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Psychology

D-Index
30
Citations
4555
World Ranking
11340
National Ranking
5926

Overview

Evan Heit is a researcher affiliated with the National Science Foundation in the United States. Their academic focus spans multiple disciplines, primarily within the broad fields of Computer Science, Psychology, and Social Sciences.

The main areas of study for this scientist include:

  • Computer Science
  • Psychology
  • Social Sciences

Evan Heit's work delves into several specific subfields, reflecting a range of interdisciplinary interests. These subfields are:

  • Artificial Intelligence
  • Developmental and Educational Psychology
  • Sociology and Political Science
  • Social Psychology

The scientist has contributed research on a variety of topics, emphasizing both cognitive and social dimensions, as well as technical applications. The main topics of their studies are:

  • Child and Animal Learning Development
  • Social and Intergroup Psychology
  • Cultural Differences and Values
  • Neural Networks and Applications
  • AI-based Problem Solving and Planning
  • Natural Language Processing Techniques

Throughout their career, Evan Heit has collaborated with several colleagues, notably including:

  • Ulrike Hahn
  • Lewis Bott

This profile does not list specific recent paper titles or publication venues associated with Evan Heit; however, the interdisciplinary nature of their work suggests involvement in fields such as artificial intelligence and social sciences publications.

Best Publications

  • Properties of inductive reasoning.

    Evan Heit

  • Similarity and Property Effects in Inductive Reasoning

    Evan Heit;Joshua Rubinstein

  • Associative recognition: a case of recall-to-reject processing.

    Caren M. Rotello;Evan Heit

  • Relations between inductive reasoning and deductive reasoning.

    Evan Heit;Caren M. Rotello

  • Assessing the Belief Bias Effect With ROCs: It's a Response Bias Effect

    Chad Dube;Caren M. Rotello;Evan Heit

  • Models of the effects of prior knowlege on category learning.

    Evan Heit

  • Observational Learning From Internal Feedback: A Simulation of an Adaptive Learning Method

    Dorrit Billman;Evan Heit

  • The Instantiation Principle in Natural Categories

    Evan Heit;Lawrence W. Barsalou

  • Two-Process Models of Recognition Memory: Evidence for Recall-to-Reject?

    Caren M. Rotello;Evan Heit

  • Knowledge selection in category learning

    Evan Heit;Lewis Bott

  • Models of the effects of prior knowledge on category learning.

    Evan Heit

  • Bayesian models of cognition

    Nick Chater;Mike Oaksford;Ulrike Hahn;Evan Heit

  • When more data steer us wrong: replications with the wrong dependent measure perpetuate erroneous conclusions.

    Caren M. Rotello;Evan Heit;Chad Dubé

  • Diversity-Based Reasoning in Children

    Evan Heit;Ulrike Hahn

  • Modeling the effects of argument length and validity on inductive and deductive reasoning.

    Caren M. Rotello;Evan Heit

  • The role of diverse instruction in conceptual change

    Brett K Hayes;Alison Goodhew;Evan Heit;Joanna Gillan

  • Categorization using chains of examples

    Evan Heit

  • Influences of prior knowledge on selective weighting of category members.

    Evan Heit

  • Nonmonotonic extrapolation in function learning.

    Lewis Bott;Evan Heit

  • Inductive reasoning 2.0.

    Brett K. Hayes;Evan Heit

  • The Opposite of Republican: Polarization and Political Categorization

    Evan Heit;Stephen P. Nicholson

  • Adaptive changes of response criterion in recognition memory

    Evan Heit;Noellie Brockdorff;Koen Lamberts

Frequent Co-Authors

Ulrike Hahn
Ulrike Hahn Birkbeck, University of London
Mike Oaksford
Mike Oaksford Birkbeck, University of London
Stephan Lewandowsky
Stephan Lewandowsky University of Bristol
Nick Chater
Nick Chater University of Warwick
Rick Dale
Rick Dale University of California, Los Angeles
Douglas L. Medin
Douglas L. Medin Northwestern University
Gordon H. Bower
Gordon H. Bower Stanford University
Lawrence W. Barsalou
Lawrence W. Barsalou University of Glasgow

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