scholarly journals IDENTIFYING STRESS SIGNATURES ACROSS THE ENGINEERING DESIGN PROCESS: PERCEIVED STRESS DURING CONCEPT GENERATION, CONCEPT SELECTION, AND PROTOTYPING

2020 ◽  
Vol 1 ◽  
pp. 1505-1514
Author(s):  
H. Nolte ◽  
C. McComb
Keyword(s):  
Design Process ◽  
Perceived Stress ◽  
Physiological Response ◽  
Mental Stress ◽  
Physiological Stress ◽  
Stress Component ◽  
Concept Generation ◽  
Concept Selection ◽  
Engineering Design Process ◽  
Cognitive Experience

AbstractVarious aspects of the design process often lead to stress. This study used pre- and post-task surveys to gather information regarding the designer's cognitive experience, physiological response, and perceived sources of stress during concept generation, concept selection, and prototyping. Results confirmed that design is highly cognitive, and that mental stress is present. Variability in the results also suggests that a physiological stress component might be present. Additionally, perceived sources of stress were examined, and recommendations were offered for instructors of design courses.

scholarly journals The cognitive experience of engineering design: an examination of first-year student stress across principal activities of the engineering design process

2021 ◽  
Vol 7 ◽  
Author(s):  
Hannah Nolte ◽  
Christopher McComb
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Physical Modelling ◽  
Design Activity ◽  
Concept Generation ◽  
Concept Selection ◽  
Student Stress ◽  
Engineering Design Process ◽  
Design Activities ◽  
Cognitive Experience

Abstract The engineering design process can produce stress that endures even after it has been completed. This may be particularly true for students who engage with the process as novices. However, it is not known how individual components of the design process induce stress in designers. This study explored the cognitive experience of introductory engineering design students during concept generation, concept selection and physical modelling to identify stress signatures for these three design activities. Data were collected for the design activities using pre- and post-task surveys. Each design activity produced distinct markers of cognitive experience and a unique stress signature that was stable across design activity themes. Rankings of perceived sources of stress also differed for each design activity. Students, however, did not perceive any physiological changes due to the stress of design for any of the design activities. Findings indicate that physical modelling was the most stressful for students, followed by concept generation and then concept selection. Additionally, recommendations for instructors of introductory engineering design courses were provided to help them apply the results of this study. Better understanding of the cognitive experience of students during design can support instructors as they learn to better teach design.

How Engineering Design Students’ Creative Preferences and Cognitive Styles Impact Their Concept Generation and Screening

2018 ◽  
Author(s):  
Katie Heininger ◽  
Hong-En Chen ◽  
Kathryn Jablokow ◽  
Scarlett R. Miller
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Engineering Students ◽  
Idea Generation ◽  
Risk Tolerance ◽  
Concept Generation ◽  
Undergraduate Engineering ◽  
Engineering Design Process ◽  
Individual Traits ◽  
The Impact

The flow of creative ideas throughout the engineering design process is essential for innovation. However, few studies have examined how individual traits affect problem-solving behaviors in an engineering design setting. Understanding these behaviors will enable us to guide individuals during the idea generation and concept screening phases of the engineering design process and help support the flow of creative ideas through this process. As a first step towards understanding these behaviors, we conducted an exploratory study with 19 undergraduate engineering students to examine the impact of individual traits, using the Preferences for Creativity Scale (PCS) and Kirton’s Adaption-Innovation inventory (KAI), on the creativity of the ideas generated and selected for an engineering design task. The ideas were rated for their creativity, quality, and originality using Amabile’s consensual assessment technique. Our results show that the PCS was able to predict students’ propensity for creative concept screening, accounting for 74% of the variation in the model. Specifically, team centrality and influence and risk tolerance significantly contributed to the model. However, PCS was unable to predict idea generation abilities. On the other hand, cognitive style, as measured by KAI, predicted the generation of creative and original ideas, as well as one’s propensity for quality concept screening, although the effect sizes were small. Our results provide insights into individual factors impacting undergraduate engineering students’ idea generation and selection.

