Advertisement

The Metacognitive Role of Familiarity in Artificial Grammar Learning: Transitions from Unconscious to Conscious Knowledge

  • Ryan Scott
  • Zoltán Dienes

Abstract

We present two methods by which people could learn (e.g., artificial grammars): learning by a single updating model that has the function to reflect how reality is (e.g., the standard types of connectionist models in the implicit learning literature), and learning by the use of considering hypotheticals (hypothesis testing). The first method results in unconscious knowledge of the structure of a domain. Such unconscious structural knowledge can lead to conscious knowledge that new items do (or do not) have that structure (“judgment knowledge”). When unconscious structural knowledge produces conscious judgment knowledge, the phenomenology is of intuition, a common phenomenology in implicit learning experiments. We propose a mechanism by which one becomes aware of judgment knowledge, turning feelings of guessing into those of intuition: feedback in calibrating the accuracy of one’s knowledge of the distribution of familiarity of the test strings. Accurate predictions lead to awareness of knowing, that is, to conscious knowledge. Contrary to some popular beliefs, we argue fluency plays little role in either the expression of unconscious structural knowledge or in the formation of conscious judgment knowledge. The individual difference variable Faith in Intuition was not associated with better implicit learning but it was associated with sensitivity to familiarity and the metacognitive processes by which judgment knowledge can be made conscious: that is, by which feelings of intuition are formed.

