According to the mental model theory, reasoners build an initial model representing the information given in the premises. In the context of relational reasoning, the question arises as to which kind of representation is used to cope with indeterminate or multimodel problems. The present article presents an array of possible answers arising from the initial construction of complete explicit models, partial explicit models, partial implicit models, a single "isomeric" model, or a single annotated model. Predictions generated from these views are tested in two experiments that vary the problem structure and the number of models consistent with the premises. Analyses of the premise processing times, answering times and accuracy show that the annotated model yields the best fit of the data. Implications of these findings for the mental model theory as developed for relational reasoning are discussed.In linear syllogisms such as George is heavier than Tony and Tony is heavier than Jacques, people easily infer that George is heavier than Jacques. The findings collected in numerous studies substantiate the hypothesis that people solve such problems by constructing a linear array with the largest values at the top and the smallest ones at the bottom or alternatively by constructing a left-to-right array (see, e.g., De Soto, London, & Handel, 1965;Huttenlocher, 1968;Potts, 1974). The review by Evans, Newstead, and Byrne (1993, chap. 6) shows that this view yields the best summary of the findings reported in the literature. The usage of such an integrated spatial representation seems to be independent of the relational content and works both for determinate problems (as in the example above) and for indeterminate problems as, for example, in George is heavier than Jacques and George is heavier than Tony, where the relation between Jacques and Tony remains unresolved. Support for all this has been accumulated in
This field study tested whether the basking-in-reflected-glory phenomenon would emerge in a political context. Two days before the general elections in Flanders (Belgium), 3 urban regions were systematically surveyed by 10 observers. These observers unobtrusively registered the addresses of private houses that displayed at least 1 poster (N = 482) or 1 removable lawn sign (N = 180) supporting a political party. The day after the elections, the observers checked whether the registered houses still displayed their poster(s) or lawn sign(s). A strongly positive linear relation was found between the proportional win-loss of the various political parties (compared with the previous elections) and the percentage of houses that continued to exhibit the poster(s) or lawn sign(s) in favor of that party: The better the election result, the more houses that still displayed their poster(s) or lawn sign(s). Two complementary processes seem to account for the observations: a tendency to flaunt one's association with a triumphant party (i.e., basking-in-reflected-glory) and a tendency to conceal one's association with a defeated party (i.e., cutting-off-reflected-failure). A follow-up indicated that basking-in-reflected-glory lasted for at least 1 week after the elections.The concept of basking-in-reflected-glory (BIRG) refers to a tendency of people to display or accentuate their association with successful others. This phenomenon has been demon-
This paper reports four experiments investigating whether model construction of linear reasoning problems is open to strategic decisions. A reversed choice/nochoice paradigm was used in which reasoners first had to apply two model construction strategies (acronym and rehearsal strategy) to two problem sets. Next, they could choose freely among the two strategies to apply to a new problem set. Experiment 1 showed that reasoners selected the strategy that they experienced as the most accurate one in the no-choice phase. Moreover, in Experiment 2, it was found that reasoners adapted their strategy choice to changing problem features, to use the most suitable strategy for premise encoding. Experiments 3 and 4 generalised these findings to more complex linear reasoning problems with a mixed sentence frame and a semi-continuous presentation of the premises, and to two-model problems. On the basis of these results, we argue that strategic decisions influence model construction in linear reasoning.For a long time, research in deductive reasoning has been driven by intense debates on the nature of the reasoning mechanism underlying all types of deductive reasoning. The heart of this controversy concerned the question of whether reasoning involves the syntactic application of natural deduction rules (mental rule theories; e.g., Rips, 1994) or is based upon the construction and manipulation of mental models representing the
In 2 experiments, time-accuracy curves were derived for recall and recognition from episodic memory for both young and older adults. In Experiment 1, time-accuracy functions were estimated for free list recall and list recall cued by rhyme words or semantic associations for 13 young and 13 older participants. In Experiment 2, time-accuracy functions were estimated for recognition of word lists with or without distractor items and with or without articulatory suppression for 29 young and 30 older participants. In both studies, age differences were found in the asymptote (i.e., the maximum level of performance attainable) and in the rate of approach toward the asymptote (i.e., the steepness of the curve). These two parameters were only modestly correlated. In Experiment 2, it was found that 89% of the age-related variance in the rate of approach and 62% of the age-related variance in the asymptote was explained by perceptual speed. The data point at the existence of 2 distinct effects of aging on episodic memory, namely a dynamic effect (growing slower) and an asymptotic effect (growing less accurate). The absence of Age x Condition interactions in the age-related parameters in either experiment points at the rather general nature of both aging effects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with đŸ’™ for researchers
Part of the Research Solutions Family.