Sage Journals: Discover world-class research

Abstract

Classic dual process theories of human reasoning attribute explicit reasoning to effortful, deliberative thinking. According to these models, intuitive processes lack any access to the formal rules of logic and probability and hence rely exclusively on superficial problem features to determine a response. However, in recent years, researchers have demonstrated that reasoners are able to solve simple logical or probabilistic problems relatively automatically, a capability which has been called “logical intuition.” In four experiments, we instructed participants to judge the validity (Experiments 1 and 4), likeability (Experiments 1, 2, and 3), and physical brightness (Experiments 2, 3, and 4) of the conclusion to several reasoning problems. Brightness judgements were made by evaluating the font shade brightness of the argument’s conclusion. Participants were also asked to complete a range of individual differences measures, drawing on cognitive ability and cognitive style, to evaluate the extent to which “logical intuitions” were linked to measures of deliberative reasoning. The results showed that participants judged the conclusion of logically valid statements to be more valid, more likable, and more physically bright than invalid statements. Participants with higher cognitive ability and unlimited processing time showed greater effects of logical validity in their liking judgements (varied across experiments). However, these effects were absent in the brightness tasks, suggesting that logic effects observed under instructions to judge conclusion brightness are a purer measure of “logical intuition.” We discuss the implications of our findings for recent dual process theories of human reasoning.

Keywords

Reasoning dual process theory logical intuition cognitive ability individual differences

Get full access to this article

View all access options for this article.

References

Baayen

R. H.

Davidson

D. J.

Bates

D. M.

(2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412. https://doi.org/10.1016/j.jml.2007.12.005

Bago

De Neys

(2017a). Fast logic?: Examining the time course assumption of dual process theory. Cognition, 158, 90–109. https://doi.org/10.1016/j.cognition.2016.10.014

Bago

De Neys

(2017b). Rise and fall of conflicting intuitions during reasoning. In Proceedings of the Annual Meeting of the Cognitive Science Society. https://cogsci.mindmodeling.org/2017/papers/0028/paper0028.pdf

Bago

De Neys

(2019a). Advancing the specification of dual process models of higher cognition: A critical test of the hybrid model view. Thinking and Reasoning, 26, 1–30. https://doi.org/10.1080/13546783.2018.1552194

Bago

De Neys

(2019b). The Smart System 1: Evidence for the intuitive nature of correct responding on the bat-and-ball problem. Thinking and Reasoning, 25, 257–299. https://doi.org/10.1080/13546783.2018.1507949

Bago

Frey

Vidal

Houdé

Borst

De Neys

(2018). Fast and slow thinking: Electrophysiological evidence for early conflict sensitivity. Neuropsychologia, 117, 483–490. https://doi.org/10.1016/j.neuropsychologia.2018.07.017

Bago

Raoelison

De Neys

(2019). Second-guess: Testing the specificity of error detection in the bat-and-ball problem. Acta Psychologica, 193, 214–228. https://doi.org/10.1016/j.actpsy.2019.01.008

Banks

A. P.

Hope

(2014). Heuristic and analytic processes in reasoning: An event-related potential study of belief bias. Psychophysiology, 51, 290–297. https://doi.org/10.1111/psyp.12169

Barr

D. J.

Levy

Scheepers

Tily

H. J.

(2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 68, 255–278. https://doi.org/10.1016/j.jml.2012.11.001

10.

Betsch

Glöckner

(2010). Intuition in judgment and decision making: Extensive thinking without effort. Psychological Inquiry, 21, 279–294. https://doi.org/10.1080/1047840X.2010.517737

11.

Bonner

Newell

B. R.

(2010). In conflict with ourselves? An investigation of heuristic and analytic processes in decision making. Memory and Cognition, 38, 186–196. https://doi.org/10.3758/MC.38.2.186

12.

Bridges

Pitiot

MacAskill

Peirce

(2020). The timing mega-study: Comparing a range of experiment generators, both lab-based and online. https://psyarxiv.com/d6nu5/download?format=pdf

13.

