Shifts in learning dynamics drive developmental improvements in the acquisition of structured knowledge

Children are adept statistical learners, capable of parsing streams of structured input into meaningful units, but the explicit knowledge of environmental structure that they acquire through experience often differs from that of adults. To date, however, it is unclear how developmental changes in learning mechanisms influence structured knowledge acquisition. To address this question, we tested 110 children, adolescents, and adults, ages 8 - 22 years, on a predictive learning task, in which they experienced sequences of stimuli with a higher-order temporal structure. After an initial learning phase, participants’ explicit knowledge of the relations between stimuli was probed via two additional task measures. We used a recently introduced computational model to characterize participants’ response times during learning, and found that all participants relied on simple, recency-based prediction, anticipating that they would encounter stimuli they recently encountered in the past. With increasing age, however, participants demonstrated greater evidence of additionally relying on a more sophisticated learning mechanism, which captured a predictive representation of the contingent relations between stimuli. The extent to which participants demonstrated evidence of this more complex form of predictive learning related to — and accounted for age-related improvements in — their explicit knowledge of the task’s underlying structure. Our results suggest that age-related changes in the use of different predictive learning mechanisms influences the structured knowledge that people derive from experience, providing an account for why children, adolescents, and adults form different representations of their environments from identical streams of experiences.