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Attention, Perception, & Psychophysics

, Volume 81, Issue 1, pp 137–157 | Cite as

Semisupervised category learning facilitates the development of automaticity

  • Katleen Vandist
  • Gert Storms
  • Eva Van den Bussche
Article

Abstract

In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised category learning late in learning, when automaticity develops, is unknown. Therefore, in Experiment 1, all participants were first trained on the information-integration category structure for 2 days until they reached an expert level. Afterwards, half of the participants learned in a supervised way and the other half in a semisupervised way over two successive days. Both groups received an equal number of feedback trials. Finally, all participants took part in a test day where they were asked to respond as quickly as possible. Participants were significantly faster on this test in the semisupervised group than in the supervised group. This difference was not found on day 2, implying that the no-feedback trials in the semisupervised condition facilitated automaticity. Experiment 2 was designed to test whether the higher number of trials in the semisupervised condition of Experiment 1 caused the faster response times. We therefore created an almost supervised condition where participants almost always received feedback (95%) and an almost unsupervised condition where participants almost never received feedback (5%). All conditions now contained an equal number of trials to the semisupervised condition of Experiment 1. The results show that receiving feedback almost always or almost never led to slower response times than the semisupervised condition of Experiment 1. This confirms the advantage of semisupervised learning late in learning.

Keywords

Categorization Semisupervised learning Automaticity 

Supplementary material

13414_2018_1595_MOESM1_ESM.pdf (1.7 mb)
ESM 1 (PDF 1778 kb)

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Copyright information

© The Psychonomic Society, Inc. 2018

Authors and Affiliations

  • Katleen Vandist
    • 1
    • 2
  • Gert Storms
    • 2
  • Eva Van den Bussche
    • 1
    • 2
  1. 1.Department of PsychologyVrije Universiteit BrusselBrusselsBelgium
  2. 2.Department of Experimental PsychologyKU LeuvenLeuvenBelgium

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