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CHANGES IN COGNITION AND NEUROCOGNITION WHEN THINKING ALOUD DURING DESIGN

Published online by Cambridge University Press:  19 June 2023

Tripp Shealy ,
John Gero ,
Paulo Ignacio  and
Inuk Song
Tripp Shealy*
Affiliation:
Virginia Tech;
John Gero
Affiliation:
University of North Carolina at Charlotte.
Paulo Ignacio
Affiliation:
Virginia Tech;
Inuk Song
Affiliation:
Virginia Tech;
*
Shealy, Tripp, Virginia Tech, United States of America, [email protected]

Abstract

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The think-aloud protocol provides researchers an insight into the designer's mental state, but little is understood about how thinking aloud influences design. The study presented in this paper sets out to measure the cognitive and neurocognitive changes in designers when thinking aloud. Engineering students (n=50) were randomly assigned to the think-aloud or control group. Students were outfitted with a functional near-infrared spectroscopy band. Students were asked to design a personal entertainment system. The think-aloud group spent significantly less time designing. Their design sketches included significantly fewer words. The think-aloud group also required significantly more resources in the left and right dorsolateral prefrontal cortex (DLPFC). The left DLPFC is often recruited for language processing, and the right DLPFC is involved in visual representation and problem-solving. The faster depletion of neurocognitive resources may have contributed to less time designing. Thinking aloud influences design cognition and neurocognition, but these effects are only now becoming apparent. More research and the adoption of neuroscience techniques can help shed light on these differences.

Keywords

Design cognitionDesign methodsDesign processprotocol analysisfNIRS
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 867 - 876
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Alexiou, K., Zamenopoulos, T., Gilbert, S. (2011), “Imaging the Designing Brain: A Neurocognitive Exploration of Design Thinking”, Design Computing and Cognition. Springer Netherlands, pp. 489–504. https://doi.org/10.1007/978-94-007-0510-4_26CrossRefGoogle Scholar
Amaro, E., Barker, G.J. (2006), “Study design in fMRI: Basic principles”, Brain and Cognition Vol. 60, pp. 220–232. https://doi.org/10.1016/j.bandc.2005.11.009CrossRefGoogle Scholar
Baddeley, A. (2003), “Working memory: looking back and looking forward”, Nature Reviews Neuroscience Vol. 4, pp. 829–839. https://doi.org/10.1038/nrn1201CrossRefGoogle Scholar
Basil, M.D. (2012), “Multiple Resource Theory”, Encyclopedia of the Sciences of Learning. Springer US, Boston, MA, pp. 2384–2385. https://doi.org/10.1007/978-1-4419-1428-6_25CrossRefGoogle Scholar
Bilda, Z., Gero, J.S. (2005), “Does sketching off-load visuo-spatial working memory”, Studying designers, Sydney, Australia, pp. 145–160. Available at: https://cs.gmu.edu/∼jgero/publications/2005/05BildaGeroSD05.pdf (Accessed: 20 April 2021)Google Scholar
Blumenfeld, R.S., Parks, C.M., Yonelinas, A.P., Ranganath, C. (2011), “Putting the pieces together: The role of dorsolateral prefrontal cortex in relational memory encoding”, Journal of Cognitive Neuroscience Vol. 23, pp. 257–265. https://doi.org/10.1162/jocn.2010.21459CrossRefGoogle ScholarPubMed
Buchsbaum, B.R., D'Esposito, M. (2008), “The search for the phonological store: From loop to convolution”, Journal of Cognitive Neuroscience Vol. 20, pp. 762–778. https://doi.org/10.1162/jocn.2008.20501CrossRefGoogle ScholarPubMed
