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)

With S.S. Stevens, operationism became an important influence in psychology. In this paper I discuss the differences between Bridgman's and Stevens' proposals on operationism and the role that operational definitions play in scientific theory. I discuss how Stevens' notions of the basic act of discrimination and of the relation procedure–outcome influenced B.F. Skinner's criteria under which the main conceptual distinctions in operant psychology were formulated. The operational origin of the dichotomies between respondent and operant behavior, contingency-shaped and rulegoverned behavior, private (...) and public events, and verbal and nonverbal behavior are examined. (shrink)

A description of the author's application of protocol analysis in the teaching of philosophy.

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)

Argues that the path to the good life does not consist in working toward some abstract concept of the good, but rather by ameliorating the problems of the practices and institutions that make up our practical life.

As interpreted here, Garfinkel's "ethnomethodological experiment" (1967) demonstrates the existence of a social convention by flouting it and observing the consternation and aversive consequences for the perpetrator which that provokes. I suggest that the hostility which behaviorism has provoked throughout its history is evidence that it flouts an important social convention, the convention that, whenever possible, human beings are treated as and must always give the appearance of being rational agents. For these purposes, a rational agent is someone whose behavior (...) is controlled by a logically consistent body of means-end beliefs ("rules" in Skinner's terminology) and complementing desires which between them provide a basis for predicting how the individual will behave and for suggesting what arguments will persuade the agent to modify his or her beliefs and the behavior based upon them. The behaviorist flouts this convention by suggesting that its fictional character makes it unsuitable for the purposes of scientific explanation of behavior. The hostility that this suggestion provokes is evidence of the importance attached by the verbal community both to preserving a consistent and rational connection between what is said and what is done and presenting it as part of the natural order of things. (shrink)

Psychology has benefited from an enormous wealth of knowledge about processes of cognition in relation to how the brain organizes information. Within the categorization literature, this behavior is often explained through theories of memory construction called exemplar theory and prototype theory which are typically based on similarity or rule functions as explanations of how categories emerge. Although these theories work well at modeling highly controlled stimuli in laboratory settings, they often perform less well outside of these settings, such as explaining (...) the emergence of background knowledge processes. In order to explain background knowledge, we present a non-similarity-based post-Skinnerian theory of human language called Relational Frame Theory (RFT) which is rooted in a philosophical world view called functional contextualism (FC). This theory offers a very different interpretation of how categories emerge through the functions of behavior and through contextual cues, which may be of some benefit to existing categorization theories. Specifically, RFT may be able to offer a novel explanation of how background knowledge arises, and we provide some mathematical considerations in order to identify a formal model. Finally, we discuss much of this work within the broader context of general semantic knowledge and artificial intelligence research. (shrink)

The concept of rule-governed behavior is often used in the analysis of problem solving, conceptualization, and thinking. Rule-governed behavior has been described as behavior that is controlled by verbally constructed and transmitted discriminative stimuli. Instructions, advice, and examples are typical instances of rules that govern behavior during acquisition in problem solving situations. Nevertheless, some problems arise in identifying instructions with rules and instructionally-controlled behavior with rule-governed behavior. In this article, I argue that instructions, as instances of constructed discriminative stimuli, are (...) the outcome of abstract stimulus control in humans. Descriptions of contingencies and performance may result from effective performance under abstract stimulus control. Instructions, as stimulus conditions, do not necessarily reproduce the abstract contingencies under which they were constructed. Therefore, instructions and self-instructions do not control abstract behavior. Instructions shape up new effective behavior by prompting and restricting response variation. A conceptual analysis along these arguments suggests that the usefulness of the distinction between rule-governed and contingency-shaped behaviors is questionable. (shrink)