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1. Work in Progress: Using Neuro-responses to Understand Creativity, the Engineering Design Process, and Concept Generation

   https://doi.org/10.18260/1-2--35701  

   Hartog, Tess ; Marshall, Megan ; Alhashim, Amin ; Ahad, Md Tanvir ; Siddique, Zahed ( January 2020 , Paper presented at 2020 ASEE Virtual Annual Conference)

   null (Ed.)

   Investigations of creativity have been an intriguing topic for a long time, but assessing creativity is extremely complex. Creativity is a cornerstone of engineering disciplines, so understanding creativity and how to enhance creative abilities through engineering education has received substantial attention. Fields outside of engineering are no stranger to neuro-investigations of creativity and although some neuro-response studies have been conducted to understand creativity in engineering, these studies need to map the engineering design and concept generation processes better. Using neuroimaging techniques alongside engineering design and concept generation processes is necessary for understanding how to improve creative idea generation and creativity studies in engineering. In this paper, a survey is provided of the literature for the different neurological approaches that have been used to study the engineering design process and creative processes. Also presented are proposed strategies to apply these neurological approaches to engineering design to understand the creative process in greater detail. Furthermore, results from a pilot study investigating neuro-responses of engineers are presented. 

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2. Tools for Assessing the Creative Person, Process, and Product in Engineering Education

   Lerdal, Kristin ; Surovek, Andrea ; Cetin, Kristen ; Cetin, Bora ; Ahn, Benjamin ( June 2019 , ASEE Annual Conference proceedings)

   WIP: Assessing the Creative Person, Process and Product in Engineering Education This evidence-based practice paper provides guidance in assessing creativity in engineering education. In the last decade, a number of vision statements on the future of engineering education (e.g. Educating the Engineer of 2020, the ASCE Body of Knowledge) point to the fact that creativity is essential to engineering innovation; it is regarded as an important attribute in the education of engineers in order to meet the most urgent national challenges and to drive economic growth in the new millennium. Yet studies suggest that engineering students’ creative skills are being left underdeveloped or diminish over the course of their studies, or worse, that students who consider themselves to be creative are being driven away from engineering as a chosen field. On the surface, creativity skills are perceived as difficult to utilize in the engineering classroom, primarily due to the didactic nature of science and engineering instruction. Assessing the product of open ended or ill-structured assignments remains a difficult task as well. This study examines available assessments for creativity that are founded in three of the Four Ps of creativity: person, process, product (the fourth P, press, is not considered in this work.) The intent is to identify verified metrics that can be used to quantify creativity with a particular look to whether the metrics are appropriate for creativity, particularly as they pertain to the science and engineering domains. These metrics are examined for applicability to science and engineering, ease of administration and completion, expertise required to score, cost to administer, and time required to administer. Rather than determining the “best” metrics, this examination will provide guidelines for engineering educators and researchers interested in creativity for selecting appropriate metrics to be used in classrooms and research studies based on metric attributes. 

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3. Creative Self-Efficacy of Undergraduate Women Engineering Majors

   Delahanty, C. ; & Silverman, J. ( July 2021 , 2021 ASEE Virtual Annual Conference Content Access)

   Creative self-efficacy (CSE) was studied in connection to beliefs about creativity. CSE is one’s belief in their own creative potential. The belief that creativity can improve was discussed as a “Growth Creativity Mindset” (GCM), and the belief that creativity cannot improve was discussed as a “Fixed Creativity Mindset” (FCM). Creativity within engineering has been described as crucial to the field, and as an aspect that is appealing to women engineers. Undergraduate women engineering students local to the Philadelphia area volunteered to take a survey of CSE and beliefs about creativity. Quantitative data analysis showed that an increase in GCM likely results in an increase in CSE for students with higher than average GPA. A change in CSE had no effect on FCM. Interviews were conducted with 15 survey respondents with different levels of CSE who met criteria for success in the engineering major (2.5 GPA or above and successful completion of calculus II). Synthesis of the quantitative and qualitative data revealed that interview participants had similar lived experiences that lead them to a level of success in the engineering major, but different lived experiences that distinguished them with respect to CSE level. All participants were exposed to project based learning (PBL), had strong personal influences, exhibited perseverance in overcoming struggles, and described their negative perceptions of engineering before entering the major. Participants with all levels of CSE highlighted their own creativity with respect to the performing and visual arts, before reflecting on innovation as creative. Most participants with low CSE described their lack of creativity in the arts. They also discussed being “intimidated” by negative classroom experiences more than their peers with higher levels of CSE. Those with low CSE were also exposed to more engineering centered experiences in high school, and most had a parent who worked in the profession. It is expected that this research will provide a more comprehensive understanding of CSE, perceptions of engineering as a creative field, and the educational reform needed that connects creativity to engineering in an atmosphere that welcomes diversity. 

