Mental Models in Spatial Reasoning

Age differences in syllogistic reasoning in relation to crystallized and fluid ability were studied in 278 adults from 19 to 96 years of age. Two reasoning tasks, the evaluation and the construction of conclusions for syllogisms of varying complexity and believability, a vocabulary test, and 3 tasks of working memory were administered. The magnitude of age-related variance on selected reasoning tasks was only partially reduced by statistically controlling measures of both working memory and vocabulary. Additional age-related effects on reasoning were found to be significantly associated with number of mental models and bias produced by conflict between belief and logic. A significant bias was also found toward acceptance of invalid syllogisms as valid, even when contents were abstract. These sources of error in logic are discussed in relation to Johnson-Laird's (1983) theory of mental models and Evan's (1989) account of bias in human reasoning.

Human reasoning involving quantified statements is one area in which findings from cognitive psychology and linguistic pragmatics complement each other. I will show how mental models theory provides a promising account of the mechanisms underlying peoples’ performance in three types of reasoning tasks involving quantified premises and conclusions. I will further suggest that relevance theory can help to explain the way in which mental models are employed in the reasoning processes. Conversely, mental models theory suggests that human reasoning typically does not involve deductive rules, which in turn entails a modification to the nature of the deductive processes proposed by relevance theory. The mechanism proposed by mental models theory also helps to clarify the nature of the relevance theory distinction between conceptual and procedural information.

Towards explaining the cognitive efficacy of Euler diagrams in syllogistic reasoning: A relational perspective

When solving a simple probabilistic problem, people tend to build an incomplete mental representation. We observe this pattern in responses to probabilistic problems over a set of premises using the conjunction, disjunction, and conditional propositional connectives. The mental model theory of extensional reasoning explains this bias towards underestimating the number of possibilities: In reckoning with different interpretations of the premises (logical rules, mental model theoretical, and, specific to conditional premises, conjunction and biconditional interpretation) the mental model theory accounts for the majority of observations. Different interpretations of a premise result in a build-up of mental models that are often incomplete. These mental models are processed using either an extensional strategy relying on proportions amongst models, or a conflict monitoring strategy. The consequence of considering too few possibilities is an erroneous probability estimate akin to that faced by decision makers who fail to generate and consider all alternatives, a characteristic of bounded rationality. We compare our results to the results published by Johnson-Laird, Legrenzi, Girotto, Legrenzi, and Caverni [Johnson-Laird, P., Legrenzi, P., Girotto, V., Legrenzi, M., & Caverni, J. (1999). Naive probability: A mental model theory of extensional reasoning. Psychological Review, 106, 62-88. doi: 10. 1037/0033-295X.106.1.62], and we observe lower performance levels than those in the original article.

This study is situated within the scope of critical analysis. It examines Moroccan citizens’ cognitive reception of political discourse through a linguistic and socio-cognitive perspective. Focusing on three major political parties representing the country’s principal ideological poles—the CU, PJD, and SUPF—the research investigates how citizens interpret political messages and the cognitive mechanisms underlying their perceptions. Guided by Van Dijk’s (2008) mental model theory, the study explores how participants construct understanding based on personal experiences, cultural knowledge, and socially shared representations. The Data collected via a cognitively structured questionnaire reveal that participants frequently rely on pre-existing mental models shaped by negative episodic memories, social images, and culturally ingrained perceptions. These cognitive patterns result in a persistent misalignment between politicians’ intended discourse and the public’s interpretations. The findings also indicate that participants judge political discourse more by the parties’ perceived social roles than by their actual ideologies, which contributes to fixed perceptions and widespread political disengagement among the Moroccan public. Accordingly, the study highlights the importance of political literacy as a mechanism to align citizens’ mental models with parties’ cognitive frameworks, thereby fostering a more coherent social understanding of Moroccan political messaging.

Syllogistic reasoning, that is the drawing of inferences for categorical-quantified assertions, is one of the oldest branches of deductive reasoning research with a history exceeding 100years. In syllogistic reasoning experiments, "No Valid Conclusion" (NVC) is one of the most frequently selected responses and corresponds to the logically correct conclusion for 58% of the syllogistic problem domain. To date, NVC is often neglected in computational models or just treated as a by-product of the underlying inferential mechanisms such as a last resort when the search for alternatives is exhausted. We illustrate that NVC represents a major shortcoming of current models for human syllogistic reasoning. By introducing heuristic rules for predicting NVC, we demonstrate that simple extensions of the existing models result in substantial improvements in their predictive performances. Our results emphasize the need for better NVC handling in cognitive modeling of human reasoning and provide directions for modelers on how to enhance their approaches.

