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Journal articles on the topic 'Reasoning (Psychology) Logic'

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Published: 4 June 2021

Last updated: 1 February 2022

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1

Stenning, Keith, and Michiel van Lambalgen. "Reasoning, logic, and psychology." Wiley Interdisciplinary Reviews: Cognitive Science 2, no. 5 (2010): 555–67. http://dx.doi.org/10.1002/wcs.134.

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Oaksford, Mike, and Nick Chater. "New Paradigms in the Psychology of Reasoning." Annual Review of Psychology 71, no. 1 (2020): 305–30. http://dx.doi.org/10.1146/annurev-psych-010419-051132.

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The psychology of verbal reasoning initially compared performance with classical logic. In the last 25 years, a new paradigm has arisen, which focuses on knowledge-rich reasoning for communication and persuasion and is typically modeled using Bayesian probability theory rather than logic. This paradigm provides a new perspective on argumentation, explaining the rational persuasiveness of arguments that are logical fallacies. It also helps explain how and why people stray from logic when given deductive reasoning tasks. What appear to be erroneous responses, when compared against logic, often t

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3

Terrell, Dudley J., and J. M. Johnston. "Logic, Reasoning, and Verbal Behavior." Behavior Analyst 12, no. 1 (1989): 35–44. http://dx.doi.org/10.1007/bf03392475.

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4

Hobson, J. Allan, Suchada Sangsanguan, Henry Arantes, and David Kahn. "Dream logic—The inferential reasoning paradigm." Dreaming 21, no. 1 (2011): 1–15. http://dx.doi.org/10.1037/a0022860.

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5

Aune, Bruce. "Formal logic and practical reasoning." Theory and Decision 20, no. 3 (1986): 301–20. http://dx.doi.org/10.1007/bf00134043.

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6

Allott, Nicholas, and Hiroyuki Uchida. "Classical logic, conditionals and “nonmonotonic” reasoning." Behavioral and Brain Sciences 32, no. 1 (2009): 85. http://dx.doi.org/10.1017/s0140525x09000296.

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AbstractReasoning with conditionals is often thought to be non-monotonic, but there is no incompatibility with classical logic, and no need to formalise inference itself as probabilistic. When the addition of a new premise leads to abandonment of a previously compelling conclusion reached by modus ponens, for example, this is generally because it is hard to think of a model in which the conditional and the new premise are true.

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Widlok, Thomas, and Keith Stenning. "Seeking Common Cause between Cognitive Science and Ethnography: Alternative Logic in Cooperative Action." Journal of Cognition and Culture 18, no. 1-2 (2018): 1–30. http://dx.doi.org/10.1163/15685373-12340027.

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Abstract Alternative logics have been invoked periodically to explain the systematically diﬀerent modes of thought of the subjects of ethnography: one logic for ‘us’ and another for ‘them’. Recently anthropologists have cast doubt on the tenability of such an explanation of diﬀerence. In cognitive science, [Stenning and van Lambalgen, 2008] proposed that with the modern development of multiple logics, at least several logics are required for making sense of the cognitive processes of reasoning for diﬀerent purposes and in diﬀerent contexts. Alongside Classical logic (CL) — the logic of dispute

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8

Legrenzi, Paolo, and Maria Sonino Legrenzi. "Reasoning and Social Psychology : From Mental Logic To a Perspective Approach." Intellectica. Revue de l'Association pour la Recherche Cognitive 11, no. 1 (1991): 53–80. http://dx.doi.org/10.3406/intel.1991.1378.

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Klaczynski, Paul A., and Wejdan Felmban. "Effects of Thinking Dispositions, General Ability, Numeracy, and Instructional Set on Judgments and Decision-Making." Psychological Reports 123, no. 2 (2018): 341–70. http://dx.doi.org/10.1177/0033294118806473.

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To explore hypotheses based on Stanovich’s proposal that analytic processing comprises a reflective-level, an algorithmic level, and specific mindware, 342 participants completed measures of thinking dispositions, general ability (GA), numeracy, and probabilistic and nonprobabilistic reasoning. In a control condition, numeracy predicted probabilistic reasoning at high levels of both thinking dispositions and GA, and GA predicted nonprobabilistic reasoning at high levels of thinking dispositions. In a logic instruction condition, numeracy predicted probabilistic reasoning when GA was high, and

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10

Oaksford, Mike, and Nick Chater. "The uncertain reasoner: Bayes, logic, and rationality." Behavioral and Brain Sciences 32, no. 1 (2009): 105–20. http://dx.doi.org/10.1017/s0140525x0900051x.