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4. Delahanty, C., & Silverman, J. (2022, August), Lived Experiences that Influence How Women Engineering Majors Describe Themselves as Creative, Paper presented at 2022 ASEE Annual Conference Content Access, https://peer.asee.org/collections/131

   Delahanty, C. ; Silverman, J. ( August 2022 , 2022 ASEE Annual Conference Content Access)

   Engineering is a creative profession where diverse perspectives of both men and women are crucial to the field. The importance of better understanding the pipeline of female students into engineering, and the path to their success in the major is evident. In 2017, women comprised approximately 20% of engineering graduates, up from 18% in 1997, and 15% never entered the engineering workforce. In 2019, women comprised 48% of the workforce, 34% of the STEM workforce, and only 16% of practicing engineers, a 3% increase from 2009. In an effort to better understand these disparities, this mixed methods research investigated the creative self-efficacy (CSE) of women engineering majors and their beliefs about creativity in relation to lived experiences and explores the research question: In what ways do undergraduate women engineering students describe their creativity and how their lived experiences influenced their decision to major in engineering? The researchers investigated the lived experiences of women engineering students before they entered the engineering major in relation to the way they described themselves as creative. A survey of CSE and beliefs about creativity was administered to 121 undergraduate women engineering students who volunteered for this study. Interviews were conducted of 15 participants selected from survey results with different levels of CSE who met the researcher’s criteria for success in the engineering major. The findings of this study lead to several conclusions: (1) students’ descriptions of themselves as creative corresponded more with the arts than to innovation in engineering; (2) students who described themselves as less creative: (a) had a lower level of CSE; (b) had a greater exposure to engineering in high school through engineering-centered courses and clubs; (c) had a family member who worked in the profession; (d) described more negative classroom experiences at all educational levels that involved intimidation, isolation, and gender-bias. 

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5. Electroencephalogram Experimentation to Understand Creativity of Mechanical Engineering Students

   https://doi.org/10.1115/1.4056473  

   Ahad, Md Tanvir ; Hartog, Tess ; Alhashim, Amin G. ; Marshall, Megan ; Siddique, Zahed ( January 2023 , ASME Open Journal of Engineering)

   Electroencephalogram (EEG) alpha power (8–13 Hz) is a characteristic of various creative task conditions and is involved in creative ideation. Alpha power varies as a function of creativity-related task demands. This study investigated the event-related potentials (ERPs), alpha power activation, and potential machine learning (ML) to classify the neural responses of engineering students involved with creativity task. All participants performed a modified alternate uses task (AUT), in which participants categorized functions (or uses) for everyday objects as either creative, nonsense, or common. At first, this study investigated the fundamental ERPs over central and parietooccipital temporal areas. The bio-responses to understand creativity in engineering students demonstrates that nonsensical and creative stimuli elicit larger N400 amplitudes (−1.107 mV and −0.755 mV, respectively) than common uses (0.0859 mV) on the 300–500 ms window. N400 effect was observed on 300–500 ms window from the grand average waveforms of each electrode of interest. ANOVA analysis identified a significant main effect: decreased alpha power during creative ideation, especially over (O1/2, P7/8) parietooccipital temporal area. Machine learning is used to classify the specific temporal area data’s neural responses (creative, nonsense, and common). A k-nearest neighbors (kNN) classifier was used, and results were evaluated in terms of accuracy, precision, recall, and F1- score using the collected datasets from the participants. With an overall 99.92% accuracy and area under the curve at 0.9995, the kNN classifier successfully classified the participants’ neural responses. These results have great potential for broader adaptation of machine learning techniques in creativity research.

    

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