Inspired Internal Search: Using Neuroimaging to Understand Design Ideation and Concept Generation With Inspirational Stimuli

2018 ◽  
Author(s):  
Kosa Goucher-Lambert ◽  
Jarrod Moss ◽  
Jonathan Cagan
Keyword(s):  
Cognitive Processes ◽  
Analogical Reasoning ◽  
Design Research ◽  
Idea Generation ◽  
Brain Activation ◽  
Specific Pattern ◽  
Design Activity ◽  
Concept Generation ◽  
Levels Of Abstraction ◽  
Insight Into

While a large subset of work within the design research community has demonstrated that supportive stimuli (e.g., analogies) are a powerful assistive tool for designers, little is known about the cognitive processes enabling inspiration during design activity. To provide insight into this open question, a functional magnetic resonance imaging (fMRI) experiment was developed to study design concept generation with and without support from inspirational stimuli (N = 21). The stimuli provided in this work were words given at varying levels of abstraction from the design problems and were meant to support cognitive processes similar to analogical reasoning. Results from this work demonstrate that inspirational stimuli of any kind (near or far from the problem space) improve the fluency of idea generation and illustrate the moments during ideation that such stimuli can be used as a supportive tool. Furthermore, neuroimaging data help to uncover distinct brain activation networks based upon reasoning with and without inspirational stimuli. We find that the successful application of inspirational stimuli during concept generation leads to a specific pattern of brain activation, which we term “inspired internal search.” Prior work by the authors has demonstrated an impasse-based activation network that is more prevalent in the absence of inspirational stimuli. Together, these brain activation networks provide insight into the differences between ideating with and without inspirational stimuli. Moreover these networks lend new meaning to what happens when a presented stimuli is too far from the design problem being solved.

Confirmation and Cognitive Bias in Design Cognition

2012 ◽  
Author(s):  
Gregory M. Hallihan ◽  
Hyunmin Cheong ◽  
L. H. Shu
Keyword(s):  
Information Processing ◽  
Analogical Reasoning ◽  
Design Research ◽  
Cognitive Biases ◽  
Confirmation Bias ◽  
Psychological Research ◽  
Human Information Processing ◽  
Concept Generation ◽  
Design Cognition ◽  
Concept Evaluation

The desire to better understand design cognition has led to the application of literature from psychology to design research, e.g., in learning, analogical reasoning, and problem solving. Psychological research on cognitive heuristics and biases offers another relevant body of knowledge for application. Cognitive biases are inherent biases in human information processing, which can lead to suboptimal reasoning. Cognitive heuristics are unconscious rules utilized to enhance the efficiency of information processing and are possible antecedents of cognitive biases. This paper presents two studies that examined the role of confirmation bias, which is a tendency to seek and interpret evidence in order to confirm existing beliefs. The results of the first study, a protocol analysis involving novice designers engaged in a biomimetic design task, indicate that confirmation bias is present during concept generation and offer additional insights into the influence of confirmation bias in design. The results of the second study, a controlled experiment requiring participants to complete a concept evaluation task, suggest that decision matrices are effective tools to reduce confirmation bias during concept evaluation.

scholarly journals To sext or not to sext. The role of social-cognitive processes in the decision to engage in sexting

2021 ◽  
Vol 38 (4) ◽  
pp. 1410-1429
Author(s):  
Claire Wilson ◽  
Tommy van Steen ◽  
Christabel Akinyode ◽  
Zara P. Brodie ◽  
Graham G. Scott
Keyword(s):  
Cognitive Processes ◽  
Self Efficacy ◽  
Social Cognitive ◽  
Cognitive Factors ◽  
Relationship Status ◽  
Injunctive Norm ◽  
The Social ◽  
And Behavior ◽  
Insight Into