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AbstractHuman cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. InBayesian Rationalitywe argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is a residual role for logic in understand

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De Neys, Wim, and Gordon Pennycook. "Logic, Fast and Slow: Advances in Dual-Process Theorizing." Current Directions in Psychological Science 28, no. 5 (2019): 503–9. http://dx.doi.org/10.1177/0963721419855658.

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Studies on human reasoning have long established that intuitions can bias inference and lead to violations of logical norms. Popular dual-process models, which characterize thinking as an interaction between intuitive (System 1) and deliberate (System 2) thought processes, have presented an appealing explanation for this observation. According to this account, logical reasoning is traditionally considered as a prototypical example of a task that requires effortful deliberate thinking. In recent years, however, a number of findings obtained with new experimental paradigms have brought into ques

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Pfeifer, Niki, and Gernot D. Kleiter. "Mental probability logic." Behavioral and Brain Sciences 32, no. 1 (2009): 98–99. http://dx.doi.org/10.1017/s0140525x09000442.

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AbstractWe discuss Oaksford & Chater's (O&C's) probabilistic approach from a probability logical point of view. Specifically, we comment on subjective probability, the indispensability of logic, the Ramsey test, the consequence relation, human nonmonotonic reasoning, intervals, generalized quantifiers, and rational analysis.

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13

Ball, Linden J., Peter Phillips, Caroline N. Wade, and Jeremy D. Quayle. "Effects of Belief and Logic on Syllogistic Reasoning." Experimental Psychology 53, no. 1 (2006): 77–86. http://dx.doi.org/10.1027/1618-3169.53.1.77.

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Studies of syllogistic reasoning have demonstrated a nonlogical tendency for people to endorse more believable conclusions than unbelievable ones. This belief bias effect is more dominant on invalid syllogisms than valid ones, giving rise to a logic by belief interaction. We report an experiment in which participants’ eye movements were recorded in order to provide insights into the nature and time course of the reasoning processes associated with manipulations of conclusion validity and believability. Our main dependent measure was people’s inspection times for syllogistic premises, and we te

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14

Johnson-Laird, P. N. "Peirce, logic diagrams, and the elementary operations of reasoning." Thinking & Reasoning 8, no. 1 (2002): 69–95. http://dx.doi.org/10.1080/13546780143000099.

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15

Neys, Wim De. "Dual Processing in Reasoning." Psychological Science 17, no. 5 (2006): 428–33. http://dx.doi.org/10.1111/j.1467-9280.2006.01723.x.

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Human reasoning has been characterized as an interplay between an automatic belief-based system and a demanding logic-based reasoning system. The present study tested a fundamental claim about the nature of individual differences in reasoning and the processing demands of both systems. Participants varying in working memory capacity performed a reasoning task while their executive resources were burdened with a secondary task. Results were consistent with the dual-process claim: The executive burden hampered correct reasoning when the believability of a conclusion conflicted with its logical v

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Urbański, Mariusz. "Formal modeling of human reasoning: errors, limitations and Baconian bees." Logical Investigations 26, no. 2 (2020): 106–15. http://dx.doi.org/10.21146/2074-1472-2020-26-2-106-115.

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Since the end of the XX century we are witnessing a practical, or cognitive, turn in logic. Drawing on enormous achievements brought about by the mathematical turn that started more than a hundred years ago, logic now has came back to its Artistotelian roots as an instrument by which we come to know anything. The re-forged alliance between logic – now well equipped with sophisticated formal tools – and psychology results in more and more substantial developments in studies on human reasoning and problem solving. To reap the fruits of this alliance we need to be aware that it leads to a shift i

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17

Stryker, Robin, Danielle Docka-Filipek, and Pamela Wald. "Employment Discrimination Law and Industrial Psychology: Social Science as Social Authority and the Co-Production of Law and Science." Law & Social Inquiry 37, no. 04 (2012): 777–814. http://dx.doi.org/10.1111/j.1747-4469.2011.01277.x.

