This study examined two possible bases for grammatical judgments following syntactical learning: unconscious representations of a formal grammar, as in Reber's (1976) hypothesis of implicit learning, and conscious rules within informal grammars. Experimental subjects inspected strings generated by a finite-state grammar, viewed either one at a time or all at a time, with implicit or explicit learning instructions. In a transfer test, experimental and control subjects judged the grammatically of grammatical and nongrammatical strings, reporting on every trial the bases for their judgments. In replication of others' results, experimental subjects met the critical test for grammatical abstraction: significantly correct classification of novel strings. We found, however, that reported rules predicted those grammatical judgments without significant residual. Subjects evidently acquired correlated grammars, personal sets of conscious rules, each of limited scope and many of imperfect validity. Those rules themselves were shown to embody abstractions, consciously represented novelty that could account for abstraction embodied in judgments. The better explanation of these results, we argue, credits grammatical judgments to conscious rules within informal grammars rather than to unconscious representations of a formal grammar.

Recent studies of concept formation using ill-defined categories suggest that abstraction of category-level information is more or less an automatic consequence of experience with exemplars. An experiment using ill-defined categories composed of photographs of women was designed to test this assumption. Experimental manipulations required subjects to learn either identification (exemplar level) and/ or classification (category level) responses to the photographs. Exemplar learning was generally found to proceed faster and with fewer errors than did category learning, and depending on the specific procedural manipulation, abstraction ranged from good to poor. Interactive-and independent-cue models were applied to the transfer data. The fits of the models indicated that when abstraction was good (as defined by transfer performance), the interactive-cue model best characterized the results; as degree of abstraction declined, the independent-cue model performed best. The results were discussed in terms of the relative contributions of categorylevel and exemplar-specific (idiosyncratic) information during classification learning.A considerable amount of recent research has been directed at the question of how people learn about and use ill-defined or "fuzzy" concepts and categories (see Mervis & Rosch, 1981; Smith & Medin, 1981, for reviews). A common theme running through virtually all these studies is the assumption, either implicit or explicit, that abstraction is more or less an automatic consequence of experience with exemplars of a category. It is well known in the literature on problem solving that transfer between two problems having the same underlying structure is often far from perfect (e.g., Reed, Ernst, & Banerji, 1974), and one might expect similar limitations in the learning of ill-defined concepts. Nonetheless, research on learning fuzzy concepts has focused on the what of abstraction, not the whether. Candidates for the what of abstraction include a prototype representing the central tendency of a category, simple or conjoint feature frequency, complex hypotheses or descriptions, best examples, or even the exemplars themselves (e.g.,

No abstract

This article reformulates and reanalyzes a problem originally put forth by Homa, Sterling, and Trepel (1981). The question is whether a pure, exemplar-based abstraction process is an adequate model of category learning or whether it is necessary to postulate an additional prototype-abstraction process. Based on quantitative discrepancies from a pure, exemplar-based model, Homa et al. argued that it was necessary to recognize the operation of a prototype-abstraction process in order to fully explain their results. However, Homa et al. never actually fit the exemplar plus prototype model to the data to determine if indeed the additional prototype process could explain the deviations from the pure exemplar model. The present article compared the pure exemplar model with a mixed (exemplar plus prototype) model and did not find consistent evidence requiring the postulation of an additional prototype-abstraction process. These results point out the difficulty of distinguishing alternative classification models and underscore the need for careful analytic work in this area.

In this article we examine Reber, Allen, and Regan's (1985) commentary on our analysis of consciousness and abstraction in a case of syntactical learning and judgment (Dulany, Carlson, & Dewey, 1984). We reject their methodological criticism; it is not recall, but assessment at the moment of judgment, that maximizes the validity of reports of rules in consciousness at many moments of judgment. Furthermore, as our computer simulations show, if subjects' reports were merely guessed justifications of unconsciously controlled judgments, the obtained relation of rules to judgments is an event so deviant as to be expected about once in 10 billion occasions. In addition, we discuss a number of broader issues raised by our analysis and their response: judgment after early learning and after automatization, correlated grammars and consciousness, the scope and mental abstractness of rules, conscious and unconscious control, and intuition. Although Reber et al. raise questions that should be examined, we find no reason to revise the interpretation of our experiment.