Bunce, S.C., Izzetoglu, K., Ayaz, H., Shewokis, P., Izzetoglu, M., Pourrezaei, K., Onaral, B. (2011), “Implementation of fNIRS for Monitoring Levels of Expertise and Mental Workload”, Foundations of Augmented Cognition, Springer Berlin Heidelberg, pp. 13–22. https://doi.org/10.1007/978-3-642-21852-1_2CrossRefGoogle Scholar
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., Vidal, F. (2015), “Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view”, International Journal of Psychophysiology Vol. 97, pp. 210–220. https://doi.org/10.1016/j.ijpsycho.2015.05.004CrossRefGoogle Scholar
Byrne, A. (2011), “Measurement of Mental Workload in Clinical Medicine: A Review Study”, Anesthesia and Pain Medicine Vol. 1, pp. 90–94. https://doi.org/10.5812/kowsar.22287523.2045CrossRefGoogle Scholar
Causse, M., Chua, Z., Peysakhovich, V., Campo, N.D., Matton, N. (2017), “Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS”, Scientific Reports Vol. 7, pp. 1–15. https://doi.org/10.1038/s41598-017-05378-xCrossRefGoogle Scholar
Csipo, T., Lipecz, A., Mukli, P., Bahadli, D., Abdulhussein, O., Owens, C.D., Tarantini, S., Hand, R.A., Yabluchanska, V., Kellawan, J.M., Sorond, F., James, J.A., Csiszar, A., Ungvari, Z.I., Yabluchanskiy, A. (2021), “Increased cognitive workload evokes greater neurovascular coupling responses in healthy young adults”, PLOS ONE Vol. 16, e0250043. https://doi.org/10.1371/journal.pone.0250043CrossRefGoogle ScholarPubMed
Curtis, C.E., D'Esposito, M. (2003), “Persistent activity in the prefrontal cortex during working memory”, Trends in Cognitive Sciences Vol. 7, pp. 415–423.CrossRefGoogle ScholarPubMed
Dietrich, A. (2004), “The cognitive neuroscience of creativity”, Psychonomic Bulletin & Review Vol. 11, pp. 1011–1026. https://doi.org/10.3758/BF03196731Google Scholar
Ericsson, K.A., Simon, H.A. (1993), “Protocol analysis: Verbal reports as data”, Protocol analysis: Verbal reports as data, The MIT Press, Cambridge, MA, US.CrossRefGoogle Scholar
Ericsson, K.A., Simon, H.A. (1980), “Verbal reports as data”. Psychological Review Vol. 87, pp. 215–251. https://doi.org/10.1037/0033-295X.87.3.215CrossRefGoogle Scholar
Euston, D.R., Gruber, A.J., McNaughton, B.L. (2012), “The Role of Medial Prefrontal Cortex in Memory and Decision Making”, Neuron Vol. 76, 1057–1070. https://doi.org/10.1016/j.neuron.2012.12.002CrossRefGoogle ScholarPubMed
Fox, M.C., Ericsson, K.A., Best, R. (2011), “Do procedures for verbal reporting of thinking have to be reactive? A meta-analysis and recommendations for best reporting methods”, Psychological Bulletin Vol. 137, pp. 316–344. https://doi.org/10.1037/a0021663CrossRefGoogle Scholar
Garcin, B., Volle, E., Dubois, B., Levy, R. (2012), “Similar or Different? The Role of the Ventrolateral Prefrontal Cortex in Similarity Detection”, PLOS ONE Vol. 7, e34164. https://doi.org/10.1371/journal.pone.0034164CrossRefGoogle ScholarPubMed
Gero, J.S. (2015), Studying Visual and Spatial Reasoning for Design Creativity, Springer Netherlands, Dordrecht.CrossRefGoogle Scholar
Gero, J.S., Milovanovic, J. (2020), “A framework for studying design thinking through measuring designers’ minds, bodies and brains”, Design Science Vol. 6. https://doi.org/10.1017/dsj.2020.15CrossRefGoogle Scholar
Grohs, J., Shealy, T., Maczka, D., Hu, M. (2017), “Evaluating the Potential of fNIRS Neuroimaging to Study Engineering Problem Solving and Design”, ASCE, Columbus, OH. Available at: https://peer.asee.org/evaluating-the-potential-of-fnirs-neuroimaging-to-study-engineering-problem-solving-and-design (Accessed: 06 May 2021)Google Scholar
Hertrich, I., Dietrich, S., Blum, C., Ackermann, H. (2021), “The Role of the Dorsolateral Prefrontal Cortex for Speech and Language Processing”, Frontiers in Human Neuroscience Vol. 15.CrossRefGoogle ScholarPubMed