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This article combines Monahan and Walker's classification of social facts, social authority, and social frameworks with political-institutionalism's view of law and science as competing institutional logics to explain how, and with what consequences, employment discrimination law and industrial-organizational (I-O) psychology became co-produced. When social science is incorporated into enforcement of legislative law as social authority—rationale for judicial rule making—law's institutional logic of relying on precedent and reasoning by analogy ensures that social science will have ongoing infl

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18

Collins, Allan, and Ryszard Michalski. "The Logic of Plausible Reasoning: A Core Theory." Cognitive Science 13, no. 1 (1989): 1–49. http://dx.doi.org/10.1207/s15516709cog1301_1.

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19

Stalder, Daniel R. "Does Logic Moderate the Fundamental Attribution Error?" Psychological Reports 86, no. 3 (2000): 879–82. http://dx.doi.org/10.2466/pr0.2000.86.3.879.

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The fundamental attribution error was investigated from an individual difference perspective. Mathematicians were compared with nonmathematicians (Exp. 1; n: 84), and undergraduates who scored high on a test of logical reasoning ability were compared with those who scored low (Exp. 2; n: 62). The mathematicians and those participants scoring higher on logic appeared less prone to the fundamental attribution error, primarily using a measure of confidence in attributions.

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20

Beller, Sieghard, and Hans Spada. "The logic of content effects in propositional reasoning: The case ofconditional reasoning with a point of view." Thinking & Reasoning 9, no. 4 (2003): 335–78. http://dx.doi.org/10.1080/13546780342000007.

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21

Blanchette, I., and A. Richards. "Reasoning About Emotional and Neutral Materials: Is Logic Affected by Emotion?" Psychological Science 15, no. 11 (2004): 745–52. http://dx.doi.org/10.1111/j.0956-7976.2004.00751.x.

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22

Bennett, Bruce M., Donald D. Hoffman, and Paresh Murthy. "Lebesgue Logic for Probabilistic Reasoning and Some Applications to Perception." Journal of Mathematical Psychology 37, no. 1 (1993): 63–103. http://dx.doi.org/10.1006/jmps.1993.1004.

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23

Oaksford, Mike, and Nick Chater. "Précis ofBayesian Rationality: The Probabilistic Approach to Human Reasoning." Behavioral and Brain Sciences 32, no. 1 (2009): 69–84. http://dx.doi.org/10.1017/s0140525x09000284.

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AbstractAccording to Aristotle, humans are the rational animal. The borderline between rationality and irrationality is fundamental to many aspects of human life including the law, mental health, and language interpretation. But what is it to be rational? One answer, deeply embedded in the Western intellectual tradition since ancient Greece, is that rationality concerns reasoning according to the rules of logic – the formal theory that specifies the inferential connections that hold with certainty between propositions. Piaget viewed logical reasoning as defining the end-point of cognitive deve

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24

Ferrigno, Stephen, Yiyun Huang, and Jessica F. Cantlon. "Reasoning Through the Disjunctive Syllogism in Monkeys." Psychological Science 32, no. 2 (2021): 292–300. http://dx.doi.org/10.1177/0956797620971653.

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The capacity for logical inference is a critical aspect of human learning, reasoning, and decision-making. One important logical inference is the disjunctive syllogism: given A or B, if not A, then B. Although the explicit formation of this logic requires symbolic thought, previous work has shown that nonhuman animals are capable of reasoning by exclusion, one aspect of the disjunctive syllogism (e.g., not A = avoid empty). However, it is unknown whether nonhuman animals are capable of the deductive aspects of a disjunctive syllogism (the dependent relation between A and B and the inference th

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25

Evans, Jonathan St B. T. "Logic and human reasoning: An assessment of the deduction paradigm." Psychological Bulletin 128, no. 6 (2002): 978–96. http://dx.doi.org/10.1037/0033-2909.128.6.978.

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26

Girotto, Vittorio, Paul Light, and Christopher Colbourn. "Pragmatic Schemas and Conditional Reasoning in Children." Quarterly Journal of Experimental Psychology Section A 40, no. 3 (1988): 469–82. http://dx.doi.org/10.1080/02724988843000023.

