Acquisition of Abstract Knowledge in Implicit Learning of Anagram Solution Scheme

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Abstract

The article addresses the problem of unconscious gaining of abstract knowledge. Participants solved circular 5-letter anagram arranged by the same invariant scheme. The learned schematic invariant is not perceptive, contrary to the usual invariant acquisition technique in other studies. The possibility of implicit learning of a solution scheme is discussed. Efficiency of anagram solving is compared between the groups with constant or changed solution scheme during the test stage. The change of the solution scheme leads to a decrease of efficiency, i.e. to the lower number of the solved anagrams. The results support the possibility of gaining unconscious abstract knowledge concerning the scheme without any perceptual invariant component. Possible use of a similar stimulus material in studies of interaction between visual and verbal components of working memory is briefly discussed.

General Information

Keywords: implicit learning, anagram solving, invariant learning, representation of abstract knowledge

Journal rubric: Cognitive Psychology

DOI: https://doi.org/10.17759/exppsy.2021140103

For citation: Deeva T.M., Kozlov D.D. Acquisition of Abstract Knowledge in Implicit Learning of Anagram Solution Scheme. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2021. Vol. 14, no. 1, pp. 95–107. DOI: 10.17759/exppsy.2021140103. (In Russ., аbstr. in Engl.)

References

  1. Deeva T.M., Agafonov A.Yu., Kryukova A.P., Shilov Yu.E. Vlijanie implicitnogo usvoenija invariantov na jeffektivnost’ reshenija zadachi klassifikacii [The Impact of the Invariants Implicit Learning on the Effectiveness of Classification]. Peterburgskij psihologicheskij zhurnal=St. Petersburg Psychological Journal, 2018, no 24, pp. 26—39. (In Russ.).
  2. Ivanchej I.I. Teorii implicitnogo nauchenija: protivorechivye podhody k odnomu fenomenu ili neprotivorechivye opisanija raznyh? [Theories of Implicit Learning: Contradictory Approaches to the Same Phenomenon or Consistent Descriptions of Different Types of Learning?]. Rossijskij zhurnal kognitivnoj nauki=The Russian Journal of Cognitive Science, 2014, Vol. 1, no. 4, pp. 4—30. Available at: http://www. cogjournal.ru/1/4/pdf/IvancheiRJCS2014.pdf (Accessed 10.10.2019). (In Russ.).
  3. Ljashevskaja O.N., Sharov S.A. Chastotnyj slovar’ sovremennogo russkogo jazyka (na materialah Nacional’nogo korpusa russkogo jazyka) [Russian language frequency dictionary (based on the materials of the National corpus of the Russian language)]. Moscow: Azbukovnik, 2009. 1087 p. (In Russ.).
  4. Medyncev A.A. Vlijanie implicitnoj podskazki na avtomaticheskie processy obrabotki informacii v zadache na reshenie anagramm [The influence of implicit cue on information processing in anagram solving task]. Eksperimental’naja psihologija=Experimental Psychology, 2017. Vol. 10, no. 1, pp. 23—37. DOI:10.17759/exppsy.2017100103. (In Russ.).
  5. Moroshkina N.V. Vlijanie konflikta implicitnyh i jeksplicitnyh znanij subekta na rezul’taty nauchenija v zadache klassifikacii [Influence of the Conflict of Iimplicit and Explicit Knowledge of a Subject on the Results of Learning Process in Classification Task] Eksperimental’naja psihologija=Experimental Psychology, 2013, no 3, pp. 62—73. (In Russ.).
  6. Moroshkina N.V., Gershkovich V.A. Aktual’nye tendencii v issledovanii implicitnogo nauchenija [Current Tendencies in Implicit Learning Studies]. Vestnik SPbGU=Vestnik of Saint Petersburg University. Serija 16: Psihologija. Pedagogika, 2014, no 4, pp. 14—24. (In Russ.).
  7. Puzyrev A.V. Anagrammy kak javlenie jazyka: Opyt sistemnogo osmyslenija [Anagrams as a Phenomenon of Language: the Experience of System Understanding]. Moscow; Penza: In-t jazykoznanija RAN, PGPU im. V.G. Belinskogo, 1995. 378 p. (In Russ.).
  8. Utochkin I.S., Jurevich M.A., Bulatova M.E. Zritel’naja rabochaja pamjat’: metody, issledovanija, teorii [Visual Working Memory: Methods, Research, Theory]. Rossijskij zhurnal kognitivnoj nauki=The Russian Journal of Cognitive Science, 2016, Vol. 3, no 3, pp. 58—76. Available at: http://www.cogjournal.ru/3/3/ pdf/UtochkinYurevichBulatovaRJCS2016.pdf (Accessed 10.10.2019). (In Russ.).