Technology has given rise to online behaviors such as sexting. It is important that we examine predictors of such behavior in order to understand who is more likely to sext and thus inform intervention aimed at sexting awareness. We used the Theory of Planned Behavior (TPB) to examine sexting beliefs and behavior. Participants (n = 418; 70.3% women) completed questionnaires assessing attitudes (instrumental and affective), subjective norms (injunctive and descriptive), control perceptions (self-efficacy and controllability) and intentions toward sexting. Specific sexting beliefs (fun/carefree beliefs, perceived risks and relational expectations) were also measured and sexting behavior reported. Relationship status, instrumental attitude, injunctive norm, descriptive norm and self-efficacy were associated with sexting intentions. Relationship status, intentions and self-efficacy related to sexting behavior. Results provide insight into the social-cognitive factors related to individuals’ sexting behavior and bring us closer to understanding what beliefs predict the behavior.

scholarly journals Establishing Analogy Categories for Bio-Inspired Design

Designs ◽  
2018 ◽  
Vol 2 (4) ◽  
pp. 47 ◽  
Author(s):  
Jacquelyn Nagel ◽  
Linda Schmidt ◽  
Werner Born
Keyword(s):  
Analogical Reasoning ◽  
Design Research ◽  
Design Method ◽  
Biological Systems ◽  
Design Pedagogy ◽  
Biological Inspiration ◽  
Research And Teaching ◽  
Difficult Time ◽  
Behavior Learning ◽  
The Common

Biological systems have evolved over billions of years and cope with changing conditions through the adaptation of morphology, physiology, or behavior. Learning from these adaptations can inspire engineering innovation. Several bio-inspired design tools and methods prescribe the use of analogies, but lack details for the identification and application of promising analogies. Further, inexperienced designers tend to have a more difficult time recognizing or creating analogies from biological systems. This paper reviews biomimicry literature to establish analogy categories as a tool for knowledge transfer between biology and engineering to aid bio-inspired design that addresses the common issues. Two studies were performed with the analogy categories. A study of commercialized products verifies the set of categories, while a controlled design study demonstrates the utility of the categories. The results of both studies offer valuable information and insights into the complexity of analogical reasoning and transfer, as well as what leads to biological inspiration versus imitation. The influence on bio-inspired design pedagogy is also discussed. The breadth of the analogy categories is sufficient to capture the knowledge transferred from biology to engineering for bio-inspired design. The analogy categories are a design method independent tool and are applicable for professional product design, research, and teaching purposes.

scholarly journals An earlier role for intent in children’s partner choice versus punishment

2020 ◽  
Author(s):  
Justin Martin ◽  
Kyleigh Leddy ◽  
Liane Young ◽  
Katherine McAuliffe
Keyword(s):  
Young Children ◽  
Moral Judgment ◽  
Cognitive Processes ◽  
Developmental Trajectories ◽  
Partner Choice ◽  
Moral Judgments ◽  
Equal Weight ◽  
Behavioral Differences ◽  
The Many ◽  
Insight Into

Among the many factors that influence our moral judgments, two are especially important: whether the person caused a bad outcome and whether they intended for it to happen. Notably, the weight accorded to these factors in adulthood varies by the type of judgment being made. For punishment decisions, intentions and outcomes carry relatively equal weight; for partner choice decisions (i.e., deciding whether or not to interact with someone again), intentions are weighted much more heavily. These behavioral differences in punishment and partner choice judgments may also reflect more fundamental differences in the cognitive processes supporting these decisions. Exploring how punishment and partner choice emerge in development provides important and unique insight into these processes as they emerge and mature. Here, we explore the developmental emergence of punishment and partner choice decisions in 4- to 9-year-old children. Given the importance of intentions for partner choice decisions¬–from both theoretical and empirical perspectives–we targeted the sensitivity of these two responses to others’ intentions as well as outcomes caused. Our punishment results replicate past work: young children are more focused on outcomes caused and become increasingly sensitive to intentions with age. In contrast, partner choice judgments exhibit sensitivity to intentions at an earlier age than punishment judgments, manifesting as earlier partner choice in cases of attempted violations. These results reveal distinct developmental trajectories for punishment and partner choice judgments, with implications for our understanding of the processes underlying these two responses as well as the development of moral judgment more broadly.

scholarly journals Creating Something Different: Similarity, Contrast, and Representativeness in Categorization