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Solving problems involving conditional relationships has been postulated to play a central role in the development of deductive reasoning, which itself underpins much cognitive developmental theory. The traditional Piagetian and “natural logic” approaches to this topic have more recently been challenged by findings that are more readily explained in terms of the concept of pragmatic schemas. On this basis it was predicted that even young “pre-formal” children would be able to succeed in a Reduced Array Selection Task if the test statement (referring to a previously told story about bees living

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27

Markovits, Henry, and Fabien Savary. "Pragmatic Schemas and the Selection Task: To Reason or Not to Reason." Quarterly Journal of Experimental Psychology Section A 45, no. 1 (1992): 133–48. http://dx.doi.org/10.1080/14640749208401319.

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Cheng and Holyoak (1985) have proposed that people possess classes of linguistically based schemas that have an internal structure that is determined by pragmatic considerations. They found that when permission schemas (“If you want to do P, then you must do Q”) are used in the selection task, the success rate is much superior to what is usually observed. According to Cheng and Holyoak, this is due to the fact that the permission schema is defined by a set of production rules that give the same answers to problems of conditional inference as those of formal logic. In order to test this hypothe

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28

Forcada, Miquel. "IBN BĀJJA ONTAṢAWWURANDTAṢDĪQ: SCIENCE AND PSYCHOLOGY". Arabic Sciences and Philosophy 24, № 1 (2014): 103–26. http://dx.doi.org/10.1017/s0957423913000106.

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AbstractAs is well known,taṣawwurandtaṣdīq,conceptualization and assent, are essential notions in the epistemology of Arabo-Islamic philosophy. Conceptualization amounts to the definition of an object of knowledge, and assent to the recognition,viasome kind of reasoning, that this definition is true. One of the authors who dealt with both topics in greatest depth was al-Fārābī, whoseoeuvreexerted a profound influence on Ibn Bājja. This article analyzes the materials ontaṣawwurandtaṣdīqfound in Ibn Bājja's notes regarding al-Fārābī's writings on logic and scientific method, namely the glosses t

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29

Denison, Stephanie, and Fei Xu. "Infant Statisticians: The Origins of Reasoning Under Uncertainty." Perspectives on Psychological Science 14, no. 4 (2019): 499–509. http://dx.doi.org/10.1177/1745691619847201.

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Humans frequently make inferences about uncertain future events with limited data. A growing body of work suggests that infants and other primates make surprisingly sophisticated inferences under uncertainty. First, we ask what underlying cognitive mechanisms allow young learners to make such sophisticated inferences under uncertainty. We outline three possibilities, the logic, probabilistic, and heuristics views, and assess the empirical evidence for each. We argue that the weight of the empirical work favors the probabilistic view, in which early reasoning under uncertainty is grounded in in

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Stenning, Keith, and Jon Oberlander. "A Cognitive Theory of Graphical and Linguistic Reasoning: Logic and Implementation." Cognitive Science 19, no. 1 (1995): 97–140. http://dx.doi.org/10.1207/s15516709cog1901_3.

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31

Sokolov, I. A. "Theory and practice in artificial intelligence." Вестник Российской академии наук 89, no. 4 (2019): 365–70. http://dx.doi.org/10.31857/s0869-5873894365-370.

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Artificial Intelligence is an interdisciplinary field, and formed about 60 years ago as an interaction between mathematical methods, computer science, psychology, and linguistics. Artificial Intelligence is an experimental science and today features a number of internally designed theoretical methods: knowledge representation, modeling of reasoning and behavior, textual analysis, and data mining. Within the framework of Artificial Intelligence, novel scientific domains have arisen: non-monotonic logic, description logic, heuristic programming, expert systems, and knowledge-based software engin

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32

van den Daele, Leland. "Cognitive Development of the Binary Operations for Standard and Nonstandard Logic." Perceptual and Motor Skills 83, no. 3_suppl (1996): 1271–88. http://dx.doi.org/10.2466/pms.1996.83.3f.1271.