  9. Baddeley A. The episodic buffer: a new component of working memory. Trends in Cognitive Sciences, 2000. Vol. 4 (11), pp. 417—423. DOI:10.1016/S1364-6613(00)01538-2
  10. Baddeley A.D., Hitch G. Working memory. Psychology of Learning and Motivation, 1974. Vol. 8, pp. 47— 89. DOI:10.1016/S0079-7421(08)60452-1
  11. Bright J.E.H., Burton A.M. Past midnight: Semantic processing in an implicit learning task. Quarterly Journal of Experimental Psychology, 1994. Vol. 47A, pp. 71—89. DOI:10.1080/14640749408401144
  12. Cleeremans A. Connecting Conscious and Unconscious Processing. Cognitive Science, 2014. Рp. 1—30. DOI:10.1111/cogs.12149
  13. Cock, J.J., Berry, D.C., Gaffan, E.A. New strings for old: The role of similarity processing in an incidental learning task. Quarterly Journal of Experimental Psychology, 1994. Vol. 47A, pp. 1015—1034. DOI:10.1080/14640749408401105
  14. Jacoby L.L., Dallas M. On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Pyschology: General, 1981. Vol. 110 (3), pp. 306—340. DOI:10.1037/0096-3445.110.3.306
  15. Kaplan I. T., Schoenfeld W. N. Oculomotor patterns during the solution of visually displayed anagrams // Journal of Experimental Psychology, 1966. Vol. 72(3). P. 447—451. DOI:10.1037/h0023632
  16. Kelly S.W., Wilkin K. A dual-process account of digit invariance learning. Quarterly Journal of Experimental Psychology, 2006. Vol. 59, pp. 1664-1680. DOI:10.1080/17470210500303839
  17. Lewicki P. Processing information about covariations that cannot be articulated. Journal of Experimental Psychology: Learning, Memory and Cognition, 1986. Vol. 12 (l), pp. 135—146. DOI:10.1037/0278- 7393.12.1.135
  18. Luchins A.S. Mechanization in problem solving: The effect of Einstellung. Psychological Monographs, 1942. Vol. 54, no. 6, pp. 1—95. DOI:10.1037/h0093502
  19. Luchins A.S., Luchins E.H. New experimental attempts at preventing mechanisation in problem solving. Journal of General Psychology, 1950. Vol. 42, pp. 279—297. DOI:10.1080/00221309.1950.9920160
  20. Massing M., Blandin Y., Panzer S. (2016). Magnifying visual target information and the role of eye movements in motor sequence learning // Acta Psychologica. 2016. Vol. 163, pp. 59—64. DOI:10.1016/j. actpsy.2015.11.004
  21. McGeorge P., Burton A.M. Semantic processing in an incidental learning task. The Quarterly Journal of Experimental Psychology, 1990. Vol. 42A, pp. 597—609. DOI:10.1080/14640749008401239
  22. Newell B.R., Bright J.E.H. Evidence against hyperspeci-city in implicit invariance learning. Quarterly Journal of Experimental Psychology, 2002. Vol.55A, pp. 1109—1126. DOI:10.1080/02724980244000062
  23. Newell B.R., Bright J.E.H. Well past midnight: Calling time on implicit invariant learning? European Journal of Cognitive Psychology, 2002. Vol.14(2), pp. 185—205. DOI:10.1080/09541440143000023
  24. Öllinger M., Jones G., Knoblich G. Investigating the Effect of Mental Set on Insight Problem Solving // Experimental Psychology, 2008. Vol. 55(4), pp. 269—282. DOI:10.1027/1618-3169.55.4.269
  25. Perruchet P., Pacteau C. Synthetic grammar learning: Implicit rule abstraction or explicit fragmentary knowledge? Journal of Experimental Psychology: General, 1990. Vol. 119 (3), pp. 264—275. DOI:10.1037/0096-3445.119.3.264
  26. Remillard G. Pure perceptual-based sequence learning // Journal of Experimental Psychology: Learning, Memory, and Cognition. 2003. Vol. 29(4). P. 581—597. DOI:10.1037/0278-7393.29.4.581
  27. Sanderson P. Verbal knowledge and skilled task performance: Association, dissociation and mental models. Journal of Experimental Psychology: Learning, Memory and Cognition, 1989. Vol. 15 (4), pp. 729— 747. DOI:10.1037/0278-7393.15.4.729
  28. Shanks D.R., John M.F.St. Characteristics of dissociable human learning systems. Behavioral and Brain Sciences, 1994. No. 17, pp. 367—447. DOI:10.1017/S0140525X00035032

Information About the Authors

Tatiana M. Deeva, Candidate of the Academic Degree, Institute of Psychology, Russian Academy of Sciences, Samara, Russia, ORCID: https://orcid.org/0000-0002-6250-7152, e-mail: tatianadeeva@yandex.ru

D. D. Kozlov, Senior Lecturer of the Department of Social Psychology, Samara National Research University, Samara, Russia, ORCID: https://orcid.org/0000-0001-9768-5584, e-mail: ddkozlov@gmail.com

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