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  1. Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search.Vincenzo Crupi, Jonathan D. Nelson, Björn Meder, Gustavo Cevolani & Katya Tentori - 2018 - Cognitive Science 42 (5):1410-1456.
    Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the (...)
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  • Active inductive inference in children and adults: A constructivist perspective.Neil R. Bramley & Fei Xu - 2023 - Cognition 238 (C):105471.
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  • Opacity, obscurity, and the geometry of question-asking.Christina Boyce-Jacino & Simon DeDeo - 2020 - Cognition 196 (C):104071.
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  • Effects of explanation on children’s question asking.Azzurra Ruggeri, Fei Xu & Tania Lombrozo - 2019 - Cognition 191 (C):103966.
    The capacity to search for information effectively by asking informative questions is crucial for self-directed learning and develops throughout the preschool years and beyond. We tested the hypothesis that explaining observations in a given domain prepares children to ask more informative questions in that domain, and that it does so by promoting the identification of features that apply to multiple objects, thus supporting more effective questions. Across two experiments, 4- to 7-year-old children (N = 168) were prompted to explain observed (...)
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  • The Efficiency of Question‐Asking Strategies in a Real‐World Visual Search Task.Alberto Testoni, Raffaella Bernardi & Azzurra Ruggeri - 2023 - Cognitive Science 47 (12):e13396.
    In recent years, a multitude of datasets of human–human conversations has been released for the main purpose of training conversational agents based on data‐hungry artificial neural networks. In this paper, we argue that datasets of this sort represent a useful and underexplored source to validate, complement, and enhance cognitive studies on human behavior and language use. We present a method that leverages the recent development of powerful computational models to obtain the fine‐grained annotation required to apply metrics and techniques from (...)
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  • Shake it baby, but only when needed: Preschoolers adapt their exploratory strategies to the information structure of the task.Azzurra Ruggeri, Nora Swaboda, Zi Lin Sim & Alison Gopnik - 2019 - Cognition 193 (C):104013.
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  • Memory enhancements from active control of learning emerge across development.Azzurra Ruggeri, Douglas B. Markant, Todd M. Gureckis, Maria Bretzke & Fei Xu - 2019 - Cognition 186 (C):82-94.
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  • How to Help Young Children Ask Better Questions?Azzurra Ruggeri, Caren M. Walker, Tania Lombrozo & Alison Gopnik - 2021 - Frontiers in Psychology 11.
    In this paper, we investigate the informativeness of 4- to 6-year-old children’s questions using a combined qualitative and quantitative approach. Children were presented with a hierarchical version of the 20-questions game, in which they were given an array of objects that could be organized into three category levels based on shared features. We then tested whether it is possible to scaffold children’s question-asking abilities without extensive training. In particular, we supported children’s categorization performance by providing the object-related features needed to (...)
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  • Rational information search in welfare-tradeoff cognition.Tadeg Quillien - 2023 - Cognition 231 (C):105317.
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  • Causal Information‐Seeking Strategies Change Across Childhood and Adolescence.Kate Nussenbaum, Alexandra O. Cohen, Zachary J. Davis, David J. Halpern, Todd M. Gureckis & Catherine A. Hartley - 2020 - Cognitive Science 44 (9):e12888.
    Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that appear to confirm a single hypothesis rather than those that optimally discriminate alternative hypotheses. Here, we investigated how the ability to make informative causal interventions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. Each (...)
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  • Stepwise versus globally optimal search in children and adults.Björn Meder, Jonathan D. Nelson, Matt Jones & Azzurra Ruggeri - 2019 - Cognition 191 (C):103965.
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  • “What makes this a wug?” Relations among children’s question asking, memory, and categorization of objects.Emma Lazaroff & Haley A. Vlach - 2022 - Frontiers in Psychology 13.
    Children ask many questions, but do not always receive answers to the questions they ask. We were interested in whether the act of generating questions, in the absence of an answer, is related to children’s later thinking. Two experiments examined whether children retain the questions they ask in working memory, and whether the type of questions asked relate to their categorization. Four to ten-year-old children were shown 12 novel objects, asked three questions about each, and did not receive answers to (...)
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  • Desirable difficulties during the development of active inquiry skills.George Kachergis, Marjorie Rhodes & Todd Gureckis - 2017 - Cognition 166:407-417.
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  • Supporting Early Scientific Thinking Through Curiosity.Jamie J. Jirout - 2020 - Frontiers in Psychology 11.
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  • Curiosity as a metacognitive feeling.Louise Goupil & Joëlle Proust - 2023 - Cognition 231 (C):105325.
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  • Bayesians Commit the Gambler's Fallacy.Kevin Dorst - manuscript
    The gambler’s fallacy is the tendency to expect random processes to switch more often than they actually do—for example, to think that after a string of tails, a heads is more likely. It’s often taken to be evidence for irrationality. It isn’t. Rather, it’s to be expected from a group of Bayesians who begin with causal uncertainty, and then observe unbiased data from an (in fact) statistically independent process. Although they converge toward the truth, they do so in an asymmetric (...)
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