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The binary operations of standard logic, conjunction, implication, equality, not/both, exclusive/or, and inclusive/or disjunction are usually employed as a basis for the construction and evaluation of psychological theories of logical behavior. An additional 10 binary nonstandard operations are proposed. Together the standard and nonstandard operations comprise the operations of the extended logic. An axiom of developmental order proposes that extended operations with fewer valid cases are mastered before operations with more valid cases. The operations are discussed from the perspectives of d

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33

Khalil, Elias L. "Are stomachs rational?" Behavioral and Brain Sciences 32, no. 1 (2009): 91–92. http://dx.doi.org/10.1017/s0140525x09000375.

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AbstractOaksford & Chater (O&C) would need to define rationality if they want to argue that stomachs are not rational. The question of rationality, anyhow, is orthogonal to the debate concerning whether humans use classical deductive logic or probabilistic reasoning.

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Blanchette, Isabelle. "The effect of emotion on interpretation and logic in a conditional reasoning task." Memory & Cognition 34, no. 5 (2006): 1112–25. http://dx.doi.org/10.3758/bf03193257.

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Barrouillet, Pierre, and Henry Markovits. "Is the self-organizing consciousness framework compatible with human deductive reasoning?" Behavioral and Brain Sciences 25, no. 3 (2002): 330–31. http://dx.doi.org/10.1017/s0140525x02220063.

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As stressed by Perruchet & Vinter, the SOC model echoes Johnson-Laird's mental model theory. Indeed, the latter rejects rule-based processing and assumes that reasoning is achieved through the manipulation of conscious representations. However, the mental model theory as well as its modified versions resorts to the abstraction of complex schemas and some form of implicit logic that seems incompatible with the SOC approach.

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Stupple, Edward J. N., and Linden J. Ball. "Belief–logic conflict resolution in syllogistic reasoning: Inspection-time evidence for a parallel-process model." Thinking & Reasoning 14, no. 2 (2008): 168–81. http://dx.doi.org/10.1080/13546780701739782.

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37

Oaksford, Mike, and Nick Chater. "Probabilities, causation, and logic programming in conditional reasoning: reply to Stenning and Van Lambalgen (2016)." Thinking & Reasoning 22, no. 3 (2016): 336–54. http://dx.doi.org/10.1080/13546783.2016.1139505.

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Buchtel, Emma E., and Ara Norenzayan. "Which should you use, intuition or logic? Cultural differences in injunctive norms about reasoning." Asian Journal of Social Psychology 11, no. 4 (2008): 264–73. http://dx.doi.org/10.1111/j.1467-839x.2008.00266.x.

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39

COLBERG, MAGDA. "LOGIC-BASED MEASUREMENT OF VERBAL REASONING: A KEY TO INCREASED VALIDITY AND ECONOMY." Personnel Psychology 38, no. 2 (1985): 347–59. http://dx.doi.org/10.1111/j.1744-6570.1985.tb00552.x.

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40

Stenning, Keith, and Michiel van Lambalgen. "Logic programming, probability, and two-system accounts of reasoning: a rejoinder to Oaksford and Chater (2014)." Thinking & Reasoning 22, no. 3 (2016): 355–68. http://dx.doi.org/10.1080/13546783.2016.1139504.

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Evans, Jonathan St B. T. "Does rational analysis stand up to rational analysis?" Behavioral and Brain Sciences 32, no. 1 (2009): 88–89. http://dx.doi.org/10.1017/s0140525x09000338.

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AbstractI agree with Oaksford & Chater (O&C) that human beings resemble Bayesian reasoners much more closely than ones engaging standard logic. However, I have many problems with their “rational analysis” framework, which appears to be rooted in normative rather than ecological rationality. The authors also overstate everyday rationality and neglect to account for much relevant psychological work on reasoning.

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42

Weinstein, Mark Leonard, and Dan Fisherman. "on the relevance of cognitive neuroscience for community of inquiry." childhood & philosophy 15 (January 30, 2019): 01–19. http://dx.doi.org/10.12957/childphilo.2019.37513.

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Community of inquiry is most often seen as a dialogical procedure for the cooperative development of reasonable approaches to knowledge and meaning. This reflects a deep commitment to normatively based reasoning that is pervasive in a wide range of approaches to critical thinking and argument, where the underlying theory of reasoning is logic driven, whether formal or informal. The commitment to normative reasoning is deeply historical reflecting the fundamental distinction between reason and emotion. Despite the deep roots of the distinction and its canonization in current educational thought

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Braunstein, Myron L. "A better understanding of inference can reconcile constructivist and direct theories." Behavioral and Brain Sciences 25, no. 1 (2002): 99. http://dx.doi.org/10.1017/s0140525x02240029.

