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Application of Implicit Knowledge: Deterministic or Probabilistic? Cover

Application of Implicit Knowledge: Deterministic or Probabilistic?

Open Access
|Jan 1997

Abstract

This paper distinguishes two models specifying the application of implicit knowledge. According to one model, originally suggested by Reber (1967), subjects either apply sufficient knowledge to always produce a correct response or else they guess randomly (High Threshold Theory; subjects only apply knowledge when there is sufficient knowledge to exceed a threshold ensuring a correct response); according to the other model, suggested by Dienes (1992), subjects respond with a certain probability towards each item, where the probability is determined by the match between the items structure and the induced constraints about the structure (Probability Matching Theory; subjects match their probability of responding against their personal probability that the item belongs to a certain category). One parameter versions of both models were specified and then tested against the data generated from three artificial grammar learning experiments. Neither theory could account for all features of the data, and extensions of the theories are suggested.

DOI: https://doi.org/10.5334/pb.910 | Journal eISSN: 0033-2879
Language: English
Published on: Jan 1, 1997
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 1997 Zoltán Dienes, Andreas Kurz, Regina Bernhaupt, Josef Perner, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.