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• W2952209611 abstract "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? Here we investigate the cognitive underpinnings of the human ability to prioritize what to teach. We present a computational model that decides what to teach by maximizing the learner’s expected utility of learning from instruction and from exploration, and we show that children (aged 5–7 years) make decisions that are consistent with the model’s predictions (that is, minimizing the learner’s costs and maximizing the rewards). Children flexibly considered either the learner’s utility or their own, depending on the context, and even considered costs they had not personally experienced, to decide what to teach. These results suggest that utility-based reasoning may play an important role in curating cultural knowledge by supporting selective transmission of high-utility information. Bridgers et al. combine computational modelling and developmental experiments to show that even young children reason about others’ costs and rewards to make utility-maximizing decisions about what to teach and what to let learners discover on their own." @default.
• W2952209611 created "2019-06-27" @default.
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• W2952209611 date "2019-10-14" @default.
• W2952209611 modified "2023-10-14" @default.
• W2952209611 title "Young children consider the expected utility of others’ learning to decide what to teach" @default.
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• W2952209611 doi "https://doi.org/10.1038/s41562-019-0748-6" @default.
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