Testing a Framework of Environmental Adaptation in Children's Learning Strategies

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PI/PD: Katherine Adams Shannon PROJECT SUMMARY How do children learn within their early social environments? An important factor in social learning is the responsiveness or reliability of help from social partners. Children who experience unresponsive or inconsistent caregiving may often have their bids for help go unanswered; other children may experience different social partners who vary in their helpfulness. Despite its ramifications for long-term learning outcomes, we still understand little about how young children adapt their learning strategies as a function of the reliability of help in their social environments, and how such adaptations shape learning outcomes. The goal of the current proposal is to develop and test a framework that describes environmental adaptation in children’s learning strategies. In a series of experiments with 4- to 6-year-olds, we start with a simple design that operationalizes ‘reliability of help’ as whether or not a social partner consistently responds to or ignores bids for help before children complete a learning task (e.g., figure out how a toy works). Within this experimental setting, we address 3 specific aims: In Aim 1, we ask if children adapt their (1) learning goals and (2) decisions to explore alone or seek help based on the past helpfulness of a social partner, and if so, whether these adaptations maximize learning outcomes given the likelihood of receiving help. A given behavior is adaptive if it benefits learning in one social environment, but the same behavior can lead to costs in another. It follows that a beneficial learning adaptation can become maladaptive if the conditions of the environment change. In Aim 2, we introduce a reliable-to-unreliable and unreliable-to-reliable change in the reliability of help, such that a social partner who was helpful before learning stops responding to children’s bids for help (and vice versa). Here, we test whether an environmental change can lead children to use mismatched learning strategies that, in turn, lead to suboptimal learning outcomes. In Aim 3, we construct a computational model that describes environmental adaptation in children’s learning strategies according to the principles of utility-based social reasoning, wherein children consider the behavior of their social partners to maximize the expected utility (i.e., benefits net of costs) of a given learning decision. We test model predictions against children’s behavior in the experiments. Taken together, this work will provide key empirical data and a computational model to advance our understanding of how children learn within diverse social contexts. The long-term objective of this proposal is to generate novel insights into the ways in which children, particularly those who live in less supportive environments, make decisions during social learning that shape their future learning outcomes. Findings have promise to inform interventions that improve social learning interactions as a means to support early education.