Effects of externalization on representation and recall of indeterminate problems

ive reasoning and problem solving is error-prone. One such pattern is manifested in that people err more often when problems are indeterminate than when problems are determinate W e suggest that an incomplete problem representation could account for the observed pattern of errors. W e further contend that in verbal reasoning such incomplete representation stems from a lack of systematic representations of connectives (e.g., and, or, if, etc.), and, therefore, extemalization of relations denoted by sentential connectives should improve people's representations of multiple possibilities. These predictions were tested in three reported experiments. Results indicate that determinate problems were easier to represent and recall than indeterminate problems. Furthermore, there was a tendency to represent and recall indeterminate problems as if they were determinate ones by fruncating the number of possibilities compatible with the problem. Finally, external aids dramatically improved representation and recall of indeterminate problems. These results are discussed in relation to theories of representation and reasoning

Representation of Logical Form in Memory

Current theories of human deductive reasoning make different claims about the representation of logical statements in memory. Syntactically-based theories claim that abstract logical forms are represented veridically in memory, separate from content, whereas semantic theories propose that naive reasoners represent combinations of possibilities that are based on the content of statements. We tested these predictions in two experiments in which participants had to recall and recognize statements of different logical forms. Results indicate that memory for logical form is not veridical, thus failing to support the syntactic view. In particular, results suggest that naive participants tend, whenever possible, to represent only a single possibility for a statement of any logical form. These findings are consistent with semantic theories of human deductive reasoning and have significant implications for all theories of reasoning

Problem representations and illusions in reasoning

The mental model theory of reasoning postulates that reasoners build models of the situations described in premises, and that these models normally make explicit only what is true. The theory has an unexpected consequence: it predicts the occurrence of inferences that are systematically invalid. These inferences should arise from reasoners failing to take into account what is false. We report an experiment that corroborated the occurrence of these illusory inferences, and that eliminated a number of altemative explanations for them. Results illuminate the controversy among various current theories of reasoning

Experience and maturation : The contribution of co-occurrence regularities in language to the development of semantic organization

With development knowledge becomes organized according to semantic links, including early-developing associative (e.g., juicy-apple) and gradually developing taxonomic links (e.g., apple-pear). Word co-occurrence regularities may foster these links: Associative links may form from direct co-occurrence (e.g., juicy-apple), and taxonomic links from shared co-occurrence (e.g., apple and pear co-occur with juicy). Four experiments (2017-2020) investigated this possibility with 4- to 8-year-olds (N = 148, 82 female) and adults (N = 116, 35 female) in a U.S. city with 58.6% White; 29.0% Black, and 5.8% Asian demographics. Results revealed earlier development of the abilities to form direct (ds > 0.536) than the abilities to form shared co-occurrence-based links (ds > 1.291). We argue that the asynchronous development of abilities to form co-occurrence-based links may explain developmental changes in semantic organization

The Role of Words in Cognitive Tasks: What, When, and How?

The current review focuses on how exposure to linguistic input, and count nouns in particular, affect performance on various cognitive tasks, including individuation, categorization and category learning, and inductive inference. We review two theoretical accounts of effects of words. Proponents of one account argue that words have top-down effects on cognitive tasks, and, as such, function as supervisory signals. Proponents of the other account suggest that early in development, words, just like any other perceptual feature, are first and foremost part of the stimulus input and influence cognitive tasks in a bottom-up, non-supervisory fashion. We then review evidence supporting each account. We conclude that, although much research is needed, there is a large body of evidence indicating that words start out like other perceptual features and become supervisory signals in the course of development

No frills : Simple regularities in language can go a long way in the development of word knowledge

Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of these models raise the intriguing possibility that exposure to word use in language also shapes the word knowledge that children amass during development. However, this possibility is strongly challenged by the fact that models use language input and learning mechanisms that may be unavailable to children. Across three studies, we found that unrealistically complex input and learning mechanisms are unnecessary. Instead, simple regularities of word use in children's language input that they have the capacity to learn can foster knowledge about word meanings. Thus, exposure to language may play a simple but powerful role in children's growing word knowledge. A video abstract of this article can be viewed at https://youtu.be/dT83dmMffnM. RESEARCH HIGHLIGHTS: Natural Language Processing (NLP) models can learn that words are similar in meaning from higher-order statistical regularities of word use. Unlike NLP models, infants and children may primarily learn only simple co-occurrences between words. We show that infants' and children's language input is rich in simple co-occurrence that can support learning similarities in meaning between words. We find that simple co-occurrences can explain infants' and children's knowledge that words are similar in meaning

When is a word in good company for learning?

Although identifying the referents of single words is often cited as a key challenge for getting word learning off the ground, it overlooks the fact that young learners consistently encounter words in the context of other words. How does this company help or hinder word learning? Prior investigations into early word learning from children’s real-world language input have yielded conflicting results, with some influential findings suggesting an advantage for words that keep a diverse company of other words, and others suggesting the opposite. Here, we sought to triangulate the source of this conflict, comparing different measures of diversity and approaches to controlling for correlated effects of word frequency across multiple languages. The results were striking: while different diversity measures on their own yielded conflicting results, once nonlinear relationships with word frequency were controlled, we found convergent evidence that contextual consistency supports early word learning