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Impact of the Stroop Effect on Cognitive Load Using Subjective and Psychophysiological Measures

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Computational Collective Intelligence (ICCCI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12876))

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Abstract

The Stroop effect is a delay in human response between congruent and incongruent stimuli, in which color names interfere with the ability to determine the color of the ink used to print those names. The results of the Stroop test used in our experiment were analyzed from the point of view of human cognitive load. 62 volunteers took part in a study conducted on the iMotions biometric platform in laboratory conditions. Data were collected using observations, Single Ease Question (SEQ) and NASA Task Load Index (NASA-TLX) self-report questionnaires, and galvanic skin response (GSR) biosensor. In total, based on the collected data, 18 performance, subjective and psychophysiological metrics were calculated to measure cognitive load based on Stroop test. Non-parametric tests of statistical significance of differences between individual metrics were performed for the Stroop tasks for the easy and hard level of difficulty. The Spearman’s rank correlation between individual metrics was also analysed. The conducted research allowed to make many interesting observations and showed the usefulness of most measures in the analysis of the cognitive load associated with the Stroop effect.

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References

  1. Farnsworth, B.: The Stroop effect – how it works and why. https://imotions.com/blog/the-stroop-effect/ (2019)

  2. Young, M.S., Brookhuis, K.A., Wickens, C.D., Hancock, P.A.: State of science: mental workload in ergonomics. Ergonomics 58(1), 1–17 (2015)

    Article  Google Scholar 

  3. Sweller, J.: Cognitive load during problem solving: effects on learning. Cogn. Sci. 12(1), 257–285 (1988). https://doi.org/10.1016/0364-0213(88)90023-7

    Article  Google Scholar 

  4. Sweller, J.: Cognitive load theory, learning difficulty, and instructional design. Learn. Instr. 4(4), 295–312 (1994). https://doi.org/10.1016/0959-4752(94)90003-5

    Article  Google Scholar 

  5. Sweller, J., Van Merrienboer, J.J.G., Paas, F.G.W.C.: Cognitive architecture and instructional design. Educ. Psychol. Rev. 10(3), 251–296 (1998). https://doi.org/10.1023/A:1022193728205

    Article  Google Scholar 

  6. Sweller, J.: Cognitive load theory. Psychology of Learning and Motivation – Advances in Research and Theory, vol. 55. Elsevier Inc. (2011). https://doi.org/10.1016/B978-0-12-387691-1.00002-8

  7. Pejović, V., Gjoreski, M., Anderson, C., David, K., Luštrek, M.: Toward cognitive load inference for attention management in ubiquitous systems. IEEE Pervasive Comput. 19(2), 35–45 (2020). https://doi.org/10.1109/MPRV.2020.2968909

    Article  Google Scholar 

  8. Barrouillet, P., Camos, V.: Working Memory: Loss and Reconstruction. Psychology Press (2014). https://doi.org/10.4324/9781315755854

    Book  Google Scholar 

  9. Chen, F., Zhou, J. (eds.): Robust Multimodal Cognitive Load Measurement. HIS, Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31700-7

    Book  Google Scholar 

  10. Sweller, J.: Cognitive load during problem solving: effects on learning. Cogn. Sci. 12(2), 257–285 (1988)

    Article  Google Scholar 

  11. Sweller, J., Merriënboer, J., Paas, F.: Cognitive architecture and instructional design: 20 years later. Educ. Psychol. Rev. 31(2), 261–292 (2019). https://doi.org/10.1007/s10648-019-09465-5

    Article  Google Scholar 

  12. Geary, D.C.: Educating the evolved mind: conceptual foundations for an evolutionary educational psychology. In: Carlson, J.S., Levin, J.R. (eds.) Educating the Evolved Mind: Conceptual Foundations for an Evolutionary Educational Psychology Information Age Charlotte. NC, 1, p. 99 (2007)

    Google Scholar 

  13. Geary, D.C.: An evolutionarily informed education science. Educ. Psychol. 43(4), 179–195 (2008)

    Article  Google Scholar 

  14. Geary, D.C.: Evolutionary educational psychology. APA Educational Psychology Handbook, vol. 1: Theories, Constructs, and Critical Issues, pp. 597–621. American Psychological Association (2012)

    Google Scholar 

  15. Geary, D., Berch, D.: Evolution and children’s cognitive and academic development. In: Geary, D.C., Berch, D.B. (eds.) Evolutionary perspectives on child development and education. EP, pp. 217–249. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29986-0_9

    Chapter  Google Scholar 

  16. Kirschner, P.A., Sweller, J., Kirschner, F., Zambrano, J.: From cognitive load theory to collaborative cognitive load theory. Int. J. Comput. Support. Collab. Learn. 13(2), 213–233 (2018)

    Article  Google Scholar 

  17. Tricot, A., Sweller, J.: Domain-specific knowledge and why teaching generic skills does not work. Educ. Psychol. Rev. 26(2), 265–283 (2014)

    Article  Google Scholar 

  18. Kirschner, P.A., Sweller, J., Clark, R.E.: Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problembased, experiential, and inquiry-based teaching. Educ. Psychol. 41(2), 75–86 (2006)

    Article  Google Scholar 

  19. Sweller, J., Kirschner, P.A., Clark, R.E.: Why minimally guided teaching techniques do not work: a reply to commentaries. Educ. Psychol. 42(2), 115–121 (2007)

    Article  Google Scholar 

  20. Jia, L., Kalyuga, S., Sweller, J.: Altering element Interactivity and variability in example‐practice sequences to enhance learning to write Chinese characters. Appl. Cogn. Psychol. 34(4), 837–843 (2020). https://doi.org/10.1002/acp.3668

