People are remarkably smart: They use language, possess complex motor skills, make nontrivial inferences, develop and use scientific theories, make laws, and adapt to complex dynamic environments. Much of this knowledge requires concepts and this study focuses on how people acquire concepts. It is argued that conceptual development progresses from simple perceptual grouping to highly abstract scientific concepts. This proposal of conceptual development has four parts. First, it is argued that categories in the world have different structure. Second, there might (...) be different learning systems that evolved to learn categories of differing structures. Third, these systems exhibit differential maturational course, which affects how categories of different structures are learned in the course of development. And finally, an interaction of these components may result in the developmental transition from perceptual groupings to more abstract concepts. This study reviews a large body of empirical evidence supporting this proposal. (shrink)

Although it is well documented that language plays an important role in cognitive development, there are different views concerning the mechanisms underlying these effects. Some argue that even early in development, effects of words stem from top‐down knowledge, whereas others argue that these effects stem from auditory input affecting attention allocated to visual input. Previous research (e.g., Robinson & Sloutsky, 2004a) demonstrated that non‐speech sounds attenuate processing of corresponding visual input at 8, 12, and 16 months of age, whereas the (...) current study demonstrates that words attenuate visual processing at 10 months but not at 16 months (Experiment 1). Furthermore, prefamiliarization with non‐speech sounds (Experiment 2) resulted in able processing of visual input by 16‐month‐olds. These findings suggest that some effects of labels found early in development may stem from familiarity with human speech. The possibility of general‐auditory factors underlying the effects of words on cognitive development is discussed. (shrink)

Numerous studies have found that selective attention affects category learning. However, previous research did not distinguish between the contribution of focusing and filtering components of selective attention. This study addresses this issue by examining how components of selective attention affect category representation. Participants first learned a rule‐plus‐similarity category structure, and then were presented with category priming followed by categorization and recognition tests. Additionally, to evaluate the involvement of focusing and filtering, we fit models with different attentional mechanisms to the data. (...) In Experiment 1, participants received rule‐based category training, with specific emphasis on a single deterministic feature (D feature). Experiment 2 added a recognition test to examine participants’ memory for features. Both experiments indicated that participants categorized items based solely on the D feature, showed greater memory for the D feature, were primed exclusively by the D feature without interference from probabilistic features (P features), and were better fit by models with focusing and at least one type of filtering mechanism. The results indicated that selective attention distorted category representation by highlighting the D feature and attenuating P features. To examine whether the distorted representation was specific to rule‐based training, Experiment 3 introduced training, emphasizing all features. Under such training, participants were no longer primed by the D feature, they remembered all features well, and they were better fit by the model assuming only focusing but no filtering process. The results coupled with modeling provide novel evidence that while both focusing and filtering contribute to category representation, filtering can also result in representational distortion. (shrink)

It is unclear how an argumentative environment would select for better reasoning given three general findings. First, argument rationality typically fails to persuade poor reasoners. Second, reasoned argumentation competes with more persuasive and less rational arguments for limited cognitive resources. Third, those poor at reasoning fail to distinguish between valid and invalid arguments. Reasoning, therefore, is poorly designed for argument.

The commentary discusses three components of the target proposal: (1) analogy as a host of phenomena, (2) relations as transformations, and (3) analogy as priming. The commentary argues that the first component is potentially productive, but it has yet to be fully developed, whereas the second and third components do not have an obvious way of accounting for multiple counterexamples.