Topics in Cognitive Science

Cover image for Vol. 8 Issue 3

July 2016

Volume 8, Issue 3

Pages 515–715

  1. Issue Information

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. You have free access to this content
      Issue Information (pages 515–517)

      Version of Record online: 4 AUG 2016 | DOI: 10.1111/tops.12168

  2. Introduction to Volume 8, Issue 3 of topiCS

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. You have free access to this content
  3. Topic Continuation: Visions of Cognitive Science

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. Is There a Free Lunch in Inference? (pages 520–547)

      Jeffrey N. Rouder, Richard D. Morey, Josine Verhagen, Jordan M. Province and Eric-Jan Wagenmakers

      Version of Record online: 4 AUG 2016 | DOI: 10.1111/tops.12214

      Conducting significance testing without a well-specified alternative is nothing more than hoping for a “free lunch.” We argue neither the conventional nor Bayesian frameworks support this hope and that not specifying an alternative leads to false rejections of the null hypothesis.

  4. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. You have free access to this content
      Discovering Psychological Principles by Mining Naturally Occurring Data Sets (pages 548–568)

      Robert L. Goldstone and Gary Lupyan

      Version of Record online: 12 JUL 2016 | DOI: 10.1111/tops.12212

      The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision making, language use, inference, problem solving, and representation. We consider some case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods.

  5. Articles

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. Exploring Human Cognition Using Large Image Databases (pages 569–588)

      Thomas L. Griffiths, Joshua T. Abbott and Anne S. Hsu

      Version of Record online: 4 AUG 2016 | DOI: 10.1111/tops.12209

      We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories.

    2. Testing Theories of Transfer Using Error Rate Learning Curves (pages 589–609)

      Kenneth R. Koedinger, Michael V. Yudelson and Philip I. Pavlik Jr.

      Version of Record online: 27 MAY 2016 | DOI: 10.1111/tops.12208

      We analyze naturally occurring data sets from student use of educational technologies to explore a long-standing question of the scope of transfer of learning. We contrast a faculty theory of broad transfer with a component theory of more constrained transfer. In comparisons across eight data sets, we find that the component models provide both better predictions and better explanations than the faculty models. More generally, the approach could be used to identify malleable components of cognitive functions, such as spatial reasoning or executive functions.

    3. Division of Labor in Vocabulary Structure: Insights From Corpus Analyses (pages 610–624)

      Morten H. Christiansen and Padraic Monaghan

      Version of Record online: 24 SEP 2015 | DOI: 10.1111/tops.12164

      Psychologists have used experimental methods to study language for more than a century. However, only with the recent availability of large-scale linguistic databases has a more complete picture begun to emerge of how language is actually used and what information is available as input to language acquisition. Analyses of such ‘big data’ have resulted in reappraisals of key assumptions about the nature of language, including the arbitrariness of the sign which is the focus on this paper.

    4. The Latent Structure of Dictionaries (pages 625–659)

      Philippe Vincent-Lamarre, Alexandre Blondin Massé, Marcos Lopes, Mélanie Lord, Odile Marcotte and Stevan Harnad

      Version of Record online: 18 JUL 2016 | DOI: 10.1111/tops.12211

      Only about 1% of the words in a dictionary are needed to define all the rest. These “grounding” words turn out to be more frequent and are learned earlier than the rest. In principle, they are the only words whose meanings we need to learn from direct experience. Then language can recombine them to define and describe everything else.

    5. Exploring Psychology in the Field: Steps and Examples From the Used-Car Market (pages 660–669)

      Devin G. Pope

      Version of Record online: 14 MAY 2016 | DOI: 10.1111/tops.12210

      The growing availability of large datasets in a variety of domains presents an opportunity for researchers to use field data to better understand psychological concepts. I discuss from an empirical economics point of view, steps for how to study cognition in large datasets and illustrate these steps with recent empirical papers.

    6. Does Presentation Order Impact Choice After Delay? (pages 670–684)

      Jonah Berger

      Version of Record online: 11 MAY 2016 | DOI: 10.1111/tops.12205

      Options are often presented incidentally in a sequence, but does the order items appear on a list impact choice after delay, and if so, how? Using 25 years of citation data, and a unique identification strategy, we address this question by examining the relationship between article order (i.e., position in a journal issue) and citation count. Results indicate that mere serial position affects the prominence that research achieves.

    7. You have full text access to this OnlineOpen article
      Searching Choices: Quantifying Decision-Making Processes Using Search Engine Data (pages 685–696)

      Helen Susannah Moat, Christopher Y. Olivola, Nick Chater and Tobias Preis

      Version of Record online: 1 JUN 2016 | DOI: 10.1111/tops.12207

      When making a decision, humans consider two types of information: information they have acquired through their prior experience of the world, and further information they gather to support the decision in question. We show that statistics from Google search engine queries can help us estimate the statistical structure of prior experience; and, specifically, we outline how such statistics can inform psychological theories concerning the valuation of human lives, or choices involving delayed outcomes. We conclude that search engine data constitute a valuable new resource for cognitive scientists, offering a fascinating new tool for understanding the human decision making process.

    8. Missing the Party: Political Categorization and Reasoning in the Absence of Party Label Cues (pages 697–714)

      Evan Heit and Stephen P. Nicholson

      Version of Record online: 14 MAY 2016 | DOI: 10.1111/tops.12206

      Using national opinion survey data, this research addressed claims in political science that the American electorate is either poorly informed or dependent on party label cues. The results suggested that in situations with missing information, American voters can use their knowledge to successfully infer political party membership of candidates and vote their own party interests.

  6. Corrigendum

    1. Top of page
    2. Issue Information
    3. Introduction to Volume 8, Issue 3 of topiCS
    4. Topic Continuation: Visions of Cognitive Science
    5. Editors' Introduction: Discovering Psychological Principles by Mining Naturally Occurring Data Sets
    6. Articles
    7. Corrigendum
    1. You have free access to this content

SEARCH

SEARCH BY CITATION