Literature DB >> 34918273

Transfer of category learning to impoverished contexts.

Peter S Whitehead1,2, Amanda Zamary3, Elizabeth J Marsh3.   

Abstract

Learning often happens in ideal conditions, but then must be applied in less-than-ideal conditions - such as when a learner studies clearly illustrated examples of rocks in a book but then must identify them in a muddy field. Here we examine whether the benefits of interleaving (vs. blocking) study schedules, as well as the use of feature descriptions, supports the transfer of category learning in new, impoverished contexts. Specifically, keeping the study conditions constant, we evaluated learners' ability to classify new exemplars in the same neutral context versus in impoverished contexts in which certain stimulus features are occluded. Over two experiments, we demonstrate that performance in new, impoverished contexts during test is greater for participants who received an interleaved (vs. blocked) study schedule, both for novel and for studied exemplars. Additionally, we show that this benefit extends to both a short (3-min) or long (48-h) test delay. The presence of feature descriptions during learning had no impact on transfer. Together, these results extend the growing literature investigating how changes in context during category learning or test impacts performance and provide support for the use of interleaving to promote the far transfer of category knowledge to impoverished contexts.
© 2021. The Psychonomic Society, Inc.

Entities:  

Keywords:  Category learning; Education; Feature descriptions; Interleaving; Transfer

Mesh:

Year:  2021        PMID: 34918273     DOI: 10.3758/s13423-021-02031-7

Source DB:  PubMed          Journal:  Psychon Bull Rev        ISSN: 1069-9384


  18 in total

1.  When and where do we apply what we learn? A taxonomy for far transfer.

Authors:  Susan M Barnett; Stephen J Ceci
Journal:  Psychol Bull       Date:  2002-07       Impact factor: 17.737

Review 2.  Distributed practice in verbal recall tasks: A review and quantitative synthesis.

Authors:  Nicholas J Cepeda; Harold Pashler; Edward Vul; John T Wixted; Doug Rohrer
Journal:  Psychol Bull       Date:  2006-05       Impact factor: 17.737

3.  G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences.

Authors:  Franz Faul; Edgar Erdfelder; Albert-Georg Lang; Axel Buchner
Journal:  Behav Res Methods       Date:  2007-05

4.  Improved Classification of Mammograms Following Idealized Training.

Authors:  Adam N Hornsby; Bradley C Love
Journal:  J Appl Res Mem Cogn       Date:  2014-06-01

5.  Improving Students' Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology.

Authors:  John Dunlosky; Katherine A Rawson; Elizabeth J Marsh; Mitchell J Nathan; Daniel T Willingham
Journal:  Psychol Sci Public Interest       Date:  2013-01

6.  The sequence of study changes what information is attended to, encoded, and remembered during category learning.

Authors:  Paulo F Carvalho; Robert L Goldstone
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2017-03-23       Impact factor: 3.051

7.  Similarity matters: A meta-analysis of interleaved learning and its moderators.

Authors:  Matthias Brunmair; Tobias Richter
Journal:  Psychol Bull       Date:  2019-09-26       Impact factor: 17.737

Review 8.  What makes distributed practice effective?

Authors:  Aaron S Benjamin; Jonathan Tullis
Journal:  Cogn Psychol       Date:  2010-11       Impact factor: 3.468

Review 9.  What you learn is more than what you see: what can sequencing effects tell us about inductive category learning?

Authors:  Paulo F Carvalho; Robert L Goldstone
Journal:  Front Psychol       Date:  2015-04-30

10.  Gorilla in our midst: An online behavioral experiment builder.

Authors:  Alexander L Anwyl-Irvine; Jessica Massonnié; Adam Flitton; Natasha Kirkham; Jo K Evershed
Journal:  Behav Res Methods       Date:  2020-02
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