Brisson

Schaeken

Markovits

De Neys

(2018). Conflict detection and logical complexity. Psychologica Belgica, 58, 318–332. https://doi.org/10.5334/pb.448

14.

Darlow

A. L.

Sloman

S. A.

(2010). Two systems of reasoning: Architecture and relation to emotion. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 382–392. https://doi.org/10.1002/wcs.34

15.

de Chantal

P. L.

Newman

I. R.

Thompson

Markovits

(2019). Who resists belief-biased inferences? The role of individual differences in reasoning strategies, working memory, and attentional focus. Memory and Cognition, 48, 655–671. https://doi.org/10.3758/s13421-019-00998-2

16.

De Neys

(2012). Bias and conflict: A case for logical intuitions. Perspectives on Psychological Science, 7(1), 28–38. https://doi.org/10.1177/1745691611429354

17.

De Neys

(2014). Conflict detection, dual processes, and logical intuitions: Some clarifications. Thinking and Reasoning, 20(2), 169–187. https://doi.org/10.1080/13546783.2013.854725

18.

De Neys

(2015). Heuristic bias and conflict detection during thinking. Psychology of Learning and Motivation—Advances in Research and Theory, 62, 1–32. https://doi.org/10.1016/bs.plm.2014.09.001

19.

De Neys

(2017a). Bias, conflict, and fast logic: Towards a hybrid dual process future? In De Neys

(Ed.), Dual process theory 2.0 (pp. 47–65). Routledge. https://doi.org/10.4324/9781315204550

20.

De Neys

(2017b). Dual process theory 2.0. Routledge. https://doi.org/10.4324/9781315204550

21.

De Neys

Bonnefon

J.-F.

(2013). The whens and whys of individual differences in individual thinking biases. Trends in Cognitive Sciences, 17(4), 172–178. https://doi.org/10.1016/j.tics.2013.02.001

22.

De Neys

Cromheeke

Osman

(2011). Biased but in doubt: Conflict and decision confidence. PLOS ONE, 6(1), Article e15954. https://doi.org/10.1371/journal.pone.0015954

23.

De Neys

Glumicic

(2008). Conflict monitoring in dual process theories of thinking. Cognition, 106, 1248–1299. https://doi.org/10.1016/j.cognition.2007.06.002

24.

De Neys

Moyens

Ansteenwegen

D. V.

(2010). Feeling we’re biased: Autonomic arousal and reasoning conflict. Cognitive, Affective and Behavioral Neuroscience, 10(2), 208–216. https://doi.org/10.3758/CABN.10.2.208

25.

De Neys

Pennycook

(2019). Logic, fast and slow: Advances in dual-process theorizing. Current Directions in Psychological Science, 28, 503–509.

26.

De Neys

Vartanian

Goel

(2008). Smarter than we think: When our brains detect that we are biased. Psychological Science, 19, 483–489. https://doi.org/10.1111/j.1467-9280.2008.02113.x

27.

Dube

Rotello

C. M.

Heit

(2010). Assessing the belief bias effect with ROCs: It’s a response bias effect. Psychological Review, 117, 831–863. https://doi.org/10.1037/a0019634

28.

Epstein

(1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49, 709–724. https://doi.org/10.1037/0003-066x.49.8.709

29.

Erceg

Galic

Bubić

(2019). Individual differences in abilities, knowledge and thinking dispositions among different types of problem solvers and their implications for the validity of reasoning tasks. https://psyarxiv.com/w5zau/

30.

Evans

J. S. B. T.

(2008). Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59, 255–278. https://doi.org/10.1146/annurev.psych.59.103006.093629

31.

Evans

J. S. B. T.

(2017). Dual process theory: Perspectives and problems. In De Neys

(Ed.), Dual process theory 2.0 (pp. 137–155). Routledge. https://doi.org/10.4324/9781315204550

32.

Evans

J. S. B. T.

(2018). Dual-process theories. In Ball

L. J.

Thompson

V. A.

(Eds.), The Routledge International Handbook of Thinking and Reasoning (pp. 151–165). Routledge.