Keywords

Implicit Learning Test String Incidental Learning Response Stimulus Interval Familiarity Rating 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Buchner, A. (1994). Indirect effects of synthetic grammar learning in an identification task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(3), 550–566.CrossRefGoogle Scholar
  2. Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131.CrossRefGoogle Scholar
  3. Carruthers, P. (2000). Phenomenal consciousness: A naturalistic theory. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  4. Chomsky, N. (1957). Syntactic structures. The Hague, The Netherlands: Mouton.Google Scholar
  5. Chrisley, R., & Parthemore, J. (2007) Synthetic phenomenology: Exploiting embodiment to specify the non-conceptual content of visual experience. Journal of Consciousness Studies 14, 44–58.Google Scholar
  6. Cleeremans, A., & Dienes, Z. (2008). Computational models of implicit learning. In R. Sun (Ed.), Handbook of computational cognitive modeling (pp. 396–421). Cambridge, UK: Cambridge: University Press.Google Scholar
  7. Cleeremans, A., & Jiménez, L. (2002). Implicit learning and consciousness: A graded, dynamic perspective. In R. M. French & A. Cleeremans (Eds.), Implicit learning and consciousness (pp. 1–40). Hove, UK: Psychology Press.Google Scholar
  8. Destrebecqz, A., & Cleeremans, A. (2001). Can sequence learning be implicit? New evidence with the process dissociation procedure. Psychonomic Bulletin and Review, 8(2), 343–350.CrossRefGoogle Scholar
  9. Dienes, Z. (2008). Subjective measures of unconscious knowledge. Models of Brain and Mind: Physical, Computational and Psychological Approaches, 168, 49–64.CrossRefGoogle Scholar
  10. Dienes, Z., Altmann, G. T. M., Kwan, L., & Goode, A. (1995). Unconscious knowledge of artificial grammars is applied strategically. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(5), 1322–1338.CrossRefGoogle Scholar
  11. Dienes, Z., & Perner, J. (1999) A theory of implicit and explicit knowledge. Behavioural and Brain Sciences, 22, 735–755.CrossRefGoogle Scholar
  12. Dienes, Z., & Scott, R. (2005). Measuring unconscious knowledge: Distinguishing structural knowledge and judgment knowledge. Psychological Research, 69(5–6), 338–351.CrossRefGoogle Scholar
  13. Dulany, D. E. (1997). Consciousness in the explicit (deliberative) and implicit (evocative). In J. Cohen & J. Schooler (Eds.), Scientific approaches to consciousness (pp. 179–212). Mahwah, NJ: Erlbaum.Google Scholar
  14. Dulany, D. E., Carlson, R. A., & Dewey, G. I. (1984). A case of syntactical learning and judgment: How conscious and how abstract? Journal of Experimental Psychology: General, 113(4), 541–555.CrossRefGoogle Scholar
  15. Epstein, S. (1983). The unconscious, the preconscious and the self-concept. In J. Suls & A. Greenwald (Eds.), Psychological perspectives on the self (Vol. 2, pp. 219–247). Hillsdale, NJ: Erlbaum.Google Scholar
  16. Epstein, S., Pacini, R., Denes Raj, V., & Heier, H. (1996). Individual differences in intuitive-experiential and analytical-rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390–405.CrossRefGoogle Scholar
  17. Evans, J. S. B. T., & Over, D. E. (1999). Rationality and reasoning. Hove, UK: Psychology Press.Google Scholar
  18. Fu, Q., Fu, X., & Dienes, Z. (2008). Implicit sequence learning and conscious awareness. Consciousness and Cognition, 17(1), 185–202.CrossRefGoogle Scholar
  19. Gray, J. A. (1995). The contents of consciousness: A neuropsychological conjecture. Behavioral and Brain Sciences, 18(4), 659–722.CrossRefGoogle Scholar
  20. Higham, P. A., Vokey, J. R., & Pritchard, J. (2000). Beyond dissociation logic: Evidence for controlled and automatic influences in artificial grammar learning. Journal of Experimental Psychology: General, 129(4), 457–470.CrossRefGoogle Scholar
  21. Jacoby, L. L., & Dallas, M. (1981). On the relationship between autobiographical memory and perceptual learning. Journal of Experimental Psychology: General, 110, 306–340.CrossRefGoogle Scholar
  22. Jacoby, L. L., & Whitehouse, K. (1989). An illusion of memory: False recognition influenced by unconscious perception. Journal of Experimental Psychology: General, 118(2), 126–135.CrossRefGoogle Scholar
  23. Jacoby, L. L. (1991). A process dissociation framework: Separating automatic from intentional uses of memory. Journal of Memory and Language, 30(5), 513–541.CrossRefGoogle Scholar
  24. Jiménez, L. (Ed.). (2003). Attention and implicit learning. Amsterdam: Benjamins.Google Scholar
  25. Kinder, A., & Assmann, A. (2000). Learning artificial grammars: No evidence for the acquisition of rules. Memory and Cognition, 28(8), 1321–1332.CrossRefGoogle Scholar
  26. Kinder, A., Shanks, D. R., Cock, J., & Tunney, R. J. (2003). Recollection, fluency, and the explicit/implicit distinction in artificial grammar learning. Journal of Experimental Psychology: General, 132(4), 551–565.CrossRefGoogle Scholar