Hertzum, M., Borlund, P., Kristoffersen, K.B. (2015), “What Do Thinking-Aloud Participants Say? A Comparison of Moderated and Unmoderated Usability Sessions”, International Journal of Human–Computer Interaction Vol. 31, pp. 557–570. https://doi.org/10.1080/10447318.2015.1065691CrossRefGoogle Scholar
Hertzum, M., Holmegaard, K.D. (2015), “Thinking Aloud Influences Perceived Time”, Human Factors Vol. 57, pp. 101–109. https://doi.org/10.1177/0018720814540208CrossRefGoogle Scholar
Hu, M., 2018. Neuroscience for Engineering Sustainability: Measuring Cognition During Design Ideation and Systems Thinking Among Students in Engineering (Thesis). Virginia Tech.Google Scholar
Hu, M., Shealy, T. (2019), “Application of Functional Near-Infrared Spectroscopy to Measure Engineering Decision-Making and Design Cognition: Literature Review and Synthesis of Methods”, Journal of Computing in Civil Engineering Vol. 33, 04019034. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000848CrossRefGoogle Scholar
Hu, M., Shealy, T., Gero, J.S. (2018), “Neuro-cognitive Differences Among Engineering Students when Using Unstructured, Partially Structured, and Structured Design Concept Generation Techniques”, ASEE Annual Conference & Exposition.Google Scholar
Hu, M., Shealy, T., Milovanovic, J. (2021), “Cognitive differences among first-year and senior engineering students when generating design solutions with and without additional dimensions of sustainability”, Design Science Vol. 7. https://doi.org/10.1017/dsj.2021.3CrossRefGoogle Scholar
Jahani, S., Fantana, A.L., Harper, D., Ellison, J.M., Boas, D.A., Forester, B.P., Yücel, M.A. (2017), “fNIRS can robustly measure brain activity during memory encoding and retrieval in healthy subjects”, Scientific Reports Vol. 7. https://doi.org/10.1038/s41598-017-09868-wCrossRefGoogle Scholar
Jamali, M., Grannan, B., Haroush, K., Moses, Z.B., Eskandar, E.N., Herrington, T., Patel, S., Williams, Z.M. (2019), “Dorsolateral prefrontal neurons mediate subjective decisions and their variation in humans”, Nature Neuroscience Vol. 22, pp. 1010–1020. https://doi.org/10.1038/s41593-019-0378-3CrossRefGoogle Scholar
Lara, A.H., Wallis, J.D. (2015), “The Role of Prefrontal Cortex in Working Memory: A Mini Review.” Frontiers in Systems Neuroscience Vol. 9, pp. 173. https://doi.org/10.3389/fnsys.2015.00173CrossRefGoogle Scholar
Maior, H.A., Pike, M., Wilson, M.L., Sharples, S. (2014), “Continuous detection of workload overload: An fnirs approach”, Contemporary Ergonomics and Human Factors Vol. 450.Google Scholar
Mars, R.B., Grol, M.J. (2007), “Dorsolateral Prefrontal Cortex, Working Memory, and Prospective Coding for Action”, Journal of Neuroscience Vol. 27, pp. 1801–1802. https://doi.org/10.1523/JNEUROSCI.5344-06.2007CrossRefGoogle ScholarPubMed
Midha, S., Maior, H.A., Wilson, M.L., Sharples, S. (2021), “Measuring Mental Workload Variations in Office Work Tasks using fNIRS”, International Journal of Human-Computer Studies, Vol. 147, 102580. https://doi.org/10.1016/j.ijhcs.2020.102580CrossRefGoogle Scholar
Mihov, K.M., Denzler, M., Förster, J. (2010), “Hemispheric specialization and creative thinking: A meta-analytic review of lateralization of creativity”, Brain and Cognition, Vol. 72, pp. 442–448. https://doi.org/10.1016/j.bandc.2009.12.007CrossRefGoogle Scholar
Milovanovic, J., Hu, M., Shealy, T., Gero, J. (2021), “Characterization of concept generation for engineering design through temporal brain network analysis”, Design Studies, Vol. 76, 101044. https://doi.org/10.1016/j.destud.2021.101044CrossRefGoogle Scholar
Milovanovic, J., Hu, M., Shealy, T., Gero, J. (2020), “Evolution of Brain Network Connectivity in the Prefrontal Cortex During Concept Generation Using Brainstorming for a Design Task”, ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers Digital Collection. https://doi.org/10.1115/DETC2020-22563CrossRefGoogle Scholar
