How we Reason

Johnson‐Laird, P. N.

doi:10.1093/acprof:oso/9780199551330.003.0028

Cited by 223 publications

(346 citation statements)

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“…Deductive reasoning is hard for humans [1]. Even simple deductive tasks often yield low performances [2].…”

Section: Introductionmentioning

confidence: 99%

“…This would probably happen because the human mind does not seem to work according to the rules of logic [3]. The psychological processing of deduction, in contrast, would proceed by representing mental simulations inferred from given information [1]. An important collection of evidence suggests that humans construct mental models to achieve deductive conclusions [4].…”

Section: Introductionmentioning

confidence: 99%

“…A further comparison between such statements would yield the sought conclusion to a deductive problem or situation. This view is proposed by the Mental Models Theory (MMT) [1]. The MMT emphasizes the semantic and pragmatic variables of reasoning, whereas previous theories were focused on syntactic or formal components of human thought [4].…”

Section: Introductionmentioning

confidence: 99%

“…Syntactic components are those related to abstract structures and to their formal properties. The MMT defines working memory as the short-term memory system that regulates reasoning [1]. This system would be responsible for the representation and inference of deductive processes [4].…”

Section: Introductionmentioning

confidence: 99%

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The Shallow Processing of Logical Negation

Macbeth¹

2013

PBS

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Abstract:The aim of this study is to introduce a novel reasoning phenomenon concerned with the shallow processing of negation in the context of sentential reasoning. By analogy to other psychological explanations that account for superficial responses with conditionals, this study proposes an account for biconditionals derived from a recent theory of negation. This theory predicts that the psychological use of negation returns small scope products. This would happen because the human mind tends to avoid the working memory overload by simplifying its reasoning processes. A within-subjects experimental design was applied to test this conjecture. Results were consistent with such small scope negation prediction. The obtained evidence extends the observation of shallow reasoning processes to the negation of conjunctions and disjunctions that take the form of biconditionals. The results of this study support a mental models approach to account for the psychology of logical negation.

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“…Deductive reasoning is hard for humans [1]. Even simple deductive tasks often yield low performances [2].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Shallow Processing of Logical Negation

Macbeth¹

2013

PBS

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show abstract

“…System 1 executes routine tasks without much cognitive effort, but if a mismatch between expectation and reality is perceived, this may initiate slower, more effortful, conscious cognitive processes (system 2). De Boer [25] building on Schön [28] and Johnson-Laird [27] similarly suggests that a change in cognition is triggered by a surprise when expectation and reality do not match, leading to reflection on the current approach.…”

Section: Discussionmentioning

confidence: 99%

Models of Automation Surprise: Results of a Field Survey in Aviation

Boer¹,

Dekker²

2017

Preprint

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Automation surprises in aviation continue to be a significant safety concern and the community's search for effective strategies to mitigate them are ongoing. The literature has offered two fundamentally divergent directions, based on different ideas about the nature of cognition and collaboration with automation. In this paper, we report the results of a field study that empirically compared and contrasted two models of automation surprises: a normative individual-cognition model and a sense-making model based on distributed cognition. Our data prove a good fit for the sense-making model. This finding is relevant for aviation safety, since our understanding of the cognitive processes that govern the human interaction with automation drives what we need to do to reduce the frequency of automation-induced events.

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Reasons or rationalizations: The role of principles in the moral dumbfounding paradigm

McHugh

McGann

Igou

et al. 2020

Behavioral Decision Making

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Moral dumbfounding occurs when people maintain a moral judgment even though they cannot provide reasons for it. Recently, questions have been raised about whether dumbfounding is a real phenomenon. Two reasons have been proposed as guiding the judgments of dumbfounded participants: harm‐based reasons (believing an action may cause harm) or norm‐based reasons (breaking a moral norm is inherently wrong). Participants in that research (see Royzman, Kim, & Leeman, 2015), who endorsed either reason were excluded from analysis, and instances of moral dumbfounding seemingly reduced to non‐significance. We argue that endorsing a reason is not sufficient evidence that a judgment is grounded in that reason. Stronger evidence should additionally account for (a) articulating a given reason and (b) consistently applying the reason in different situations. Building on this, we develop revised exclusion criteria across three studies. Study 1 included an open‐ended response option immediately after the presentation of a moral scenario. Responses were coded for mention of harm‐based or norm‐based reasons. Participants were excluded from analysis if they both articulated and endorsed a given reason. Using these revised criteria for exclusion, we found evidence for dumbfounding, as measured by the selecting of an admission of not having reasons. Studies 2 and 3 included a further three questions relating to harm‐based reasons specifically, assessing the consistency with which people apply harm‐based reasons across differing contexts. As predicted, few participants consistently applied, articulated, and endorsed harm‐based reasons, and evidence for dumbfounding was found.

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How we Reason

Cited by 223 publications

References 0 publications

The Shallow Processing of Logical Negation

The Shallow Processing of Logical Negation

Models of Automation Surprise: Results of a Field Survey in Aviation

Reasons or rationalizations: The role of principles in the moral dumbfounding paradigm

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