  27. Knowlton, B. J., & Squire, L. R. (1996). Artificial grammar learning depends on implicit acquisition of both abstract and exemplar-specific information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(1), 169–181.CrossRefGoogle Scholar
  28. Kuhn, G., & Dienes, Z. (2005). Implicit learning of nonlocal musical rules: Implicitly learning more than chunks. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(6), 1417–1432.CrossRefGoogle Scholar
  29. Lau, H. C. (2008). A higher order Bayesian decision theory of consciousness. Models of Brain and Mind: Physical, Computational and Psychological Approaches, 168, 35–48.CrossRefGoogle Scholar
  30. Lotz, A., & Kinder, A. (2006). Transfer in artificial grammar learning: The role of repetition information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(4), 707–715.CrossRefGoogle Scholar
  31. Meulemans, T., & Van der Linden, M. (1997). Associative chunk strength in artificial grammar learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(4), 1007–1028.CrossRefGoogle Scholar
  32. Norman, E., Price, M. C., & Duff, S. C. (2006). Fringe consciousness in sequence learning: The influence of individual differences. Consciousness and Cognition, 15, 723–760.CrossRefGoogle Scholar
  33. Norman, E., Price, M. C., Duff, S. C., & Mentzoni, R. A. (2007). Gradations of awareness in a modified sequence learning task. Consciousness and Cognition, 16, 809–837.CrossRefGoogle Scholar
  34. O’Regan, J. K., & Noe, A. (2001). A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences, 24(5), 939–973.CrossRefGoogle Scholar
  35. Pacini, R., & Epstein, S. (1999). The relation of rational and experiential information processing styles to personality, basic beliefs, and the ratio-bias phenomenon. Journal of Personality and Social Psychology, 76(6), 972–987.CrossRefGoogle Scholar
  36. Perner, J. (1991). Understanding the representational mind. Cambridge, MA: MIT Press.Google Scholar
  37. Perruchet, P., & Vinter, A. (2002). The self-organizing consciousness. Behavioral and Brain Sciences, 25(3), 297–388.Google Scholar
  38. Reber, A. S. (1967). Implicit learning of artificial grammars. Journal of Verbal Learning and Verbal Behavior, 6(6), 855–863.CrossRefGoogle Scholar
  39. Reber, A. S. (1976). Implicit learning of synthetic languages: The role of instructional set. Journal of Experimental Psychology: Human Learning and Memory, 2, 88–94.CrossRefGoogle Scholar
  40. Reber, A. S. (1989). Implicit learning and tacit knowledge. Journal of Experimental Psychology: General, 118, 219–235.CrossRefGoogle Scholar
  41. Reber, A. S., & Lewis, S. (1977). Implicit learning: An analysis of the form and structure of a body of tacit knowledge. Cognition, 114, 14–24.Google Scholar
  42. Redington, M., Friend, M., & Chater, N. (1996, July). Confidence judgments, performance, and practice, in artificial grammar learning. Paper presented at the Eighteenth Annual Conference of the Cognitive Science Society, Mawah, New Jersey.Google Scholar
  43. Rosenthal, D. (1986). Two concepts of consciousness. Philosophical Studies, 49(3), 329–359.CrossRefGoogle Scholar
  44. Rosenthal, D. M. (2005). Consciousness and mind. Oxford, England: Clarendon.Google Scholar
  45. Scott, R., & Dienes, Z. (2008). The conscious, the unconscious, and familiarity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34(5), 1264–1288.CrossRefGoogle Scholar
  46. Scott, R., & Dienes, Z. (2009). Fluency does not express implicit knowledge of artificial grammars. Manuscript submitted for publication. Google Scholar
  47. Servan Schreiber, E., & Anderson, J. R. (1990). Learning artificial grammars with competitive chunking. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(4), 592–608.CrossRefGoogle Scholar
  48. Shanks, D. R. (2005a). Connectionist models of basic human learning processes. In G. Houghton (Ed.), Connectionist models in cognitive psychology (pp. 45–82). Hove, UK: Psychology Press.Google Scholar
  49. Shanks, D. R. (2005b). Implicit learning. In K. Lamberts & R. Goldstone (Eds.), Handbook of cognition (pp. 202–220). London: Sage.Google Scholar
  50. Shanks, D. R., & St. John, M. F. (1994). Characteristics of dissociable human learning systems. Behavioral & Brain Sciences, 17, 367–447.CrossRefGoogle Scholar
  51. Sun, R. (2002). Duality of the mind. Mahwah, NJ: Erlbaum.Google Scholar
  52. Tanaka, D., Kiyokawa, S., Yamada, A., Dienes, Z., & Shigemasu, K. (2008). Role of selective attention in artificial grammar learning. Psychonomic Bulletin and Review, 15, 1154–1159.CrossRefGoogle Scholar
  53. Wan, L. L., Dienes, Z., & Fu, X. L. (2008). Intentional control based on familiarity in artificial grammar learning. Consciousness and Cognition, 17(4), 1209–1218.CrossRefGoogle Scholar
  54. Wilkinson, L., & Shanks, D. R. (2004). Intentional control and implicit sequence learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2), 354–369.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of SussexBrightonUK

Personalised recommendations