2019 ◽  
Author(s):  
Joseph L. Austerweil ◽  
Shi Xian Liew ◽  
Nolan Bradley Conaway ◽  
Kenneth J. Kurtz
Keyword(s):  
Cognitive Processes ◽  
Category Learning ◽  
Human Cognition ◽  
Fundamental Importance ◽  
Concept Generation ◽  
Statistical Structure ◽  
Representativeness Heuristic ◽  
New Concepts ◽  
Novel Approaches ◽  
Computational Analyses

The ability to generate new concepts and ideas is among the most fascinating aspects of human cognition, but we do not have a strong understanding of the cognitive processes and representations underlying concept generation. In this paper, we study the generation of new categories using the computational and behavioral toolkit of traditional artificial category learning. Previous work in this domain has focused on how the statistical structure of known categories generalizes to generated categories, overlooking whether (and if so, how) contrast between the known and generated categories is a factor. We report three experiments demonstrating that contrast between what is known and what is created is of fundamental importance for categorization. We propose two novel approaches to modeling category contrast: one focused on exemplar dissimilarity and another on the representativeness heuristic. Our experiments and computational analyses demonstrate that both models capture different aspects of contrast’s role in categorization.

Validation of Function Pruning Rules Through Similarity at Three Levels of Abstraction

2012 ◽  
Vol 134 (4) ◽  
Author(s):  
Benjamin W. Caldwell ◽  
Gregory M. Mocko
Keyword(s):  
Conceptual Design ◽  
Clustering Algorithm ◽  
Controlled Vocabulary ◽  
Design Activity ◽  
Conceptual Level ◽  
Levels Of Abstraction ◽  
Similarity Metric ◽  
Level Of Abstraction ◽  
Design By Analogy ◽  
Function Models

Function modeling is often used in the conceptual design phase as an approach to capture a form-independent purpose of a product. Previous research uses a repository of reverse-engineered function models to support conceptual-based design tools, such as similarity and design-by-analogy. These models, however, are created at a different level of abstraction than models created in conceptual design for new products. In this paper, a set of pruning rules is developed to generate an abstract, conceptual-level model from a reverse-engineered function model. The conceptual-level models are compared to two additional levels of abstraction that are available in a design repository. The abstract models developed through the pruning rules are tested using a similarity metric to understand their usefulness in conceptual design. The similarity of 128 products is computed using the Functional Basis controlled vocabulary and a matrix-based similarity metric at each level of abstraction. A matrix-based clustering algorithm is then applied to the similarity results to identify groups of similar products. A subset of these products is studied to further compare the three levels of abstraction and to validate the pruning rules. It is shown that the pruning rules are able to convert reverse-engineered function models to conceptual-level models, better supporting design-by-analogy, a conceptual-stage design activity.

UNDERSTANDING BLOGGERS POSTING ABOUT POP CULTURE: LINGUAPRAGMATICS OF «UNPOPULAR OPINION» IN THE ENGLISH INTERNET-DISCOURSE

2021 ◽  
Author(s):  
A.V. Kukovskaya
Keyword(s):  
Discourse Analysis ◽  
Cognitive Processes ◽  
Pop Culture ◽  
Computer Mediated ◽  
The Subject ◽  
The Given ◽  
Insight Into ◽  
Blog Posts ◽  
Subcultural Community

The paper explores communication within the English blogosphere in which the discourse manifests itself in blog posts, devoted, in particular, to reactions to a variety of pop-culture works. These posts are characterized by specific linguapragmatics. The article examines the language and the discourse of bloggers from the standpoint of the Linguistic Creativity approach, which may help to have an in-depth insight into the mechanisms of cognitive processes. The topicality of this topic is justified by the interest that modern linguists have in text studies, discourse analysis and computer-mediated Internet-discourse. The novelty of the article lies in the fact that the given discourse and the linguapragmatics of the posts in question in the English blogosphere have not so far received the attention they deserve and should be the subject of more research and analysis. The paper supplies relevant conclusions made on the basis of the empiric material. The research demonstrates that within the English Internet-discourse of bloggers, who interpret modern pop culture and can be considered a subcultural community, among other types of posts there can be singled out the so-called “unpopular opinion”, that boasts a number of linguapragmatic peculiarities coinciding with the communicative goals of bloggers. Decoding such posts may be a challenge and we, among other things, want to draw researchers’ attention to the “language of bloggers” and its study.