33.

Evans

J. S. B. T.

Handley

S. J.

Bacon

A. M.

(2009). Reasoning under time pressure: A study of causal conditional inference. Experimental Psychology, 56(2), 77–83. https://doi.org/10.1027/1618-3169.56.2.77

34.

Evans

J. S. B. T.

Handley

S. J.

Harper

C. N. J.

Johnson-Laird

P. N.

(1999). Reasoning about necessity and possibility: A test of the mental model theory of deduction. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 1495–1513. https://doi.org/10.1037/0278-7393.25.6.1495

35.

Evans

J. S. B. T.

Stanovich

K. E.

(2013). Dual-process theories of higher cognition: Advancing the debate. Perspectives on Psychological Science, 8, 223–241. https://doi.org/10.1177/1745691612460685

36.

Frederick

(2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19, 25–42. https://doi.org/10.1257/089533005775196732

37.

Frey

Johnson

E. D.

De Neys

(2018). Individual differences in conflict detection during reasoning. Quarterly Journal of Experimental Psychology, 71, 1188–1208. https://doi.org/10.1080/17470218.2017.1313283

38.

Gigerenzer

(2011). Adaptive thinking: Rationality in the real world. https://doi.org/10.1093/acprof:oso/9780195153729.001.0001

39.

Gigerenzer

Gaissmaier

(2010). Heuristic decision making. https://doi.org/10.1146/annurev-psych-120709-145346

40.

Glöckner

Betsch

(2012). Decisions beyond boundaries: When more information is processed faster than less. Acta Psychologica, 139, 532–542. https://doi.org/10.1016/j.actpsy.2012.01.009

41.

Gould

S. J.

(1989). The streak of streaks. CHANCE, 2, 10–16. https://doi.org/10.1080/09332480.1989.10554932

42.

Hagmayer

Sloman

S. A.

(2009). Decision makers conceive of their choices as interventions. Journal of Experimental Psychology: General, 138, 22–38. https://doi.org/10.1037/a0014585

43.

Hammond

(1996). Human judgment and social policy: Irreducible uncertainty, inevitable error, unavoidable injustice. https://books.google.com/books?hl=en&lr=&id=VxRnDAAAQBAJ&oi=fnd&pg=PR9&dq=Hammond+1996+Human+judgment+and+social+policy&ots=xvQrKJKm7E&sig=f4cEf4_FBRC3OJMiuJ3IscPHK4k

44.

Handley

S. J.

Newstead

S. E.

Trippas

(2011). Logic, Beliefs, and Instruction: A Test of the Default Interventionist Account of Belief Bias. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37(1), 28–43. https://doi.org/10.1037/a0021098

45.

Handley

S. J.

Trippas

(2015). Dual processes and the interplay between knowledge and structure: A new parallel processing model. Psychology of Learning and Motivation—Advances in Research and Theory, 62, 33–58. https://doi.org/10.1016/bs.plm.2014.09.002

46.

Hayes

B. K.

Wei

Dunn

J. C.

Stephens

R. G.

(2020). Why is logic so likeable? A single-process account of argument evaluation with logic and liking judgments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 46, 699–719. https://doi.org/10.1037/xlm0000753

47.

Hedge

Powell

Sumner

(2018). The reliability paradox: Why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods, 50, 1166–1186. https://doi.org/10.3758/s13428-017-0935-1

48.

Heim

(1970). AH 4 Group Test of General Intelligence. Manual (Rev. ed.). N.F.E.R. Pub. Co.

49.

Heit

Rotello

C. M.

(2014). Traditional difference-score analyses of reasoning are flawed. Cognition, 131, 75–91. https://doi.org/10.1016/j.cognition.2013.12.003

50.

Howarth

Handley

(2016). Belief bias, base rates and moral judgment: Re-evaluating the default interventionist dual process account. In Galbraith

Lucas

Over

(Eds.), The thinking mind: A Festschrift for Ken Manktelow (pp. 83–97). Psychology Press. https://doi.org/10.4324/9781315676074

51.

