Two experiments examine the effects of unreportable hints on anagram solving performance and on solvers' subjective experience of insight. In Experiment 1, after seeing a hint presented too briefly to identify, participants solved anagrams preceded by the solution fastest and solved anagrams preceded by unrelated hints slowest. Participants' “warmth” ratings for solution hints were more insight-like than those for unrelated hints. In Experiment 2 a hint, or no hint, was presented at one of three different exposure durations. Participants benefited from (...) solution-relevant hints that were either unreportable or reportable, but showed a cost only for unrelated hints that were reportable. Participants' ratings of their insight experiences showed that unreportable solution and semantically related hints produced more insight-like experiences than did unrelated hints. The results suggest that unreportable processing of solution-related information is important for the insight experience. (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)

Human behavior depends on the ability to effectively introspect about our performance. For simple perceptual decisions, this introspective or metacognitive ability varies substantially across individuals and is correlated with the structure of focal areas in prefrontal cortex. This raises the possibility that the ability to introspect about different perceptual decisions might be mediated by a common cognitive process. To test this hypothesis, we examined whether inter-individual differences in metacognitive ability were correlated across two different perceptual tasks where individuals made judgments (...) about different and unrelated visual stimulus properties. We found that inter-individual differences were strongly correlated between the two tasks for metacognitive ability but not objective performance. Such stability of an individual’s metacognitive ability across different perceptual tasks indicates a general mechanism supporting metacognition independent of the specific task. (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, (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)

Two experiments examine the effects of unreportable hints on anagram solving performance and on solvers' subjective experience of insight. In Experiment 1, after seeing a hint presented too briefly to identify, participants solved anagrams preceded by the solution fastest and solved anagrams preceded by unrelated hints slowest. Participants' “warmth” ratings for solution hints were more insight-like than those for unrelated hints. In Experiment 2 a hint, or no hint, was presented at one of three different exposure durations . Participants benefited (...) from solution-relevant hints that were either unreportable or reportable, but showed a cost only for unrelated hints that were reportable. Participants' ratings of their insight experiences showed that unreportable solution and semantically related hints produced more insight-like experiences than did unrelated hints. The results suggest that unreportable processing of solution-related information is important for the insight experience. (shrink)

ABSTRACTHow accurate are insights compared to analytical solutions? In four experiments, we investigated how participants' solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants' self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, (...) whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants' analytic solutions included relatively more incorrect responses than timeouts compared to their insight responses. (shrink)