Deeva Tatyana M.
Graduate student of the Department of General Psychology of the Samara National Research University named after Academician S.P. Korolev.
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Simple regularities acquisition in the studies of implicit learningLomonosov Psychology Journal, 2020, 1. p. 124-142read more2611
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Background. According to modern empirical data, unconsciously processed information can have a significant impact on human behavior in all spheres of activity. Information about the unconscious information processing is fragmented and often contradictory. For the study of implicit learning different approaches are traditionally used, but none of them are effective for the clear results about the consciousness and abstractness degree of the knowledge obtained. We could more carefully inquire into the matter of unconscious knowledge and its influence on the cognitive problems solving with information about implicit learning of simple rules. This methodology makes it possible to apply more strong criteria for explicit knowledge and assumes purer experimental effects of implicit learning.
Objective. To consider and analyze the experience of use experimental techniques with simple regularities acquisition in the studies of implicit learning.
Methods. Review and analysis of studies using simple regularities in the field of implicit learning.
Results. In the article researches within the experimental paradigms "invariant learning" and "hidden covariation detection" are considered. The most significant experiments, their results and the criticism has led to an improvement of experimental procedures are presented. The problems of using different types of tasks in the training and test stages are described. The main possibilities and limitations of using these paradigms for revealing the effect of implicit learning are outlined. Further perspectives for the application of these techniques are considered. But one needs for a more rigorous approach to measuring the level of awareness.
Conclusion.Experimental paradigms with simple regularities acquisition may be promising for the study of implicit association learning mechanisms.
Keywords: implicit learning; invariant learning; hidden covariation detection DOI: 10.11621/vsp.2020.01.07
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