Literature DB >> 15238029

The advantage of timely intervention.

David A Lagnado1, Steven Sloman.   

Abstract

Can people learn causal structure more effectively through intervention rather than observation? Four studies used a trial-based learning paradigm in which participants obtained probabilistic data about a causal chain through either observation or intervention and then selected the causal model most likely to have generated the data. Experiment 1 demonstrated that interveners made more correct model choices than did observers, and Experiments 2 and 3 ruled out explanations for this advantage in terms of informational differences between the 2 conditions. Experiment 4 tested the hypothesis that the advantage was driven by a temporal signal; interveners may exploit the cue that their interventions are the most likely causes of any subsequent changes. Results supported this temporal cue hypothesis. Copyright 2004 APA, all rights reserved

Entities:  

Mesh:

Year:  2004        PMID: 15238029     DOI: 10.1037/0278-7393.30.4.856

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  22 in total

1.  The importance of decision making in causal learning from interventions.

Authors:  David M Sobel; Tamar Kushnir
Journal:  Mem Cognit       Date:  2006-03

2.  Models of covariation-based causal judgment: a review and synthesis.

Authors:  José C Perales; David R Shanks
Journal:  Psychon Bull Rev       Date:  2007-08

3.  Evidence for online processing during causal learning.

Authors:  Pei-Pei Liu; Christian C Luhmann
Journal:  Learn Behav       Date:  2015-03       Impact factor: 1.986

Review 4.  Causal learning is collaborative: Examining explanation and exploration in social contexts.

Authors:  Cristine H Legare; David M Sobel; Maureen Callanan
Journal:  Psychon Bull Rev       Date:  2017-10

5.  Brief cognitive training interventions in young adulthood promote long-term resilience to drug-seeking behavior.

Authors:  Josiah R Boivin; Denise M Piscopo; Linda Wilbrecht
Journal:  Neuropharmacology       Date:  2015-06-09       Impact factor: 5.250

6.  Successful structure learning from observational data.

Authors:  Anselm Rothe; Ben Deverett; Ralf Mayrhofer; Charles Kemp
Journal:  Cognition       Date:  2018-07-02

7.  Failures of explaining away and screening off in described versus experienced causal learning scenarios.

Authors:  Bob Rehder; Michael R Waldmann
Journal:  Mem Cognit       Date:  2017-02

Review 8.  Reasoning about causal relationships: Inferences on causal networks.

Authors:  Benjamin Margolin Rottman; Reid Hastie
Journal:  Psychol Bull       Date:  2013-04-01       Impact factor: 17.737

9.  A self-agency bias in preschoolers' causal inferences.

Authors:  Tamar Kushnir; Henry M Wellman; Susan A Gelman
Journal:  Dev Psychol       Date:  2009-03

Review 10.  Structure learning in action.

Authors:  Daniel A Braun; Carsten Mehring; Daniel M Wolpert
Journal:  Behav Brain Res       Date:  2009-08-29       Impact factor: 3.332

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.