Neuromarketing and the Potential Application of Scientific Methods in Measuring Consumer Behaviour

2018 ◽  
pp. 317-336
Author(s):  
Cynthia A. Bulley ◽  
Veronica Adu-Brobbey ◽  
Esther O. Duodu
Keyword(s):  
Developing Country ◽  
Potential Application ◽  
Consumer Behaviour ◽  
Marketing Research ◽  
Brain Activation ◽  
Research Data ◽  
Research Tool ◽  
Field Of Study ◽  
Scientific Methods ◽  
Insight Into

Consumer behaviour studies have taken a new turn. Marketers, economists and other consumer related disciplines are looking to science to accurately determine consumer behaviour. The purpose of this chapter is to provide insight into a burgeoning field of study, neuromarketing, documenting various research studies and applications of mechanisms in determining brain activities and other uses of science to benefit marketing research. Data for the study is derived from impartial cross-referencing of conceptual and empirical articles published in major journals. The application of neuroimaging technique in research have provided marketers with concrete evidence of brain activation that signal increased activities during stimulation (Lewis & Bridger, 2005; Rossiter et al., 2001). Further, the implication and causes of concern in using neuroscience methods in marketing are highlighted. Developing country studies on neuromarketing are examined to determine its application and use as a marketing research tool.

Concept Generation Algorithms for Repository-Based Early Design

2006 ◽  
Author(s):  
Jayson Vucovich ◽  
Nikhil Bhardwaj ◽  
Hoi-Hei (Terence) Ho ◽  
Manjeshwar Ramakrishna ◽  
Mayur Thakur ◽  
...  
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Design Research ◽  
Hidden Markov ◽  
Functional Model ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Design Knowledge ◽  
Concept Generation ◽  
Failure Data

Modern product and engineering design research explores methods for formally generating design concepts from stored knowledge. We discuss a design methodology which utilizes archived design knowledge gained from product dissection to aid novice designers in developing new product designs. In this design paradigm, new designs are developed as a model of the product’s intended functionality, rather than a model of actual, physical components. This paper formulates an algorithm to automatically generate a set of components to instantiate such a functional model using archived design knowledge, which maps components to the functions they can satisfy and provides precedents for which components can be connected. In order to avoid generating an exponential number of instantiations, component failure data is leveraged to develop a dynamic programming algorithm. In addition, a method which uses this information to train a Hidden Markov Model is also developed. This Hidden Markov Model is consulted to generate a set of instantiations with low failure rates while avoiding exponential runtime.

A Validation Regarding Effectiveness of Scenario Graph

2011 ◽  
Author(s):  
Hiroyuki Yagita ◽  
Akira Tose ◽  
Madoka Nakajima ◽  
Sun K. Kim ◽  
Takashi Maeno
Keyword(s):  
Contextual Information ◽  
Idea Generation ◽  
Test Group ◽  
Problem Formulation ◽  
Service Development ◽  
Control Group ◽  
Design Teams ◽  
Concept Generation ◽  
Significant Difference

Scenario Graph is a structured mind mapping methodology that aids design teams to generate potential scenarios for new products and services while visually organizing contextual information. Since its introduction in industry and academia, the Scenario Graph has helped design teams to capture new values and behaviors of potential customers during the problem formulation stage. At the same time, the Scenario Graph, sharing a common challenge with various design methods, has faced difficulty regarding validation of its effectiveness as a design method. This paper describes a validation framework for a method in problem formulation stages and an experiment, which compare ideation results of 87 people — 43 people with the Scenario Graph method (as a test group) and 44 people with the Brainstorming (as a control group) — to solve an identical problem. While the results show no statistically significant difference in the number of ideas generated, the data reveals statistically significant differences in the quality of ideas. The test group, which used the Scenario Graph, yielded ideas that were more novel, feasible, and abstract than the control group, which used the Brainstorming, did. These metrics represent a way to measure the quality of ideas in the domain of engineering design. Our experiment confirms the hypotheses that the Scenario Graph is effective in improving the performance of idea generation sessions, which is consistent with qualitative evaluations. The lessons, gained from this experiment, provide an insight on how this method can be effectively used during the early stages of concept generation of a company’s process for product and/or service development.

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