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Category: Project

Description: Humans learn from their own experience, but they also learn a great deal from others. Direct instruction facilitates learning without the costs of exploration, yet teachers must be selective because not everything can nor needs to be taught. How do we decide what to teach, and what to leave for learners to discover? By combining developmental experiments and computational modeling, we examine the cognitive underpinnings of how we decide what to teach, and what to let others discover on their own. We find that young children make teaching decisions that balance the benefits of social learning and the costs of exploration. Given a choice between two causal devices that they could teach to a learner (leaving the other for the learner to explore), children made decisions that (1) increased the learner's expected rewards (i.e., teaching the device that yields a more enjoyable effect), and (2) decreased the learner's expected costs (i.e., teaching the device that would be harder to figure out by oneself). These decisions are consistent with a computational model that maximizes the learner's expected utility (difference between rewards and costs) of learning from instruction and from exploration. Further experiments show that children consider either the learner's utility or their own depending on the context, and even consider costs they have not personally experienced to decide what is best to teach. These results highlight the richness of early social reasoning and how it supports selective transmission of information that is critical to successful cultural learning.