Howarth

Handley

Walsh

(2019). The logic sense: Exploring the role of executive functioning in belief and logic-based judgments. Thinking & Reasoning, 25, 416–448. https://doi.org/10.1080/13546783.2018.1523808

52.

Howarth

Handley

S. J.

Walsh

(2016). The logic-bias effect: The role of effortful processing in the resolution of belief–logic conflict. Memory and Cognition, 44, 330–349. https://doi.org/10.3758/s13421-015-0555-x

53.

Iacobucci

Posavac

S. S.

Kardes

F. R.

Schneider

M. J.

Popovich

D. L.

(2015). Toward a more nuanced understanding of the statistical properties of a median split. Journal of Consumer Psychology, 25, 652–665. https://doi.org/10.1016/j.jcps.2014.12.002

54.

Kahneman

Frederick

(2002). Representativeness revisited. Heuristics of Intuitive Judgment: Extensions and Applications, 225, 1090–1091. https://doi.org/10.1038/2251090a0

55.

Kahneman

Frederick

(2005). A model of heuristic judgement. In Holyoak

K. J.

Morrison

R. G.

(Eds.), The Cambridge handbook of thinking and reasoning (pp. 267–293). Cambridge University Press. https://doi.org/10.1111/cogs.12119

56.

Klauer

K. C.

Musch

Naumer

(2000). On belief bias in syllogistic reasoning. Psychological Review, 107, 852–884. https://doi.org/10.1037/0033-295X.107.4.852

57.

Klauer

K. C.

Singmann

(2013). Does logic feel good? Testing for intuitive detection of logicality in syllogistic reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(4), 1265–1273. https://doi.org/10.1037/a0030530

58.

Lakens

Scheel

A. M.

Isager

P. M.

(2018). Equivalence testing for psychological research: A tutorial. Advances in Methods and Practices in Psychological Science, 1, 259–269. https://doi.org/10.1177/2515245918770963

59.

Lenth

Singmann

Love

Buerkner

Herve

(2018). Package “emmeans” (R Package Version 1.15-15). https://doi.org/10.1080/00031305.1980.10483031>.License

60.

Macmillan

N. A.

Creelman

C. D.

(2004). Detection theory: A user’s guide (2nd ed.). https://doi.org/10.4324/9781410611147

61.

Markovits

Brisson

de Chantal

P. L.

Thompson

V. A.

(2017). Interactions between inferential strategies and belief bias. Memory and Cognition, 45, 1182–1192. https://doi.org/10.3758/s13421-017-0723-2

62.

Mata

Ferreira

M. B.

Voss

Kollei

(2017). Seeing the conflict: An attentional account of reasoning errors. Psychonomic Bulletin and Review, 24(6), 1980–1986. https://doi.org/10.3758/s13423-017-1234-7

63.

Matuschek

Kliegl

Vasishth

Baayen

Bates

(2017). Balancing Type I error and power in linear mixed models. Journal of Memory and Language, 94, 305–315. https://doi.org/10.1016/j.jml.2017.01.001

64.

McClelland

G. H.

Lynch

J. G.

Irwin

J. R.

Spiller

S. A.

Fitzsimons

G. J.

(2015). Median splits, Type II errors, and false-positive consumer psychology: Don’t fight the power. Journal of Consumer Psychology, 25, 679–689. https://doi.org/10.1016/j.jcps.2015.05.006

65.

Meier

B. P.

Robinson

M. D.

Crawford

L. E.

Ahlvers

W. J.

(2007). When “light” and “dark” thoughts become light and dark responses: Affect biases brightness judgments. Emotion, 7, 366–376. https://doi.org/10.1037/1528-3542.7.2.366

66.

Melnikoff

D. E.

Bargh

J. A.

(2018). The mythical number two. Trends in Cognitive Sciences, 22, 280–293. https://doi.org/10.1016/j.tics.2018.02.001

67.

