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Updated: May 13, 2026

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
Selective social learning: new perspectives on learning from others
Melissa A Koenig1, Mark A Sabbagh
1Institute of Child Development, University of Minnesota, Twin Cities, USA. mkoenig@umn.edu
Abstract:
This special issue was motivated by the recent, wide-ranging interest in the development of children's selective social learning. Human beings have a far-reaching dependence on others for information, and the focus of this issue is on the processes by which children selectively and intelligently learn from others. It showcases some of the finest current work in this area and also aims to encourage new lines of investigation and new ways of thinking about how children learn from others. This issue also serves to highlight this new direction in basic research for the broader community of researchers, educators, and practitioners. Research on issues related to the facilitation of social learning has clear relevance to early educational contexts. In addition, by bringing together a varied pool of research on the same general topic, developmental scientists can discern the consistencies and themes that emerge from their collective efforts. The work presented here illustrates the breadth of children's selectivity across ages and domains of development, and it highlights the growing range of methods that can be recruited to investigate selectivity. This new research leads the field to reconsider the various ways in which social information guides learning and calls for novel theoretical accounts of these developments.
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