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Alicia M. Chen; Andrew Palacci; Natalia Vélez; Robert D. Hawkins; Samuel J. Gershman – Cognitive Science, 2024
How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N…
Descriptors: Bayesian Statistics, Models, Teaching Methods, Evaluation
Tutku Öztel; Fuat Balci – Cognitive Science, 2024
One of the most prominent social influences on human decision making is conformity, which is even more prominent when the perceptual information is ambiguous. The Bayes optimal solution to this problem entails weighting the relative reliability of cognitive information and perceptual signals in constructing the percept from self-sourced/endogenous…
Descriptors: Bayesian Statistics, Computation, Social Influences, Decision Making