Modeling something that is believed to be false: the competition of scripts and models in linear reasoning

This chapter studies the effect of the believability of a temporal ordering described by linear reasoning problems on model construction and on model maintenance. It appears harder to process premises stating an unbelievable ordering than premises stating a believable or an arbitrary ordering. Furthermore, conclusion evaluation on the basis of an unbelievable model is less accurate and slower than on the basis of a believable or neutral model. These disrupting effects prove to be quite robust and hard to control. Taken together, the findings presented in the chapter indicate that the content of the model is an important factor affecting reasoning performance

Growing slower and less accurate: Adult age differences in time-accuracy functions for recall and recognition from episodic memory

In 2 experiments, time-accuracy curves were derived for recall and recognition from episodic memory for 42 young and 43 older adults. In Exp 1, time-accuracy functions were estimated for free list recall and list recall cued by rhyme words or semantic associations; in Exp 2, time-accuracy functions were estimated for recognition of word lists with or without distractor items and with or without articulatory suppression. 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 2 parameters were only modestly correlated. In Exp 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 × Condition interactions in the age-related parameters in either experiment points at the rather general nature of both aging effects. (PsycInfo Database Record (c) 2022 APA, all rights reserved)info:eu-repo/semantics/publishe

Model construction and elaboration in spatial linear syllogisms

When faced with linear syllogisms, reasoners usually construct an integrated spatial representation of the premise content. As a consequence multi-model problems are mon difficult than one-model problems, because the representation is more complex in multi-model problems. In the present chapter, the question is raised whether three-model problems are indeed more difficult than two-model problems. Data show that there is a reliable difference between two-model and three-model problems. However, the difference is so small that it cannot be explained by assuming that the reasoner builds an explicit representation of all three models. Overall, the last premise, the one that discloses the multi-model nature of the problem, requires more reading and processing time than other premises, and this difference is larger in multi-model than in one-model problems. The data suggest that the representation constructed leaves the additional models implicit by entering a marker that can be easily fleshed out when needed