    Article  Google Scholar 

  21. Roussel, S., Joulia, D., Tricot, A., Sweller, J.: Learning subject content through a foreign language should not ignore human cognitive architecture: a cognitive load theory approach. Learn. Instr. 52, 69–79 (2017)

    Article  Google Scholar 

  22. Renaud, P., Blondin, J.P.: The stress of Stroop performance: physiological and emotional responses to color-word interference, task pacing, and pacing speed. Int. J. Psychophysiol. 27(2), 87–97 (1997)

    Article  Google Scholar 

  23. Petkar, H.C: Effects of working memory demand on performance and mental stress during the Stroop task. Masters Thesis, Concordia University (2011)

    Google Scholar 

  24. Williams, J.M.G., Mathews, A., MacLeod, C.: The emotional Stroop task and psychopathology. Psychol. Bull. 120(1), 3–24 (1996)

    Article  Google Scholar 

  25. Wagner, P., Wagner, T.: The Galvanic Skin Response GSR Investigation Cheating. http://www.rsu.edu/wpcontent/uploads/2015/06/TheGalvanicSkinResponseGSRInvestigationCheating.pdf (2013). Retrieved 8 Dec 2020

  26. Braithwaite, J., Watson, D., Jones, R., Rowe, M.: A Guide for Analysing Electrodermal Activity (EDA) Skin Conductance Responses (SCRs) for Psychological Experiments. Technical Report, 2nd version. University of Birmingham, UK (2015)

    Google Scholar 

  27. Nourbakhsh, N., Wang, Y., Chen, F., Calvo, R.A.: Using galvanic skin response for cognitive load measurement in arithmetic and reading tasks. In: Proceedings of the 24th Australian Computer-Human Interaction Conference, OzCHI 2012, pp. 420–423 (2012). https://doi.org/10.1145/2414536.2414602

  28. Shi, Y., Ruiz, N., Taib, R., Choi, E., Chen, F.: Galvanic skin response (GSR) as an index of cognitive load. In: CHI 2007 Extended Abstracts on Human Factors in Computing Systems, pp. 2651–2656 (2007)

    Google Scholar 

  29. Yoshihiro, S., Takumi, Y., Koji, S., Akinori, H., Koichi, I., Tetsuo, K.: Use of frequency domain analysis of skin conductance for evaluation of mental workload. J. Physiol. Anthropol. 27(4), 173–177 (2008)

    Article  Google Scholar 

  30. O’Donnell, R.D., Eggemeier, F.T.: Workload assessment methodology. Handbook of Perception and Human Performance. Vol. 2. Cognitive Processes and Performance. K.R. Boff, L. Kaufman and J.P. Thomas (1986)

    Google Scholar 

  31. Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv. Psychol. 52(3), 139–183 (1988)

    Article  Google Scholar 

  32. Hart, S.G.: NASA-task load index (NASA-TLX); 20 years later. In: Proceedings of the 50th Annual Meeting on Human Factors and Ergonomics Society, pp. 904–908 (2006)

    Google Scholar 

  33. Gibson, A., et al.: Assessing usability testing for people living with dementia. In: ACM International Conference Proceeding Series, October, 25–31 (2016). https://doi.org/10.1145/3051488.3051492

  34. GSR R-Notebooks: Processing in iMotions and algorithms used (Latest Version). https://help.imotions.com/hc/en-us/articles/360010312220-GSR-R-Notebooks-Processing-in-iMotions-and-algorithms-used-Latest-Version (2021). Last accessed 6 Jan 2021

  35. Benedek, M., Kaernbach, C.: A continuous measure of phasic electrodermal activity. J. Neurosci. Methods 190(1), 80–91 (2010). https://doi.org/10.1016/j.jneumeth.2010.04.028

    Article  Google Scholar 

  36. R Notebooks (EDA): GSR Epoching, https://help.imotions.com/hc/en-us/articles/360013685940-R-Notebooks-EDA-GSR-Epoching (2021). Last accessed 6 Jan 2021

  37. Gautam, A., Simoes-Capela, N., Schiavone, G., Acharyya, A., de Raedt, W., Van Hoof, C.: A data driven empirical iterative algorithm for GSR signal pre-processing. In: 26th European Signal Processing Conference (EUSIPCO), pp. 1162–1166 (2018). https://doi.org/10.23919/eusipco.2018.8553191

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Authors and Affiliations

  1. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Patient Zihisire Muke, Mateusz Piwowarczyk, Zbigniew Telec, Bogdan Trawiński, Putri Ayu Maharani & Patryk Bresso

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  1. Patient Zihisire Muke
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  2. Mateusz Piwowarczyk
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  3. Zbigniew Telec
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  4. Bogdan Trawiński
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  5. Putri Ayu Maharani
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  6. Patryk Bresso
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Correspondence to Bogdan Trawiński .

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Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Democritus University of Thrace, Kimmeria, Xanthi, Greece

    Lazaros Iliadis

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Zihisire Muke, P., Piwowarczyk, M., Telec, Z., Trawiński, B., Maharani, P.A., Bresso, P. (2021). Impact of the Stroop Effect on Cognitive Load Using Subjective and Psychophysiological Measures. In: Nguyen, N.T., Iliadis, L., Maglogiannis, I., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2021. Lecture Notes in Computer Science(), vol 12876. Springer, Cham. https://doi.org/10.1007/978-3-030-88081-1_14

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  • DOI: https://doi.org/10.1007/978-3-030-88081-1_14

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