infancy but chiefly when the signal is meaningfully relevant to infants’ experience with sounds, objects, language, and people.
Highlights
Just as scientists draw inferences by combing through disorderly data, so infants learn by sifting the most important information out of a noisy signal
While all modern theories of cognitive development agree that infants possess powerful general mechanisms for learning about the world (Csibra & Gergely, 2009; Doumas, Hummel, & Sandhofer, 2008; Endress & Bonatti, 2016; Frost, Armstrong, Siegelman, & Christiansen, 2015; Gopnik, 2012; Marcus, 2000; Romberg & Saffran, 2010; Saffran & Kirkham, 2017; Smith, Suanda, & Yu, 2014), the ways in which these mechanisms are narrowed and specialized, to focus on extracting the most vital information from different specific domains, is much more controversial
We can conclude that infants learn these abstract patterns more reliably from spoken syllables than from a variety of other stimuli: learning from syllables increased the size of the learning effect by g = 0.21
Summary
Just as scientists draw inferences by combing through disorderly data, so infants learn by sifting the most important information out of a noisy signal. How they achieve this is currently unclear. Alongside their domain general capacities, infants possess a set of learning mechanisms that are specialized for extracting information from and about very specific domains, such as language. Evidence for this comes from studies on how infants extract and generalize across regularities (Gerken, 2006; Marcus, 2000; Marcus, Vijayan, Bandi Rao & Vishton, 1999), including a prominent finding that such learning seems to be facilitated by speech. The topic of how infants learn these abstract patterns has since become a mainstay for developmental and cognitive science
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