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Information Search: Developmental change in the effectiveness of active learning strategies

Deciding what evidence is most valuable to obtain is a basic challenge faced by learners of any age. Research investigating children’s active information search has used variants of the “20-questions game”, where the task is to identify an unknown target object by asking as few yes-or-no questions as possible, either generating the questions from scratch or selecting them from a list of given alternatives. 

Previous research has shown that the ability to efficiently ask questions and explore the environment undergoes a large developmental change from age 4 to adulthood (Ruggeri & Lombrozo, 2015; Ruggeri, Lombrozo, Griffiths, & Xu, 2016). However, despite having difficulty generating informative questions from scratch (Ruggeri, Walker, Lombrozo, & Gopnik, 2016), 4- and 5-year-olds can already identify the most effective among given questions (Ruggeri, Sim, & Xu, 2016), suggesting that preschoolers have the computational foundations for developing successful question-asking strategies. This developmental change can be partially explained by children’s increasing ability to generate higher-order features that can be used to cluster similar objects into categories (for example, blue versus green monsters; see Ruggeri & Feufel, 2015) and by the development of more general verbal abilities and vocabulary. Additionally, computational findings provide compelling evidence of developmental differences in the implementation of stopping rules in information search: Children are more likely than adults to continue their search for information beyond the point at which the solution could be given.

 

One of our Information Search projects: MOSES (Monster One Step ahead Effective Search)

In MOSES (Monsters One Step ahead Effective Search) we use a 20-questions game, in which the goal is to identify an unknown target object (a special ‘monster’ – see examples above) by asking as few yes-no questions as possible. The game is similar to the popular children’s game “Guess Who?”, in which the goal is to identify a cartoon face by asking yes-no questions about its features. After being introduced to the goal of the game (finding the monster that turns on a special machine), children (7- to 10-year-olds) and adults are presented with four questions to choose among: they can ask for the color, the pattern, or the shape of the target monster (for example, “is the monster that turns on the machine round?”), or ask about a single monsters (“is this the monster that turns on the machine?”). Our aim is to find out whether children are intuitively able to plan one step ahead when selecting which question to ask, that is, if they can select the most effective question by considering what the feedback to their first question might be.

Current and future directions

We are currently developing new paradigms to investigate children’s spontaneous active learning strategies, to extend the exploration of the potential sources of developmental change to toddlers and infants. A multidisciplinary and multi-method approach to the study of active learning strategies has the potential to shed light on how children generate and structure their hypothesis space, revising it in response to feedback and new information. A systematic analysis of the interplay between the process of generating hypotheses and the strategies implemented to evaluate and test them can substantially advance our understanding of how children learn in real-world settings.

Relevant publications

Ruggeri, A., Lombrozo, T., Griffiths, T. L., & Xu, F.  (in press) Sources of developmental change in the efficiency of information search. Developmental Psychology.

Ruggeri, A. & Feufel, M. A. (2015). How basic-level objects facilitate question-asking in a categorization task. Frontiers in Psychology, 6(918), 1–13. doi:10.3389/fpsyg.2015.00918

Ruggeri, A., Olsson, H., & Katsikopoulos, K. V. (2015). Opening the cuebox: The information children and young adults generate and rely on when making inferences from memory. British Journal of Developmental Psychology, 33(3), 355–374. doi:10.1111/bjdp.12100

Collaborators

Tania Lombrozo, Department of Psychology, University of California, Berkeley

Fei Xu, Department of Psychology, University of California, Berkeley

Alison Gopnik, Department of Psychology, University of California, Berkeley

Thomas Griffiths, Department of Psychology, University of California, Berkeley

Douglas Markant, Center for Adaptive Rationality, Max Planck Institute for Human Development in Berlin.

Thorsten Pachur, Center for Adaptive Rationality, Max Planck Institute for Human Development in Berlin.

Björn Meder, Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development in Berlin. 

Jonathan Nelson, Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development in Berlin. 

Todd Gureckis, New York University.

Alejo Salles, Integrative Neuroscience Lab, University of Buenos Aires.