Reaction time analysis as a method of studying cognitive conflict in mental models

 
Audio is AI-generated
1

Abstract

Context and relevance..One of the rapidly developing directions in contemporary cognitive psychology is the study of mental models, understood as structured sets of beliefs underlying thinking and decision-making. Objective. The aim of this article is to review experimental studies of mental models that employ the reaction time analysisand to develop a framework for preparing, designing, and conducting studies using this method in new domains. Methods and materials. The paper presents an analytical review of key experimental studies in which reaction time is used as an indicator of cognitive processing. Particular attention is paid to the cognitive conflict between intuitive and scientific knowledge. This conflict manifests itself in increased reaction times and a higher number of errors when participants evaluate incongruent statements. Results. The review examines key factors influencing the resolution of this conflict, including level of education, scientific expertise, age, cognitive reflection, and everyday perceptual experience. Major experimental effects related to the coexistence of intuitive and scientific knowledge are described, including their evolutionary, cultural, and individual sources. The paper also discusses theoretical explanations for the persistence of intuitive beliefs and the mechanisms of cognitive control that suppress them. In addition, a research plan is proposed that includes stages of stimulus preparation, experimental procedure, and data analysis. Conclusions. The results highlight the importance of reaction time analysis as a method for studying the coexistence of intuitive and scientific knowledge and open new prospects for research within dual-process theories.

General Information

Keywords: mental models, intuitive theories, beliefs, reaction time, cognitive conflict

Journal rubric: Neurosciences and Cognitive Studies

Article type: review article

DOI: https://doi.org/10.17759/jmfp.2026150113

Funding. The article was written on the basis of the RANEPA state assignment research programme.

Received 20.12.2024

Revised 12.08.2025

Accepted

Published

For citation: Kurbanov, K.A., Loginov, N.I. (2026). Reaction time analysis as a method of studying cognitive conflict in mental models. Journal of Modern Foreign Psychology, 15(1), 145–152. (In Russ.). https://doi.org/10.17759/jmfp.2026150113

