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Toddlers strategically adapt their information search

Author

Listed:
  • Francesco Poli

    (Radboud University
    University of Cambridge)

  • Yi-Lin Li

    (University of Oxford)

  • Pravallika Naidu

    (University of Oxford)

  • Rogier B. Mars

    (Radboud University)

  • Sabine Hunnius

    (Radboud University)

  • Azzurra Ruggeri

    (Max Planck Institute for Human Development
    Technical University Munich
    Central European University)

Abstract

Adaptive information seeking is essential for humans to effectively navigate complex and dynamic environments. Here, we developed a gaze-contingent eye-tracking paradigm to examine the early emergence of adaptive information-seeking. Toddlers (N = 60, 18-36 months) and adults (N = 42) either learnt that an animal was equally likely to be found in any of four available locations, or that it was most likely to be found in one particular location. Afterwards, they were given control of a torchlight, which they could move with their eyes to explore the otherwise pitch-black task environment. Eye-movement data and Markov models show that, from 24 months of age, toddlers become more exploratory than adults, and start adapting their exploratory strategies to the information structure of the task. These results show that toddlers’ search strategies are more sophisticated than previously thought, and identify the unique features that distinguish their information search from adults’.

Suggested Citation

  • Francesco Poli & Yi-Lin Li & Pravallika Naidu & Rogier B. Mars & Sabine Hunnius & Azzurra Ruggeri, 2024. "Toddlers strategically adapt their information search," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48855-4
    DOI: 10.1038/s41467-024-48855-4
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    References listed on IDEAS

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    1. Max H. Siegel & Rachel W. Magid & Madeline Pelz & Joshua B. Tenenbaum & Laura E. Schulz, 2021. "Children’s exploratory play tracks the discriminability of hypotheses," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    2. Anthony M. Zador, 2019. "A critique of pure learning and what artificial neural networks can learn from animal brains," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    3. Celeste Kidd & Steven T Piantadosi & Richard N Aslin, 2012. "The Goldilocks Effect: Human Infants Allocate Attention to Visual Sequences That Are Neither Too Simple Nor Too Complex," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-8, May.
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