Peck, E.M., Afergan, D., Yuksel, B.F., Lalooses, F., Jacob, R.J.K. (2014), “Using fNIRS to Measure Mental Workload in the Real World”, Advances in Physiological Computing, Human–Computer Interaction Series. Springer, London, pp. 117–139. https://doi.org/10.1007/978-1-4471-6392-3_6CrossRefGoogle Scholar
Pike, M.F., Maior, H.A., Porcheron, M., Sharples, S.C., Wilson, M.L. (2014), “Measuring the Effect of Think Aloud Protocols on Workload Using fNIRS”, SIGCHI Conference on Human Factors in Computing Systems, ACM, New York, NY, USA, pp. 3807–3816. https://doi.org/10.1145/2556288.2556974CrossRefGoogle Scholar
Pisapia, N.D., Bacci, F., Parrott, D., Melcher, D. (2016), “Brain networks for visual creativity: a functional connectivity study of planning a visual artwork”, Scientific Reports, Vol. 6, 39185. https://doi.org/10.1038/srep39185CrossRefGoogle Scholar
Rodriguez-Jimenez, R., Avila, C., Garcia-Navarro, C., Bagney, A., de Aragon, A.M., Ventura-Campos, N., Martinez-Gras, I., Forn, C., Ponce, G., Rubio, G., Jimenez-Arriero, M.A., Palomo, T. (2009), “Differential dorsolateral prefrontal cortex activation during a verbal n-back task according to sensory modality,” Behavioural Brain Research Vol. 205, pp. 299–302. https://doi.org/10.1016/j.bbr.2009.08.022CrossRefGoogle Scholar
Rolls, E.T., Cheng, W., Feng, J. (2020), “The orbitofrontal cortex: reward, emotion and depression”, Brain Communications Vol. 2, fcaa196. https://doi.org/10.1093/braincomms/fcaa196CrossRefGoogle Scholar
Schneider, W.X., Owen, A.M., Duncan, J. (2012) Executive Control and the Frontal Lobe: Current Issues, Springer, Berlin, Heidelberg.Google Scholar
Shealy, T., Grohs, J., Hu, M., Maczka, D., Panneton, R. (2017), “Investigating Design Cognition during Brainstorming Tasks with Freshmen and Senior Engineering Students using Functional Near Infrared Spectroscopy”, ASEE Annual Conference, Columbus, OH.Google Scholar
Shealy, T., Hu, M. (2017), “Evaluating the potential of neuroimaging methods to study engineering cognition and project-level decision making”, EPOC-MW Conference, Engineering Project Organization Society, Fallen Leaf Lake, CA.Google Scholar
Shulman, G.L., Pope, D.L.W., Astafiev, S.V., McAvoy, M.P., Snyder, A.Z., Corbetta, M. (2010), “Right Hemisphere Dominance during Spatial Selective Attention and Target Detection Occurs Outside the Dorsal Frontoparietal Network”, Journal of Neuroscience, Vol. 30, pp. 3640–3651. https://doi.org/10.1523/JNEUROSCI.4085-09.2010CrossRefGoogle ScholarPubMed
Strait, M., Scheutz, M. (2014), “What we can and cannot (yet) do with functional near infrared spectroscopy”, Frontiers in Neuroscience Vol. 8. https://doi.org/10.3389/fnins.2014.00117CrossRefGoogle Scholar
Sun, S., Li, T., Zhou, X. (2021), “Effects of thinking aloud on cognitive effort in translation”, Linguistica Antverpiensia, New Series – Themes in Translation Studies Vol. 19.Google Scholar
Viswanathan, V.K. (2017), “Design fixation to examples: A study on the time decay of fixation”, Proceedings of the 21st International Conference on Engineering Design (ICED 17), Vol 8, Vancouver, Canada, 21-25.08.2017.Google Scholar
Whitehead, A., Montgomery, C., Swettenham, L., Robinson, N.J. (2022), “The Effect of Think Aloud on Performance and Brain Oxygenation During Cycling – An Exploratory Study”, Perception Motor Skills, Vol. 129, 1115–1136. https://doi.org/10.1177/00315125221104769CrossRefGoogle Scholar
Wickens, C.D. (2008), “Multiple Resources and Mental Workload”, Human Factors, Vol. 50, pp. 449–455. https://doi.org/10.1518/001872008X288394CrossRefGoogle ScholarPubMed