© Kurbanov K.A., Loginov N.I., 2026

License: CC BY-NC 4.0

References

  1. Спиридонов, В.Ф., Логинов, Н.И., Аммалайнен, А.В., Ануфриев, Г.В., Ардисламов, В.В. (2025). Ментальные модели в действии. Психология. Журнал Высшей школы экономики, 22(2), 316—338. (на английском языке). http://doi.org/10.17323/1813-8918-2025-2-316-338
    Spiridonov, V.F., Loginov, N.I., Ammalainen, A.V., Anufriev, G.V., Ardislamov, V.V. (2025). Mental models in action. Psychology. Journal of Higher School of Economics, 22(2), 316—338. http://doi.org/10.17323/1813-8918-2025-2-316-338
  2. Algom, D., Fitousi, D., Chajut, E. (2022). Can the Stroop effect serve as the gold standard of conflict monitoring and control? A conceptual critique. Memory and Cognition, 50, 883—897. https://doi.org/10.3758/s13421-021-01251-5
  3. Alper, S., Bayrak, F., Yilmaz, O. (2021). Psychological correlates of COVID-19 conspiracy beliefs and preventive measures: Evidence from Turkey. Current psychology, 40, 5708—5717. https://doi.org/10.1007/s12144-020-00903-0
  4. Bélanger, É., Brault Foisy, L.M., Masson, S. (2025). What insights can response times provide for education research? International Journal of Research and Method in Education, 48(1), 104—119. https://doi.org/10.1080/1743727X.2024.2336146
  5. Binnendyk, J., Pennycook, G. (2022). Intuition, reason, and conspiracy beliefs. Current Opinion in Psychology, 47, Article 101387. https://doi.org/10.1016/j.copsyc.2022.101387
  6. De Neys, W. (2023). Advancing theorizing about fast-and-slow thinking. Behavioral and Brain Sciences, 46, Article e111. https://doi.org/10.1017/S0140525X2200142X
  7. Draheim, C., Tsukahara, J.S., Martin, J.D., Mashburn, C.A., Engle, R.W. (2021). A toolbox approach to improving the measurement of attention control. Journal of Experimental Psychology: General, 150(2), 242—275. https://doi.org/10.1037/xge0000783
  8. Egner, T. (2023). Principles of cognitive control over task focus and task switching. Nature Reviews Psychology, 2, 702—714. https://doi.org/10.1038/s44159-023-00234-4
  9.  
  10. Ghasemi, O., Handley, S.J., Howarth, S., Newman, I.R., Thompson, V. (2022). Logical intuition is not really about logic. Journal of Experimental Psychology: General, 151(9), 2009—2028. https://doi.org/10.1037/xge0001179
  11. Girgis, H., Nguyen, S.P. (2020). Grown or made? Children’s determination of the origins of natural versus processed foods. Cognitive Development, 56, Article 100887. https://doi.org/10.1016/j.cogdev.2020.100887
  12. Hatano, G., Inagaki, K. (1994). Young children's naive theory of biology. Cognition, 50(1-3), 171—188. https://doi.org/10.1016/0010-0277(94)90027-2
  13. Juanchich, M., Sirota, M., Jolles, D., Whiley, L.A. (2021). Are COVID‐19 conspiracies a threat to public health? Psychological characteristics and health protective behaviours of believers. European Journal of Social Psychology, 51(6), 969—989. https://doi.org/10.1002/ejsp.2796
  14. Keil, F. (2024). Intuitive Theories. In: M.C. Frank, A. Majid (Eds.), Open Encyclopedia of Cognitive Science. Cambridge: MIT Press. https://doi.org/10.21428/e2759450.9666c9f2
  15. Keil, F. C. (2022). Wonder: Childhood and the lifelong love of science. Cambridge: MIT Press. https://doi.org/10.7551/mitpress/13640.001.0001
  16. Kelemen, D., Rottman, J., Seston, R. (2013). Professional physical scientists display tenacious teleological tendencies: Purpose-based reasoning as a cognitive default. Journal of Experimental Psychology: General, 142(4), 1074—1083. https://doi.org/10.1037/a0030399
  17. Kreps, S., Dasgupta, N., Brownstein, J.S., Hswen, Y., Kriner, D.L. (2021). Public attitudes toward COVID-19 vaccination: The role of vaccine attributes, incentives, and misinformation. npj Vaccines, 6, Article 73. https://doi.org/10.1038/s41541-021-00335-2
  18. López-Astorga, M., Ragni, M., Johnson-Laird, P.N. (2022). The probability of conditionals: A review. Psychonomic Bulletin and Review, 29, 1—20. https://doi.org/10.3758/s13423-021-01938-5
  19. Margoni, F., Surian, L., Baillargeon, R. (2024). The violation-of-expectation paradigm: A conceptual overview. Psychological Review, 131(3), 716—748. https://doi.org/10.1037/rev0000450
  20. Menendez, D., Mathiaparanam, O.N., Seitz, V., Liu, D., Donovan, A.M., Kalish, C.W., Alibali, M.W., Rosengren, K.S. (2023). Like mother, like daughter: Adults’ judgments about genetic inheritance. Journal of Experimental Psychology: Applied, 29(1), 63—77. https://doi.org/10.1037/xap0000436
  21. Raoelison, M., Thompson, V.A., De Neys, W. (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
