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Über dieses Buch

This book gathers the peer-reviewed and revised versions of papers from the Seventh International Conference on Design Computing and Cognition (DCC'16), held at Northwestern University, Evanston (Chicago), USA, from 27–29 June 2016. The material presented here reflects cutting-edge design research with a focus on artificial intelligence, cognitive science and computational theories.

The papers are grouped under the following nine headings, describing advances in theory and applications alike and demonstrating the depth and breadth of design computing and design cognition: Design Creativity; Design Cognition - Design Approaches; Design Support; Design Grammars; Design Cognition - Design Behaviors; Design Processes; Design Synthesis; Design Activity and Design Knowledge.

The book will be of particular interest to researchers, developers and users of advanced computation in design across all disciplines, and to all readers who need to gain a better understanding of designing.



Design Synthesis


Reducing Information to Stimulate Design Imagination

This paper describes an experiment that is part of a larger research project that compares the visual reasoning between groups of designers and non-designers. In particular, this experiment focuses on how designers’ processes of reasoning is characterized when they are given different levels of reduced information of an object in comparison to a group of non-designers. The experiment used deconstructed and scaled-down components of Gerrit Riedveld’s iconic Red and Blue Chair. Three groups were given 3 different levels of information—group 1 were given components painted the same color as the original chair, group 2 were given components painted in a single (white) color, and group 3 were given unpainted (natural) components. The results suggest that the 3 levels of reduced information impacted on the designers’ reasoning processes and there were clear differences in the visual reasoning processes between design and non-design participants.

Shiro Inoue, Paul A. Rodgers, Andy Tennant, Nick Spencer

Novelty, Conventionality, and Value of Invention

Recent research has suggested that conventionality, in addition to novelty, creates value for invention. A balance between the novelty and conventionality of an invention may determine its eventual value, but is rarely understood. In this study, we use patents to approximate technological inventions, and measure the novelty, conventionality, and value of invention using patent reference and citation data from USPTO. Our empirical analyses of the patents in the 1990s reveal that medium conventionality and high novelty lead to high invention value. When conventionality is low or medium, increasing it may amplify the contribution of novelty to the value of invention. When conventionality is too high, invention value is generally low regardless of novelty. These findings provide implications and guidance to designers for enhancing the value of their potential inventions.

Yuejun He, Jianxi Luo

Characterizing Tangible Interaction During a Creative Combination Task

Tangible user interfaces change the way we interact with digital information, with physical affordances that are distinctly different from pointing and keyboard/mouse interaction. As a precursor to studying the impact of tangible interfaces on design cognition, this paper presents a coding scheme for measuring the difference between two types of user interfaces: tangible and pointing. We perform a case study, using data collected from an experiment in which participants are asked to make word combinations from a set of six nouns and give them meaning. The task is presented as a design task with references to function, behavior, and structure of the word combination meanings. The case study shows large differences in gesture and action between the two conditions. We conclude with hypotheses on how interaction modalities that afford more body movement may have an impact on creativity and design cognition.

Mary Lou Maher, Lina Lee, John S. Gero, Rongrong Yu, Timothy Clausner

Dissecting Creativity: How Dissection Virtuality, Analogical Distance, and Product Complexity Impact Creativity and Self-Efficacy

Product dissection has been adopted in engineering education as a means to benchmark existing products and inspire new design ideas. Despite widespread adoption of dissection practices, however, little is known about the effectiveness of the widely varying approaches of dissection for encouraging creativity. Therefore, the purpose of this study was to identify the impact of dissection virtuality, analogical distance, and product complexity on creativity and self-efficacy through a factorial experiment with 30 engineering students. The results show that virtual dissection can be used to increase student creativity over physical dissection but this increase is moderated by the complexity and analogical distance of the product being dissected. CSE was not significantly impacted in the study. These results are used to derive implications for dissection practices in engineering education and drive future research that explores the multifaceted role of analogical distance in example-based design practices.

E. M. Starkey, A. S. McKay, S. T. Hunter, S. R. Miller

Design Cognition—Design Approaches


What Can We Learn from Autistic People About Cognitive Abilities Essential to Design? An Exploratory Study

This paper proposes to contribute to our understanding of the fundamental cognitive processes essential to design by exploring the experiences of people who have different information processing behaviors to those found in most people. In particular, we focus on people with autism spectrum conditions (ASC), because they are known to have information processing behaviors that are both maladaptive and exceptional. Central to our exploratory study is the question: what can we learn from people with ASC about cognitive processes essential to design? The scholarship on cognitive behaviors associated with the autism spectrum and narratives on the experiences with design of individuals with ASC are discussed in relation cognitive processes associated with design. We conclude that the weak central coherence theory of autism provides a useful prediction of the cognitive processes necessary for expertise in design practice.

Andy Dong, Ann Heylighen

Solution-Oriented Versus Novelty-Oriented Leadership Instructions: Cognitive Effect on Creative Ideation

The generation of novel ideas is critical to any innovative endeavor. However, one of the key obstacles to creativity is known as the fixation effect, which is the cognitive effect that constrains the generation of novel ideas due to the spontaneous activation of existing knowledge and solutions in individuals’ mind. Expert leaders have been considered to play an important role in overcoming these biases using diverse tools. One of these principal instruments is task instruction. