Conceptual fluency in inductive reasoning

Autoři: Michael Dantlgraber aff001;  Tim Kuhlmann aff001;  Ulf-Dietrich Reips aff001
Působiště autorů: Department of Psychology, University of Konstanz, Konstanz, Germany aff001
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225050


Psychological effects connected with fluent processing are called fluency effects. In a sample of 403 participants we test whether conceptual fluency effects can be found in the context of inductive reasoning, a context that has not been investigated before. As a conceptual manipulation we vary the use of symbols (persons and crosses) in reasoning tasks. These symbols were chosen to provide hints for the solution of the implemented tasks and thus manipulate fluency. We found evidence that these hints influence ease of processing. The proportion of solved tasks increased by 11% on average in the condition with conceptual hints, F(1,399) = 13.47, partial η2 = .033, p < .001. However, we did not find an effect of the conceptual manipulation on the temporal perception of the task. In a second study (n = 62) we strengthened our findings by investigating solution strategies for the tasks in more detail, 79% of the participants described the tasks in a way they were intended. Our results illustrate the advantages of the separation of ease of processing, fluency experience, and judgments.

Klíčová slova:

Cognition – Conceptual semantics – Memory – Metacognition – Ontologies – Perception – Reasoning – Sensory perception


1. Flavell JH. Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist. 1979;34:906–911. doi: 10.1037/0003-066X.34.10.906

2. Schwarz N, Bless H, Strack F, Klumpp G, Rittenauer-Schatka H, Simons A. Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology. 1991;61:195–202. doi: 10.1037/0022-3514.61.2.195

3. Tversky A, Kahneman D. Availability: A heuristic for judging frequency and probability. Cognitive Psychology. 1973;5:207–232. doi: 10.1017/CBO9780511809477.012

4. Alter AL, Oppenheimer DM. Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review. 2009;13:219–235. doi: 10.1177/1088868309341564 19638628

5. Schwarz N. Metacognitive experiences in consumer judgment and decision making. Journal of Consumer Psychology. 2004;14:332–348. doi: 10.1207/s15327663jcp1404_2

6. Forster M, Leder H, Ansorge U. It felt fluent, and I liked it: Subjective feeling of fluency rather than objective fluency determines liking. Emotion. 2013;13:280–289. doi: 10.1037/a0030115 23088777

7. Reder LM. Strategy selection in question answering. Cognitive Psychology. 1987;19:111–138. doi: 10.1016/0010-0285(87)90005-3

8. Whittlesea BWA. Illusions of familiarity. Journal of Experimental Psychology: Learning, Memory, and Cognition. 1993;19:1235–1253. doi: 10.1037/0278-7393.19.6.1235

9. Winkielman P, Schwarz N, Fazendeiro T, Reber R. The hedonic marking of processing fluency: Implications for evaluative judgment. In Musch J, Klauer KC, editors. The psychology of evaluation: Affective processes in cognition and emotion. Mahwah: NJ Lawrence Erlbaum Associates, Inc; 2003. p. 189–217.

10. Ono F, Kawahara J. The effect of false memory on temporal perception. Psychological Research. 2008;72:61–64. doi: 10.1007/s00426-006-0073-3 16821048

11. Rajaram S, Geraci L. Conceptual fluency selectively influences knowing. Journal of Experimental Psychology. Learning, Memory, and Cognition. 2000;26:1070–1074. doi: 10.1037//0278-7393.26.4.1070 10946380

12. Rajaram S. Remembering and knowing: Two means of access to the personal past. Memory & Cognition. 1993;21:89–102. doi: 10.3758/BF03211168 8433652

13. Jacoby LL, Whitehouse K. An illusion of memory: False recognition influenced by unconscious perception. Journal of Experimental Psychology: General. 1989;118:126–135. doi: 10.1037/0096-3445.118.2.126

14. McGrew KS. The Cattell-Horn-Carroll theory of cognitive abilities: Past, present, and future. In Flanagan DP, Harrison PL, editors. Contemporary intellectual assessment: Theories, tests, and issues. New York: Guilford; 2005. p. 136–181.

15. McGrew KS. CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence. 2009;37:1–10. doi: 10.1016/j.intell.2008.08.004

16. Cattell RB. Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology. 1963;54:1–22. doi: 10.1037/h0046743

17. Thurstone LL. Primary mental abilities. Chicago, IL: University of Chicago Press; 1983. doi: 10.1007/978-94-011-6129-9_8

18. Carroll JB. Human cognitive abilities: A survey of factor analytic studies. New York: Cambridge University Press; 1993. doi: 10.1017/CBO9780511571312

19. Heit E, Rubinstein J. Similarity and property effects in inductive reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition. 1994;37:, 411–422. doi: 10.1037//0278-7393.20.2.411

20. Raven JC. Progressive matrices: A perceptual test of intelligence. London: HK Lewis; 1983.

21. World Medical Association. WMA declaration of Helsinki: Ethical principles for medical research involving human subjects [internet]. 2013 [cited 8 April 2019]. Available from:

22. Henderson JM, Siefert ABC. Types and tokens in transsaccadic object identification: Effects of spatial position and left-right orientation. Psychonomic Bulletin & Review. 2001;8:753–760. doi: 10.3758/BF03196214 11848596

23. Henderson JM, Siefert ABC. The influence of enantiomorphic transformationon transsaccadic object integration. Journal of Experimental Psychology: Human Perception & Performance.1999;25:243–255. doi: 10.1037/0096-1523.25.1.243

24. Pollatsek A, Rayner K, Collins WE. Integrating pictorial information across eye movements. Journal of Experimental Psychology: General. 1984;113:426–442. doi: 10.1037/0096-3445.113.3.426

25. Kuhlmann T, Dantlgraber M, Reips U-D. Investigating measurement equivalence of visual analogue scales and Likert-type scales in Internet-based personality questionnaires. Behavior Research Methods. 2017;49:2173–2181. doi: 10.3758/s13428-016-0850-x 28130728

26. Reips U-D. Internet experiments: Methods, guidelines, metadata. Human Vision and Electronic Imaging XIV, Proceedings of SPIE. 2017;7240:724008. doi: 10.1117/12.823416

27. Reips U-D, Funke F. Interval level measurement with visual analogue scales in internet-based research: VAS Generator. Behavior Research Methods. 2008;40:699–704. doi: 10.3758/brm.40.3.699 18697664

28. Reips U-D, Neuhaus C. WEXTOR: A Web-based tool for generating and visualizing experimental designs and procedures. Behavior Research Methods, Instruments, and Computers. 2002;34:234–240. doi: 10.3758/bf03195449 12109018

29. Aust F, Diedenhofen B, Ullrich S, Musch J. Seriousness checks are useful to improve data validity in online research. Behavior Research Methods. 2013;45:527–535. doi: 10.3758/s13428-012-0265-2 23055170

30. Reips U-D. Standards for Internet-based experimenting. Experimental Psychology. 2002;49:243–256. doi: 10.1026/1618-3169.49.4.243 12455331

31. Garaizar P, Reips U-D. Best practices: Two web browser-based methods for stimulus presentation in behavioral experiments with high resolution timing requirements. Behavior Research Methods. In press. doi: 10.3758/s13428-018-1126-4 30276629

32. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–174. doi: 10.2307/2529310 843571

Článek vyšel v časopise


2019 Číslo 11