  22. Ronfard, S., Brown, S., Doncaster, E., Kelemen, D. (2021). Inhibiting intuition: Scaffolding children's theory construction about species evolution in the face of competing explanations. Cognition, 211, Article 104635. https://doi.org/10.1016/j.cognition.2021.104635
  23. Shtulman, A. (2022a). How intuitive beliefs inoculate us against scientific ones. In: J. Musolino, J. Sommer, P. Hemmer (Eds.), The cognitive science of belief: A multidisciplinary approach (pp. 353—373). Cambridge: Cambridge University Press. https://doi.org/10.1017/9781009001021.025
  24. Shtulman, A. (2022b). Navigating the conflict between science and intuition. In: M. Bélanger, P. Potvin, S. Horsts, A. Shtulman, E.F. Mortimer (Eds.), Multidisciplinary perspectives on representational pluralism in human cognition: Tracing points of convergence in psychology, science education, and philosophy of science (pp. 122—140). New York: Routledge. https://doi.org/10.4324/9781003189930-8
  25. Shtulman, A. (2023). When competing explanations converge: Coronavirus as a case study for why scientific explanations coexist with folk explanations. In: J.N. Schupbach, D.H. Glass (Eds.), Conjunctive explanations: The nature, epistemology, and psychology of explanatory multiplicity (pp. 246—268). New York: Routledge. https://doi.org/10.4324/9781003184324-14
  26. Shtulman, A., Harrington, K. (2016). Tensions between science and intuition across the lifespan. Topics in Cognitive Science, 8(1), 118—137. https://doi.org/10.1111/tops.12174
  27. Shtulman, A., Legare, C.H. (2020). Competing explanations of competing explanations: Accounting for conflict between scientific and folk explanations. Topics in Cognitive Science, 12(4), 1337—1362. https://doi.org/10.1111/tops.12483
  28. Shtulman, A., Young, A.G. (2024). Tempering the tension between science and intuition. Cognition, 243, Article 105680. https://doi.org/10.1016/j.cognition.2023.105680
  29. Stanovich, K.E., Toplak, M.E. (2023). Actively open-minded thinking and its measurement. Journal of Intelligence, 11(2), Article 27. https://doi.org/10.3390/jintelligence11020027
  30. Stricker, J., Vogel, S.E., Schöneburg-Lehnert, S., Krohn, T., Dögnitz, S., Jud, N., Spirk M., Windhaber M.C., Schneider M., Grabner, R.H. (2021). Interference between naive and scientific theories occurs in mathematics and is related to mathematical achievement. Cognition, 214, Article 104789. https://doi.org/10.1016/j.cognition.2021.104789
  31. Strobach, T. (2024). Cognitive control and meta-control in dual-task coordination. Psychonomic Bulletin and Review, 31, 1445—1460. https://doi.org/10.3758/s13423-023-02427-7
  32. Thompson, V.A., Markovits, H. (2021). Reasoning strategy vs cognitive capacity as predictors of individual differences in reasoning performance. Cognition, 217, Article 104866. https://doi.org/10.1016/j.cognition.2021.104866
  33. Wilkinson, H.R., Smid, C., Morris, S., Farran, E.K., Dumontheil, I., Mayer, S., Tolmie, A., Bell, D., Porayska-Pomsta K., Holmes, W., Mareschal, D., Thomas M.S.C., The UnLocke Team. (2020). Domain-specific inhibitory control training to improve children’s learning of counterintuitive concepts in mathematics and science. Journal of Cognitive Enhancement, 4, 296—314. https://doi.org/10.1007/s41465-019-00161-4
  34. Young, A.G., Shtulman, A. (2020a). Children’s cognitive reflection predicts conceptual understanding in science and mathematics. Psychological Science, 31(11), 1396—1408. https://doi.org/10.1177/0956797620954449
  35. Young, A.G., Shtulman, A. (2020b). How children’s cognitive reflection shapes their science understanding. Frontiers in Psychology, 11, Article 1247. https://doi.org/10.3389/fpsyg.2020.01247

Information About the Authors

Kurban A. Kurbanov, Junior Research Fellow, Laboratory for cognitive research, Russian Presidential Academy of National Economy and Public Administration, Moscow, Russian Federation, ORCID: https://orcid.org/0000-0001-7610-4509, e-mail: kurbanov-ka@mail.ru

Nikita I. Loginov, Candidate of Science (Psychology), Associate Professor, Chair of General Psychology, Psychological Department, Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russian Federation, ORCID: https://orcid.org/0000-0002-5994-4191, e-mail: lognikita@yandex.ru

Contribution of the authors

Аuthors participated in the discussion of the results and approved the final text of the manuscript.

Conflict of interest

The authors declare no conflict of interest.

Metrics

 Web Views

Whole time: 2
Previous month: 0
Current month: 2

 PDF Downloads

Whole time: 1
Previous month: 0
Current month: 1

 Total

Whole time: 3
Previous month: 0
Current month: 3