David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Behavioral and Brain Sciences 17 (3):367-447 (1994)
A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, (1) between learning that takes place with versus without concurrent awareness, and (2) between learning that involves the encoding of instances (or fragments) versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning derived from subliminal learning, conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks (e.g., artificial grammar learning) is predominantly based on rule abstraction is questionable. When subjects cannot report the rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning
|Keywords||artificial grammar categorization connectionism consciousness explicit/implicit processes instances learning memory rules|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Sascha Topolinski & Fritz Strack (2009). Scanning the “Fringe” of Consciousness: What is Felt and What is Not Felt in Intuitions About Semantic Coherence. Consciousness and Cognition 18 (3):608-618.
Nick Reed, Peter McLeod & Zoltan Dienes (2010). Implicit Knowledge and Motor Skill: What People Who Know How to Catch Don't Know. Consciousness and Cognition 19 (1):63-76.
Hilde Haider, Alexandra Eichler & Thorsten Lange (2011). An Old Problem: How Can We Distinguish Between Conscious and Unconscious Knowledge Acquired in an Implicit Learning Task? Consciousness and Cognition 20 (3):658-672.
Ben R. Newell (2009). What is the Link Between Propositions and Memories? Behavioral and Brain Sciences 32 (2):219-219.
Michał Wierzchoń, Dariusz Asanowicz, Borysław Paulewicz & Axel Cleeremans (2012). Subjective Measures of Consciousness in Artificial Grammar Learning Task. Consciousness and Cognition 21 (3):1141-1153.
Similar books and articles
Peter F. Dominey (1997). Reducing Problem Complexity by Analogical Transfer. Behavioral and Brain Sciences 20 (1):71-72.
Myles Bogner, Uma Ramamurthy & Stan Franklin (2000). Consciousness and Conceptual Learning in a Socially Situated Agent. In Kerstin Dauthenhahn (ed.), Human Cognition and Social Agent Technology. Amsterdam: John Benjamins Publishing Company 113--135.
James R. Blair & Karina S. Perschardt (2001). Empathy: A Unitary Circuit or a Set of Dissociable Neuro-Cognitive Systems? Behavioral and Brain Sciences 25 (1):27-28.
Michael Tetzlaff & Peter Carruthers (2008). Languages of Thought Need to Be Distinguished From Learning Mechanisms, and Nothing yet Rules Out Multiple Distinctively Human Learning Systems. Behavioral and Brain Sciences 31 (2):148-149.
Yoshihide Horiuchi (2003). Alice in Systems Wonderland: A Children's Systems Learning Guidebook Accompanying Alice's Adventures in Wonderland. World Futures 59 (1):37 – 50.
Simon Killcross (2000). Reinforcement and Punishment: Dissociable Systems for Action and Emotion? Behavioral and Brain Sciences 23 (2):205-205.
Pierre Poirier (2005). Atomistic Learning in Non-Modular Systems. Philosophical Psychology 18 (3):313-325.
James Blackmon, David Byrd, Robert C. Cummins, Pierre Poirier & Martin Roth (2005). Atomistic Learning in Non-Modular Systems. Philosophical Psychology 18 (3):313-325.
David C. Noelle (1999). Explicit to Whom? Accessibility, Representational Homogeneity, and Dissociable Learning Mechanisms. Behavioral and Brain Sciences 22 (5):777-778.
Added to index2009-01-28
Total downloads112 ( #15,173 of 1,700,324 )
Recent downloads (6 months)4 ( #161,079 of 1,700,324 )
How can I increase my downloads?