Children struggle with the quantifier "most". Often, this difficulty is attributed to an inability to interpret most proportionally, with children instead relying on absolute quantity comparisons. However, recent research in proportional reasoning more generally has provided new insight into children's apparent difficulties, revealing that their overreliance on absolute amount is unique to contexts in which the absolute amount can be counted and interferes with proportional information. Across two experiments, we test whether 4- to 6-year-old children's interpretation of most is similarly dependent on the discreteness of the stimuli when comparing two different quantities (e.g., who ate most of their chocolate?) and when verifying whether a single amount can be described with the term most (e.g., is most of the butterfly colored in?). We find that children's interpretation of most does depend on the stimulus format. When choosing between absolutely more vs. proportionally more as depicting most, children showed stronger absolute-based errors with discrete stimuli than continuous stimuli, and by 6-years-old were able to reason proportionally with continuous stimuli, despite still demonstrating strong absolute interference with discrete stimuli. In contrast, children's yes/no judgements of single amounts, where conflicting absolute information is not a factor, showed a weaker understanding of most for continuous stimuli than for discrete stimuli. Together, these results suggest that children's difficulty with most is more nuanced than previously understood: it depends on the format and availability of proportional vs. absolute amounts and develops substantially from 4- to 6-years-old.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cognition.2022.105149 | DOI Listing |
Nat Commun
January 2025
Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA.
Neuronal population activity in sensory cortices is the substrate for perceptual decisions. Yet, we still do not understand how neuronal information content in sensory cortices relates to behavioral reports. To reconcile neurometric and psychometric performance, we recorded the activity of V1 neurons in mice performing a Go/NoGo orientation discrimination task.
View Article and Find Full Text PDFJ Clin Invest
January 2025
Jeff and Penny Vinik Center for Allergic Disease Research, Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Mast cells (MCs) expressing a distinctive protease phenotype (MCTs) selectively expand within the epithelium of human mucosal tissues during type 2 (T2) inflammation. While MCTs are phenotypically distinct from subepithelial MCs (MCTCs), signals driving human MCT differentiation and this subset's contribution to inflammation remain unexplored. Here, we have identified TGF-β as a key driver of the MCT transcriptome in nasal polyps.
View Article and Find Full Text PDFMem Cognit
December 2024
Department of Psychology, City St George's, University of London, Northampton Square, London, EC1V 0HB, UK.
Statistical learning is a mechanism for detecting associations among co-occurring elements in many domains and species. A key controversy is whether it leads to memory for discrete chunks composed of these associated elements, or merely to pairwise associations among elements. Critical evidence for the mere-association view comes from the "phantom-word" phenomenon, where learners recognize statistically coherent but unattested items better than actually presented items with weaker internal associations, suggesting that they prioritize pairwise associations over memories for discrete units.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
December 2024
New Chemistry Unit, School of Advanced Materials (SAMat), Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR), Jakkur, Bangalore, 560064, India.
Sci Adv
December 2024
School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
Biological materials dynamically reconfigure their underlying structures in response to stimuli, achieving adaptability and multifunctionality. Conversely, mechanical metamaterials have fixed interunit connections that restrict adaptability and reconfiguration. This study introduces granular metamaterials composed of discrete bimaterial structured particles that transition between assembled and unassembled states through mechanical compression and thermal stimuli.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!