Mevel

Poirel

Rossi

Cassotti

Simon

Houdé

De Neys

(2015). Bias detection: Response confidence evidence for conflict sensitivity in the ratio bias task. Journal of Cognitive Psychology, 27, 227–237. https://doi.org/10.1080/20445911.2014.986487

68.

Morewedge

C. K.

Kahneman

(2010). Associative processes in intuitive judgment. Trends in Cognitive Sciences, 14, 435–440. https://doi.org/10.1016/j.tics.2010.07.004

69.

Morsanyi

Handley

S. J.

(2012). Logic feels so good-I like it! evidence for intuitive detection of logicality in syllogistic reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 596–616. https://doi.org/10.1037/a0026099

70.

Nakamura

Kawaguchi

(2016). People like logical truth: Testing the intuitive detection of logical value in basic propositions. PLOS ONE, 11, Article e0169166. https://doi.org/10.1371/journal.pone.0169166

71.

Newman

I. R.

Gibb

Thompson

V. A.

(2017). Rule-based reasoning is fast and belief-based reasoning can be slow: Challenging current explanations of belief-bias and base-rate neglect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(7), 1154–1170. https://doi.org/10.1037/xlm0000372

72.

Newstead

S. E.

Handley

S. J.

Harley

Wright

Farrelly

(2004). Individual differences in deductive reasoning. The Quarterly Journal of Experimental Psychology, Section A: Human Experimental Psychology, 57, 33–60. https://doi.org/10.1080/02724980343000116

73.

Newstead

S. E.

Pollard

Evans

J. S. B. T.

Allen

J. L.

(1992). The source of belief bias effects in syllogistic reasoning. Cognition, 45, 257–284. https://doi.org/10.1016/0010-0277(92)90019-E

74.

Padilla

M. A.

Veprinsky

(2012). Correlation attenuation due to measurement error: A new approach using the bootstrap procedure. Educational and Psychological Measurement, 72, 827–846. https://doi.org/10.1177/0013164412443963

75.

Parsons

Kruijt

A.-W.

Fox

(2019). Psychological science needs a standard practice of reporting the reliability of cognitive-behavioral measurements. Advances in Methods and Practices in Psychological Science, 2, 378–395. https://doi.org/10.1177/2515245919879695

76.

Peirce

Gray

J. R.

Simpson

MacAskill

Höchenberger

Sogo

. . . Lindeløv

J. K.

(2019). PsychoPy2: Experiments in behavior made easy. Behavior Research Methods, 51, 195–203. https://doi.org/10.3758/s13428-018-01193-y

77.

Pennycook

Cheyne

J. A.

Barr

Koehler

D. J.

Fugelsang

J. A.

(2014). Cognitive style and religiosity: The role of conflict detection. Memory and Cognition, 39, 1275–1289. https://doi.org/10.3758/s13421-013-0340-7

78.

Pennycook

De Neys

Evans

J. S. B. T.

Stanovich

K. E.

Thompson

V. A.

(2018). The mythical dual-process typology. Trends in Cognitive Sciences, 22, 667–668. https://doi.org/10.1016/j.tics.2018.04.008

79.

Pennycook

Fugelsang

J. A.

Koehler

D. J.

(2012). Are we good at detecting conflict during reasoning? Cognition, 124, 101–106. https://doi.org/10.1016/j.cognition.2012.04.004

80.

Pennycook

Fugelsang

J. A.

Koehler

D. J.

(2015). What makes us think? A three-stage dual-process model of analytic engagement. Cognitive Psychology, 80, 34–72. https://doi.org/10.1016/j.cogpsych.2015.05.001

81.

Pennycook

Trippas

Handley

S. J.

Thompson

V. A.

(2014). Base rates: Both neglected and intuitive. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(2), 544–554. https://doi.org/10.1037/a0034887

82.

Raoelison

M. T. S.

Thompson

V. A.

De Neys

(2020). The smart intuitor: Cognitive capacity predicts intuitive rather than deliberate thinking. Cognition, 204, Article 104381. https://doi.org/10.1016/j.cognition.2020.104381

83.

R Core Team. (2014). R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.r-project.org/

84.