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The attempt to relate distinctions in perceptual theory to different physiological systems leads to numerous exceptions and inconsistencies. A more promising approach to the reconciliation of constructivist theory and direct perception is to recognize that perception does involve inference, as the constructivists insist, but that inference is a process in logic that does not require unconscious reasoning and need be no more thought-like than resonance.

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Daniel, David B., and Paul A. Klaczynski. "Developmental and Individual Differences in Conditional Reasoning: Effects of Logic Instructions and Alternative Antecedents." Child Development 77, no. 2 (2006): 339–54. http://dx.doi.org/10.1111/j.1467-8624.2006.00874.x.

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Schroyens, Walter. "On is an ought: Levels of analysis and the descriptive versus normative analysis of human reasoning." Behavioral and Brain Sciences 32, no. 1 (2009): 101–2. http://dx.doi.org/10.1017/s0140525x09000478.

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AbstractAlgorithmic-level specifications carry part of the explanatory burden in most psychological theories. It is, thus, inappropriate to limit a comparison and evaluation of theories to the computational level. A rational analysis considers people's goal-directed and environmentally adaptive rationality; it is not normative. Adaptive rationality is by definition non-absolute; hence, neither deductive logic nor Bayesian probability theory has absolute normative status.

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De Neys, Wim. "Beyond response output: More logical than we think." Behavioral and Brain Sciences 32, no. 1 (2009): 87–88. http://dx.doi.org/10.1017/s0140525x09000326.

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AbstractOaksford & Chater (O&C) rely on a data fitting approach to show that a Bayesian model captures the core reasoning data better than its logicist rivals. The problem is that O&C's modeling has focused exclusively on response output data. I argue that this exclusive focus is biasing their conclusions. Recent studies that focused on the processes that resulted in the response selection are more positive for the role of logic.

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Stupple, Edward J. N., Linden J. Ball, Jonathan St B. T. Evans, and Emily Kamal-Smith. "When logic and belief collide: Individual differences in reasoning times support a selective processing model." Journal of Cognitive Psychology 23, no. 8 (2011): 931–41. http://dx.doi.org/10.1080/20445911.2011.589381.

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48

Stupple, Edward J. N., and Eleanor F. Waterhouse. "Short article: Negations in syllogistic reasoning: Evidence for a heuristic–analytic conflict." Quarterly Journal of Experimental Psychology 62, no. 8 (2009): 1533–41. http://dx.doi.org/10.1080/17470210902785674.

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An experiment utilizing response time measures was conducted to test dominant processing strategies in syllogistic reasoning with the expanded quantifier set proposed by Roberts (2005). Through adding negations to existing quantifiers it is possible to change problem surface features without altering logical validity. Biases based on surface features such as atmosphere, matching, and the probability heuristics model (PHM; Chater & Oaksford, 1999; Wetherick & Gilhooly, 1995) would not be expected to show variance in response latencies, but participant responses should be highly sensitiv

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De Neys, Wim, and Elke Van Gelder. "Logic and belief across the lifespan: the rise and fall of belief inhibition during syllogistic reasoning." Developmental Science 12, no. 1 (2009): 123–30. http://dx.doi.org/10.1111/j.1467-7687.2008.00746.x.

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50

St.B.T. Evans, Jonathan, John Clibbens, and Benjamin Rood. "Bias in Conditional Inference: Implications for Mental Models and Mental Logic." Quarterly Journal of Experimental Psychology Section A 48, no. 3 (1995): 644–70. http://dx.doi.org/10.1080/14640749508401409.

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Three experiments are reported in which subjects are given the opportunity to make any of the four inferences associated with conditional statements: modus ponens (MP), denial of the antecedent (DA), affirmation of the consequent (AC), and modus tollens (MT). The primary purpose of the research was to establish the generality and robustness of polarity biases that may be occasioned by systematic rotation of negative components in the conditional rules. In Experiments 1 & 2, three forms of conditionals were used: “if (not) p then (not) q”, “(not) p only if (not) q” and “(not) q if (not) p”.

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