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dc.contributor.advisorSiddique, Zahed
dc.contributor.authorMarshall, Megan
dc.date.accessioned2020-08-11T19:31:57Z
dc.date.available2020-08-11T19:31:57Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/11244/325380
dc.description.abstractThe need for creativity in engineering is far from a new concept. In fact, the idea of creativity as a key competency in engineering was identified as far back as the 1960s (Jones, 1964; McDermid, 1965; Sprecher, 1959). Multiple recent reports have also recognized the need for engineers to be “creative” and “innovative,” in addition to having sound technical skills (Robinson et al., 2005; National Academy of Engineering, 2004, 2013; Petrone, 2019). But what exactly is “creativity”? How can it be measured? How can it be cultivated in engineers and used to improve processes and products? Defining creativity has been an ongoing source of debate (Amabile, 1988; Parkhurst, 1999; Plucker et al., 2004; Simonton, 2012; Abraham, 2018). This is because creativity is an extremely complex concept contingent on multiple variables and assumptions, which also makes it hard to measure. The only two aspects many researchers consistently agree on in any definition of creativity are novelty/originality and appropriateness. Novelty/originality qualitatively is uniqueness or unusualness within a context; quantitatively it is statistical infrequency. Appropriateness is value or usefulness within a context (Abraham, 2018). In this research, these aspects of creativity are explored, and a specific definition is identified to lay a foundation for measuring creativity in an engineering context. Many commonly used methods to measure creativity are also examined, and the neuroscientific techniques of electroencephalography (EEG) and event-related potentials (ERPs) are presented as a direct way to measure creativity quantitatively. EEGs measure the voltage fluctuations on the scalp produced by the postsynaptic activity of groups of neurons firing during mental processes, and ERPs are EEG signals that are time-locked to a stimulus, noted as positive or negative signal amplitude peaks or fluctuations correlated to specific times relative to a stimulus (Luck, 2014; Abraham, 2018). Using these methods to measure creativity quantitatively enable the study of various underlying components of creative processes. For this research, a case study using ERPs is performed to analyze components related to creativity in engineers. Specifically, the N400 component, a negative amplitude occurring between 300-500ms post-stimulus, is investigated in relation to novelty and appropriateness (two key aspects of creativity), and conceptual expansion and analogical reasoning (a cognitive process integral to creative thinking) (Abraham, 2018; Kröger et al., 2013; Goucher-Lambert et al., 2018). This study also briefly examines the post-N400 component as a secondary area of interest. Though this was a small case study to investigate the suitableness of this experimental design to study and measure creativity, the initial results were promising, and partially supported the hypothesis posited. Results supported the findings of others that the N400 component does display sensitivity to novelty/unusualness, but its connection to appropriateness during conceptual expansion tasks is less clear (Rutter, Kröger, Hill, Windmann, Hermann, and Abraham, 2012; Kröger, Rutter, Hill, Windmann, Hermann, and Abraham, 2013). In the post-N400 time period, the nonsense condition and creative condition signals diverged, with the nonsense condition continuing a more negative trend while the creative condition experienced a positive shift. More research is needed to fully understand the post-N400 component, but this could be interpreted as creative ideas being successfully integrated into semantic networks (appropriateness) while nonsense ideas fail to be integrated (inappropriateness). This initial case study showed promising results, and in the future could be expanded into a larger, more statistically significant study with more data. Several other areas of interest could also be investigated with this data set, including what areas of the brain show the most activity in general and within specific frequency bands, if any ERPs can be observed in those areas, and other ERPs that may be related to creative processes. Though this was a case study, this experimental design shows promise for future investigations. It is hoped that others build on this research to further understand creativity in engineering design from a neuroscientific perspective, as well as to investigate the possibility of using neuroscientific techniques to measure creativity in engineers in order to develop their creative ability.en_US
dc.languageen_USen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectcreativityen_US
dc.subjectneuroscienceen_US
dc.subjectengineering designen_US
dc.titleAn Investigation of the N400 Component as a Measure of Creativity in Engineering Designen_US
dc.contributor.committeeMemberAllen, Janet
dc.contributor.committeeMemberLiu, Yingtao
dc.date.manuscript2020-07-29
dc.thesis.degreeMaster of Scienceen_US
ou.groupGallogly College of Engineering::School of Aerospace and Mechanical Engineeringen_US


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Attribution-NonCommercial-ShareAlike 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 4.0 International