In this paper, we study the cognitive effectiveness of diagrammatic reasoning with proportional quantifiers such as most. We first examine how Euler-style diagrams can represent syllogistic reasoning with proportional quantifiers, building on previous work on diagrams for the so-called plurative syllogism (Rescher and Gallagher, 1965). We then conduct an experiment to compare performances on syllogistic reasoning tasks of two groups: those who use only linguistic material (two sentential premises and one conclusion) and those who are also given Euler diagrams corresponding to the two premises. Our experiment showed that (a) in both groups, the speed and accuracy of syllogistic reasoning tasks with proportional quantifiers like most were worse than those with standard first-order quantifiers such as all and no, and (b) in both standard and non-standard (proportional) syllogisms, speed and accuracy for the group provided with diagrams were significantly better than the group provided only with sentential premises. These results suggest that syllogistic reasoning with proportional quantifiers like most is cognitively complex, yet can be effectively supported by Euler diagrams that represent the proportionality relationships between sets in a suitable way.

Syllogistic reasoning is important due to the prominence of syllogistic arguments in human reasoning, and also to the role they have played in theory of reasoning from Aristotle onwards. Aristotelian syllogistic logic is a formal study of the meaning of four Aristotelian quantifiers and of their properties. This paper focuses on logical system based on syllogistic reasoning. It firstly formalized the 24 valid Aristotle’s syllogisms, and then has proven that the other 22 valid Aristotle’s syllogisms can be derived from the syllogisms ‘Barbara’ AAA-1 and ‘Celarent’ EAE-1 by means of generalized quantifier theory and set theory, so the paper has completed the axiomatization of Aristotelian syllogistic Logic. This axiomatization needs to make full use of symmetry and transformable relations between/among the monotonicity of the four Aristotelian quantifiers from the perspective of generalized quantifier theory. In fact, these innovative achievements and the method in this paper provide a simple and reasonable mathematical model for studying other generalized syllogisms. It is hoped that the present study will make contributions to the development of generalized quantifier theory, and to bringing about consequences to natural language information processing as well as knowledge representation and reasoning in computer science.

According to the mental models theory, humans reason by constructing, inspecting, and validating mental models of the state of affairs described in the premises. We present a formal framework describing all three phases and testing new predictions about the construction principle humans normally use and about the deduction process itself - the model variation phase. Finally, empirical findings in support of these principles are reported.

Summary form only given. The importance of mental models in complex control tasks is discussed, and the lattice theory of mental models is described. Plans for a series of experiments using a simulation developed with the Lab View programming language to validate the lattice theory of mental models are reported. >

With the swift entry of artificial intelligence (AI) into everyday life, human-product interactions are becoming increasingly complex. We suggest an ecosystem-minded, humanity-centered design approach to better understand this complexity. Simultaneously with the development of interaction types, discussions and developments on theories of mental models are crucial to understanding and improving the nature of these interactions. In this paper, we address the gap in mental model theories and extend Norman's conceptual model at three dialogue levels: dialogue in language, mind, and use.

Our knowledge of Thales of Miletus is fragmentary. We only have very short passages attributed to him by ancient sources, and those passages are not always clearly consistent with each other. In this paper, I analyze some of the most representative ancient fragments with theses assigned to Thales of Miletus by means of a methodology based on the general framework of the unified theory of mental models. My intention in doing that is to try to clarify what he truly thought about water, the soul, and gods, and my conclusions refer to the fact that it is very possible that Thales’ philosophy was much closer to myth than sometimes assumed.

How can mental models theory account for content effects in conditional reasoning? A developmental perspective

Quantified modal inferences interest logicians, linguists, and computer scientists, but no previous psychological study of them appears to be in the literature. Here is an example of one: All those artists are businessmen. Paulo is possibly one of the artists. What follows? People tend to conclude: Paulo is possibly a businessman (Experiment 1). It seems plausible, and it follows from an intuitive mental model in which Paulo is one of a set of artists who are businessmen. Further deliberation can yield a model of an alternative possibility in which Paulo is not one of the artists, which confirms that the conclusion is only a possibility. The snag is that standard modal logics, which deal with possibilities, cannot yield a particular conclusion to any premises: Infinitely many follow validly (from any premises) but they do not include the present conclusion. Yet, further experiments corroborated a new mental model theory's predictions for various inferences (Experiment 2), for the occurrence of factual conclusions drawn from premises about possibilities (Experiment 3) and for inferences from premises of modal syllogisms (Experiment 4). The theory is therefore plausible, but we explore the feasibility of a cognitive theory based on modifications to modal logic.

Mental model theory as a model for analysing visual and multimodal discourse