Human Reasoning with Proportional Quantifiers and Its Support by Diagrams

Conference paper

DOI: 10.1007/978-3-319-42333-3_10

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9781)
Cite this paper as:
Sato Y., Mineshima K. (2016) Human Reasoning with Proportional Quantifiers and Its Support by Diagrams. In: Jamnik M., Uesaka Y., Elzer Schwartz S. (eds) Diagrammatic Representation and Inference. Diagrams 2016. Lecture Notes in Computer Science, vol 9781. Springer, Cham


In this paper, we study the cognitive effectiveness of diagrammatic reasoning with proportional quantifiers such as most. We first examine how Euler-style diagrams can represent syllogistic reasoning with proportional quantifiers, building on previous work on diagrams for the so-called plurative syllogism (Rescher and Gallagher, 1965). We then conduct an experiment to compare performances on syllogistic reasoning tasks of two groups: those who use only linguistic material (two sentential premises and one conclusion) and those who are also given Euler diagrams corresponding to the two premises. Our experiment showed that (a) in both groups, the speed and accuracy of syllogistic reasoning tasks with proportional quantifiers like most were worse than those with standard first-order quantifiers such as all and no, and (b) in both standard and non-standard (proportional) syllogisms, speed and accuracy for the group provided with diagrams were significantly better than the group provided only with sentential premises. These results suggest that syllogistic reasoning with proportional quantifiers like most is cognitively complex, yet can be effectively supported by Euler diagrams that represent the proportionality relationships between sets in a suitable way.


Euler diagrams Proportional quantifiers Reasoning Logic and cognition 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Interfaculty Initiative in Information StudiesThe University of TokyoTokyoJapan
  2. 2.Center for Simulation SciencesOchanomizu UniversityTokyoJapan

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