How Diagrams Can Support Syllogistic Reasoning: An Experimental Study

被引:15
|
作者
Sato Y. [1 ]
Mineshima K. [2 ]
机构
[1] Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo
[2] Center for Simulation Sciences, Ochanomizu University, Tokyo
基金
日本学术振兴会;
关键词
Categorical syllogism; Efficacy of diagrams; External representation; Human experimentation; Human reasoning; Logic and cognition; Quantification;
D O I
10.1007/s10849-015-9225-4
中图分类号
学科分类号
摘要
This paper explores the question of what makes diagrammatic representations effective for human logical reasoning, focusing on how Euler diagrams support syllogistic reasoning. It is widely held that diagrammatic representations aid intuitive understanding of logical reasoning. In the psychological literature, however, it is still controversial whether and how Euler diagrams can aid untrained people to successfully conduct logical reasoning such as set-theoretic and syllogistic reasoning. To challenge the negative view, we build on the findings of modern diagrammatic logic and introduce an Euler-style diagrammatic representation system that is designed to avoid problems inherent to a traditional version of Euler diagrams. It is hypothesized that Euler diagrams are effective not only in interpreting sentential premises but also in reasoning about semantic structures implicit in given sentences. To test the hypothesis, we compared Euler diagrams with other types of diagrams having different syntactic or semantic properties. Experiment compared the difference in performance between syllogistic reasoning with Euler diagrams and Venn diagrams. Additional analysis examined the case of a linear variant of Euler diagrams, in which set-relationships are represented by one-dimensional lines. The experimental results provide evidence supporting our hypothesis. It is argued that the efficacy of diagrams in supporting syllogistic reasoning crucially depends on the way they represent the relational information contained in categorical sentences. © 2015, Springer Science+Business Media Dordrecht.
引用
收藏
页码:409 / 455
页数:46
相关论文
共 50 条
  • [1] HOW DIAGRAMS CAN IMPROVE REASONING
    BAUER, MI
    JOHNSONLAIRD, PN
    [J]. PSYCHOLOGICAL SCIENCE, 1993, 4 (06) : 372 - 378
  • [2] Using Venn Diagrams to Perform Logic Reasoning: An Algorithm for Automating the Syllogistic Reasoning of Categorical Statements
    Nakatsu, Robbie T.
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2014, 29 (01) : 84 - 103
  • [3] Can natural language semantics explain syllogistic reasoning?
    Newstead, SE
    [J]. COGNITION, 2003, 90 (02) : 193 - 199
  • [4] Towards explaining the cognitive efficacy of Euler diagrams in syllogistic reasoning: A relational perspective
    Mineshima, Koji
    Sato, Yuri
    Takemura, Ryo
    Okada, Mitsuhiro
    [J]. JOURNAL OF VISUAL LANGUAGES AND COMPUTING, 2014, 25 (03): : 156 - 169
  • [5] Necessity, possibility and belief: A study of syllogistic reasoning
    Evans, JST
    Handley, SJ
    Harper, CNJ
    [J]. QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY SECTION A-HUMAN EXPERIMENTAL PSYCHOLOGY, 2001, 54 (03): : 935 - 958
  • [6] How Dynamic Visualization Technology can Support Molecular Reasoning
    Levy, Dalit
    [J]. JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY, 2013, 22 (05) : 702 - 717
  • [7] How Dynamic Visualization Technology can Support Molecular Reasoning
    Dalit Levy
    [J]. Journal of Science Education and Technology, 2013, 22 : 702 - 717
  • [8] Negative valence can evoke a liberal response bias in syllogistic reasoning
    Oshin Vartanian
    Ann Nakashima
    Fethi Bouak
    Ingrid Smith
    Joseph V. Baranski
    Bob Cheung
    [J]. Cognitive Processing, 2013, 14 : 89 - 98
  • [9] Negative valence can evoke a liberal response bias in syllogistic reasoning
    Vartanian, Oshin
    Nakashima, Ann
    Bouak, Fethi
    Smith, Ingrid
    Baranski, Joseph V.
    Cheung, Bob
    [J]. COGNITIVE PROCESSING, 2013, 14 (01) : 89 - 98
  • [10] How can we study reasoning in the brain?
    Papo, David
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2015, 9