Reber

Schwarz

(1999). Effects of perceptual fluency on judgements of truth. Consciousness and Cognition, 8(1), 338–342.

85.

Rotello

C. M.

Heit

Dubé

(2015). When more data steer us wrong: Replications with the wrong dependent measure perpetuate erroneous conclusions. Psychonomic Bulletin and Review, 22, 944–954. https://doi.org/10.3758/s13423-014-0759-2

86.

Rucker

D. D.

McShane

B. B.

Preacher

K. J.

(2015). A researcher’s guide to regression, discretization, and median splits of continuous variables. Journal of Consumer Psychology, 25, 666–678. https://doi.org/10.1016/j.jcps.2015.04.004

87.

Schönbrodt

F. D.

Perugini

(2013). At what sample size do correlations stabilize? Journal of Research in Personality, 47, 609–612. https://doi.org/10.1016/j.jrp.2013.05.009

88.

Singmann

Bolker

Westfall

Aust

(2019). afex: Analysis of factorial experiments (Version 0.16.1) [Computer software]. Comprehensive R Archive Network. https://CRAN.R-project.org/package=afex

89.

Singmann

Kellen

(2019). An introduction to mixed models for experimental psychology. In Spieler

D. H.

Schumacher

(Eds.), New methods in cognitive psychology (pp. 4–31). Taylor and Francis. https://doi.org/10.4324/9780429318405-2

90.

Singmann

Klauer

K. C.

Kellen

(2014). Intuitive logic revisited: New data and a Bayesian mixed model meta-analysis. PLOS ONE, 9(4), Article e94223. https://doi.org/10.1371/journal.pone.0094223

91.

Sloman

S. A.

(1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3–22. https://doi.org/10.1037/0033-2909.119.1.3

92.

Sloman

S. A.

(2012). Two systems of reasoning. In Gilovich

Griffin

Kahneman

(Eds.), Heuristics and biases (pp. 379–396). Cambridge University Press. https://doi.org/10.1017/cbo9780511808098.024

93.

Spearman

(1904). The proof and measurement of association between two things. The American Journal of Psychology, 15, 72–101. https://doi.org/10.2307/1412159

94.

Šrol

De Neys

(2021). Predicting individual differences in conflict detection and bias susceptibility during reasoning. Thinking and Reasoning, 27, 38–68. https://doi.org/10.1080/13546783.2019.1708793

95.

Stanovich

K. E.

(1999). Who is rational? Studies in individual differences in reasoning. Lawrence Erlbaum.

96.

Stanovich

K. E.

(2018). Miserliness in human cognition: The interaction of detection, override and mindware. Thinking & Reasoning, 24, 423–444. https://doi.org/10.1080/13546783.2018.1459314

97.

Stanovich

K. E.

West

R. F.

(1997). Reasoning independently of prior belief and individual differences in actively open-minded thinking. Journal of Educational Psychology, 89, 342–357. https://doi.org/10.1037/0022-0663.89.2.342

98.

Stanovich

K. E.

West

R. F.

(2008). On the relative independence of thinking biases and cognitive ability. Journal of Personality and Social Psychology, 94, 672–695. https://doi.org/10.1037/0022-3514.94.4.672

99.

Stephens

R. G.

Dunn

J. C.

Hayes

B. K.

(2018). Are there two processes in reasoning? The dimensionality of inductive and deductive inferences. Psychological Review, 125, 218–244. https://doi.org/10.1037/rev0000088

100.

Stephens

R. G.

Matzke

Hayes

B. K.

(2019). Disappearing dissociations in experimental psychology: Using state-trace analysis to test for multiple processes. Journal of Mathematical Psychology, 90, 3–22. https://doi.org/10.1016/j.jmp.2018.11.003

101.

Stupple

E. J. N.

Ball

L. J.

Evans

J. S. B. T.

Kamal-Smith

(2011). When logic and belief collide: Individual differences in reasoning times support a selective processing model. Journal of Cognitive Psychology, 23, 931–941. https://doi.org/10.1080/20445911.2011.589381

102.

