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. (shrink)

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, between learning that takes place with versus without concurrent awareness, and between learning that involves the encoding of instances 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 is predominantly based on rule abstraction is questionable. When subjects cannot report the “implicitly learned” 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. (shrink)

Evaluative conditioning (EC) is one of the terms that is used to refer to associatively induced changes in liking. Many controversies have arisen in the literature on EC. Do associatively induced changes in liking actually exist? Does EC depend on awareness of the fact that stimuli are associated? Is EC resistant to extinction? Does attention help or hinder EC? As an introduction to this special issue, we will discuss the extent to which the papers that are published in this issue (...) help to resolve some of the controversies that surround EC. We also speculate about possible boundary conditions of EC and attempt to reconcile conflicting results on the functional properties of EC. (shrink)

Evaluative learning refers to the change in the affective evaluation of a previously neutral stimulus that occurs after the stimulus has been associated with a second, positive or negative, affective stimulus . Four experiments are reported in which the AS was presented very briefly. Significant evaluative learning was observed in participants who did not notice the presentation of the affective stimuli or could not discriminate between the briefly presented positive and negative ASi when asked to do so . In two (...) other experiments , no significant learning effect was obtained. A meta-analysis performed on the present and previously reported results gave evidence for a small, though statistically reliable evaluative learning effect when ASi are presented “subliminally.” This finding supports the hypothesis that evaluative associations can be learned implicitly. (shrink)