Experimental data on time and interventions in children's causal structure learning

DOI

Experimental data measuring the cues that children and adults use to figure out causal structure, and more specifically to explore whether there are changes with age in the accuracy of such learning and in the ways in which different cues are used. In particular, it examines the ways in which cues about the timing of events are used, and whether children can learn about the relationship between events through acting or intervening on them. Imagine that you encounter three events A, B and C that tend to occur together. What are the relationships between A, B, and C? One possibility is that A causes B and B causes C; another possibility is that A separately causes both B and C. Research on what is termed causal structure learning examines how we go about figuring out the structure of the relationships between events. When we learn about causal structure, we are essentially learning about how the world works, thus this type of learning is fundamental to the development of knowledge itself. his project aims to examine the cues that children and adults use to figure out causal structure, and more specifically to explore whether there are changes with age in the accuracy of such learning and in the ways in which different cues are used. In particular, it will examine the ways in which cues about the timing of events are used, and whether children can learn about the relationship between events through acting or intervening on them. The proposed project will test competing theories about the benefits of intervention and also provide a systematic exploration of developmental changes in the ability to learn through intervention.

Experimental methods

Identifier
DOI https://doi.org/10.5255/UKDA-SN-851417
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=2d108def1a93682271ae2c8dbef90cd69fbe3913bd3d3f7c5ca0c591a0d1ded6
Provenance
Creator Mccormack, T, Queen's University Belfast; Lagnado, D, University College London
Publisher UK Data Service
Publication Year 2014
Funding Reference ESRC
Rights Teresa Mccormack, Queen's University Belfast. David Lagnado, University College London; The Data Collection is available to any user without the requirement for registration for download/access.
OpenAccess true
Representation
Language English
Resource Type Numeric
Discipline Psychology; Social and Behavioural Sciences
Spatial Coverage UK; United Kingdom