Thompson

V. A.

Johnson

S. C.

(2014). Conflict, metacognition, and analytic thinking. Thinking and Reasoning, 20, 215–244. https://doi.org/10.1080/13546783.2013.869763

103.

Thompson

V. A.

Newman

I. R.

(2017). Logical intuitions and other conundra for dual process theories. In De Neys

(Ed.), Dual process theory 2.0 (pp. 121–136). Routledge. https://doi.org/10.4324/9781315204550

104.

Thompson

V. A.

Pennycook

Trippas

Evans

J. S. B. T.

(2018). Do smart people have better intuitions? Journal of Experimental Psychology: General, 147(7), 945–961. https://doi.org/10.1037/xge0000457

105.

Toplak

M. E.

West

R. F.

Stanovich

K. E.

(2011). The Cognitive Reflection Test as a predictor of performance on heuristics-and-biases tasks. Memory and Cognition, 39(7), 1275–1289. https://doi.org/10.3758/s13421-011-0104-1

106.

Toplak

M. E.

West

R. F.

Stanovich

K. E.

(2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking and Reasoning, 20, 147–168. https://doi.org/10.1080/13546783.2013.844729

107.

Topolinski

(2011). A process model of intuition. European Review of Social Psychology, 22, 274–315. https://doi.org/10.1080/10463283.2011.640078

108.

Topolinski

(2017). The sense of coherence: How intuition guides reasoning and thinking. In Ball

L. J.

Thompson

V. A.

(Eds.), International handbook of thinking and reasoning (pp. 559–574). Routledge/Taylor & Francis Group.

109.

Topolinski

Reber

(2010). Immediate truth: Temporal contiguity between a cognitive problem and its solution determines experienced veracity of the solution. Cognition, 114, 117–122. https://doi.org/10.1016/j.cognition.2009.09.009

110.

Topolinski

Strack

(2009). The analysis of intuition: Processing fluency and affect in judgements of semantic coherence. Cognition and Emotion, 23, 1465–1503. https://doi.org/10.1080/02699930802420745

111.

Trippas

Handley

S. J.

(2018). The parallel processing model of belief bias: Review and extensions. In L. Ball & W. De Neys (Eds.), Dual process theory 2.0 (pp. 28–46). Routledge. https://doi.org/10.4324/9781315204550-3

112.

Trippas

Handley

S. J.

Verde

M. F.

(2013). The SDT model of belief bias: Complexity, time, and cognitive ability mediate the effects of believability. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1393–1402. https://doi.org/10.1037/a0032398

113.

Trippas

Handley

S. J.

Verde

M. F.

Morsanyi

(2016). Logic brightens my day: Evidence for implicit sensitivity to logical validity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42, 1448–1457. https://doi.org/10.1037/xlm0000248

114.

Trippas

Kellen

Singmann

Pennycook

Koehler

D. J.

Fugelsang

J. A.

Dubé

(2018). Characterizing belief bias in syllogistic reasoning: A hierarchical Bayesian meta-analysis of ROC data. Psychonomic Bulletin and Review, 6, 57–86. https://doi.org/10.3758/s13423-018-1460-7

115.

Trippas

Pennycook

Verde

M. F.

Handley

S. J.

(2015). Better but still biased: Analytic cognitive style and belief bias. Thinking and Reasoning, 21, 431–445. https://doi.org/10.1080/13546783.2015.1016450

116.

Trippas

Thompson

V. A.

Handley

S. J.

(2017). When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias. Memory and Cognition, 45(4), 539–552. https://doi.org/10.3758/s13421-016-0680-1

117.

Tversky

Kahneman

(1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90, 293–315. https://doi.org/10.1037/0033-295X.90.4.293

118.

Vernon

P. A.

(1983). Speed of information processing and general intelligence. Intelligence, 7, 53–70. https://doi.org/10.1016/0160-2896(83)90006-5

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

5.10 MB

The bright homunculus in our head: Individual differences in intuitive sensitivity to logical validity

Abstract

Keywords

Get full access to this article

References

Supplementary Material