Board 344: Neural Correlates of Learning Preferences and Individual Differences in Design Fixation: Preliminary Evidence from Functional Magnetic Resonance Imaging (fMRI)

EVANGELIA G. CHRYSIKOU; John S. Gero; Julie Milovanovic; DongHo Kim

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: NSF Grantees Poster Session
Tagged Topic: NSF Grantees Poster Session
Page Count: 5
DOI: 10.18260/1-2--42967
Permanent URL: https://peer.asee.org/42967
Download Count: 153

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Paper Authors

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EVANGELIA G. CHRYSIKOU Drexel University

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Dr. Evangelia G. Chrysikou is an Associate Professor in the Department of Psychological and Brain Sciences at Drexel University, the Director of the Applied Cognitive and Brain Sciences PhD Program (https://drexel.edu/coas/academics/departments-centers/psychology/research/applied-cognitive-and-brain-science/), and the Associate Dean for Research for the College of Arts and Sciences. She is also the President of the Society for the Neuroscience of Creativity (www.tsfnc.org). She holds a Ph.D. in Brain and Cognitive Sciences from Temple University, where she also completed a year-long postdoctoral appointment in cognitive neuropsychology, followed by postdoctoral training at the Center for Cognitive Neuroscience at the University of Pennsylvania. Dr. Chrysikou uses cognitive neuroscience methods, especially functional brain imaging and noninvasive electric brain stimulation, to study cognitive flexibility and creative thinking and problem solving, as well as the implications of such flexibility for theories of creativity, semantic knowledge organization, and cognitive control.

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John S. Gero University of North Carolina, Charlotte

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John Gero is Research Professor in Computer Science and Architecture at UNCC. He is the author of 800 research articles, editor/author of 56 books. His research publications have 28,000 citations.

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Julie Milovanovic University of North Carolina, Charlotte

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Dr. Milovanovic’s research focuses on design cognition, design neurocognition and design learning. Her research aims at bridging design science and neuroscience to explore novel ways to design and teach design.

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DongHo Kim Drexel University

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Abstract

Problem solving in design is frequently susceptible to fixation, restrictions and mistakes introduced in the design process due to previous practice, that often impede the generation of effective design solutions. Research has shown that the inclusion of examples in the problem’s instructions is associated with a tendency to conform to those examples during creative generation. Individual differences in learning tendencies during concept building might underlie one’s susceptibility to design fixation. In this exploratory study, we investigated the impact of learning preferences and domain differences in design fixation. We hypothesized that an exemplar-based approach to learning—reflected in brain activity patterns—would reinforce the impact of examples in design tasks, by increasing the salience of the example design features relative to the abstract relationships that unite them. In contrast, an abstraction-based approach to learning—reflected in different patterns of neural activity—may emphasize the abstract design rules governing the example designs, thus offering protection from design fixation to their features. Based on prior literature, we further hypothesized that differences in domain expertise between mechanical engineering and product design would mitigate these effects. Mechanical engineering or product design students participated in two experimental sessions. In the first session, they completed multiple learning and individual differences behavioral assessments; in the second session, they underwent a functional magnetic resonance imaging scan (fMRI) while completing learning and design tasks using a tablet compatible for the brain imaging environment. Participants’ thought processes were also captured through concurrent verbal protocols during the scan. We discuss preliminary findings that reflect neural correlates of individual differences in design fixation. We further highlight the importance for engineering education of using a multimethod approach regarding the quantification of design fixation, learning tendencies, and individual differences through various neurocognitive assessments.

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CHRYSIKOU, E. G., & Gero, J. S., & Milovanovic, J., & Kim, D. (2023, June), Board 344: Neural Correlates of Learning Preferences and Individual Differences in Design Fixation: Preliminary Evidence from Functional Magnetic Resonance Imaging (fMRI) Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42967

TY - CPAPER
AB - Problem solving in design is frequently susceptible to fixation, restrictions and mistakes introduced in the design process due to previous practice, that often impede the generation of effective design solutions. Research has shown that the inclusion of examples in the problem’s instructions is associated with a tendency to conform to those examples during creative generation. Individual differences in learning tendencies during concept building might underlie one’s susceptibility to design fixation. In this exploratory study, we investigated the impact of learning preferences and domain differences in design fixation. We hypothesized that an exemplar-based approach to learning—reflected in brain activity patterns—would reinforce the impact of examples in design tasks, by increasing the salience of the example design features relative to the abstract relationships that unite them. In contrast, an abstraction-based approach to learning—reflected in different patterns of neural activity—may emphasize the abstract design rules governing the example designs, thus offering protection from design fixation to their features. Based on prior literature, we further hypothesized that differences in domain expertise between mechanical engineering and product design would mitigate these effects. Mechanical engineering or product design students participated in two experimental sessions. In the first session, they completed multiple learning and individual differences behavioral assessments; in the second session, they underwent a functional magnetic resonance imaging scan (fMRI) while completing learning and design tasks using a tablet compatible for the brain imaging environment. Participants’ thought processes were also captured through concurrent verbal protocols during the scan. We discuss preliminary findings that reflect neural correlates of individual differences in design fixation. We further highlight the importance for engineering education of using a multimethod approach regarding the quantification of design fixation, learning tendencies, and individual differences through various neurocognitive assessments.
AU - EVANGELIA G. CHRYSIKOU
AU - John S. Gero
AU - Julie Milovanovic
AU - DongHo Kim
CY - Baltimore , Maryland
DA - 2023/06/25
PB - ASEE Conferences
TI - Board 344: Neural Correlates of Learning Preferences and Individual Differences in Design Fixation: Preliminary Evidence from Functional Magnetic Resonance Imaging (fMRI)
UR - https://peer.asee.org/42967
DO - 10.18260/1-2--42967
ER -