The Preferences for Creativity Scale (PCS): Identifying the Underlying Constructs of Creative Concept Selection

2016 ◽  
Author(s):  
Christine A. Toh ◽  
Scarlett R. Miller
Keyword(s):  
Decision Making ◽  
Factor Analysis ◽  
Engineering Design ◽  
Design Process ◽  
Risk Tolerance ◽  
Future Research ◽  
Concept Selection ◽  
Engineering Design Process ◽  
Confirmatory Factor ◽  
Decision Making Biases

Creativity is highly emphasized during the engineering design process, but prior research has shown that decision-making biases and individual attributes can affect perceptions and preferences for creativity. However, there is a lack of knowledge of how to measure creativity during concept selection, or about the factors that affect designers’ preferences for creative concepts in an engineering design context. As a first step in understanding what factors contribute to the promotion or filtering of creative concepts during concept selection, this study investigates the factors that can affect preferences for creativity through the development of a psychometric survey that assesses student designers’ preferences for creativity through Exploratory Factor Analysis and Confirmatory Factor Analysis. The result of these analyses is the 23-item Preferences for Creativity Scale (PCS) that assesses an individual’s preference for creativity in engineering design on 4 major dimensions: (1) Team Centrality, (2) Risk Tolerance, (3) Creative Confidence/ Preference, and (4) Motivation. The results of these analyses provide a foundation for studying creativity in the design process and allow for future research that investigates the factors that influence creative concept selection in engineering design.

Exploring the Engineering Design Process Through Computer-Aided Design and 3-D Printing

Science Scope ◽  
2017 ◽  
Vol 041 (01) ◽  
Author(s):  
Nicholas Garafolo ◽  
Nidaa Makki ◽  
Katrina Halasa ◽  
Wondimu Ahmed ◽  
Kristin Koskey ◽  
...  
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Computer Aided Design ◽  
Engineering Design Process ◽  
Computer Aided ◽  
Aided Design

scholarly journals Challenging the engineering design process for the development of facial masks in the constraint of the COVID-19 pandemic

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 660-665
Author(s):  
Giovanni Formentini ◽  
Núria Boix Rodríguez ◽  
Claudio Favi ◽  
Marco Marconi
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Engineering Design Process

Using DIME maps and STEM project-based learning to teach physics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael S. Rugh ◽  
Donald J. Beyette ◽  
Mary Margaret Capraro ◽  
Robert M. Capraro
Keyword(s):  
Educational Technology ◽  
High School Students ◽  
Engineering Design ◽  
Design Process ◽  
Teaching Method ◽  
Slow Motion ◽  
Project Based Learning ◽  
School Students ◽  
Content Type ◽  
Engineering Design Process

Purpose The purpose of this study is to examine a week-long science, technology, engineering and mathematics (STEM) project-based learning (PBL) activity that integrates a new educational technology and the engineering design process to teach middle and high school students the concepts involved in rotational physics. The technology and teaching method described in this paper can be applied to a wide variety of STEM content areas. Design/methodology/approach As an educational technology, the dynamic and interactive mathematical expressions (DIME) map system automatically generates an interactive, connected concept map of mathematically based concepts extracted from a portable document format textbook chapter. Over five days, students used DIME maps to engage in meaningful self-guided learning within the engineering design process and STEM PBL. Findings Using DIME maps within a STEM PBL activity, students explored the physics behind spinning objects, proposed multiple creative designs and built a variety of spinners to meet specified criteria and constraints. Practical implications STEM teachers can use DIME maps and STEM PBL to support their students in making connections between what they learn in the classroom and real-world scenarios. Social implications For any classroom with computers, tablets or phones and an internet connection, DIME maps are an accessible educational technology that provides an alternative representation of knowledge for learners who are underserved by traditional methods of instruction. Originality/value For STEM teachers and education researchers, the activity described in this paper uses advances in technology (DIME maps and slow-motion video capture on cell phones) and pedagogy (STEM PBL and the engineering design process) to enable students to engage in meaningful learning.

Categorization of Information Loss During the Dissemination of Design Ideas

2018 ◽  
Author(s):  
Victoria Zhao ◽  
Conrad S. Tucker
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Information Source ◽  
Information Loss ◽  
Design Solution ◽  
Sources Of Information ◽  
Comprehensive Review ◽  
Engineering Design Process ◽  
Design Idea ◽  
Design Ideas

Information is transferred through a process consisting of an information source, a transmitter, a channel, a receiver and its destination. Unfortunately, during different stages of the engineering design process, there is a risk of a design idea or solution being incorrectly interpreted due to the nonlinearity of engineering design. I.e., there are many ways to communicate a single design idea or solution. This paper provides a comprehensive review and categorization of the possible sources of information loss at different stages of the engineering design process. Next, the authors present an approach that seeks to minimize information loss during certain stages of the engineering design process. The paper i) explores design process and dissemination methods in engineering design; ii) reviews prior work pertaining to these stages of the engineering design process and iii) proposes an information entropy metric that designers can utilize in order to quantify information loss at different stages of the engineering design process. Knowledge gained from this work will aid designers in selecting a suitable dissemination solution needed to effectively achieve a design solution.

Sign in / Sign up

Export Citation Format

Share Document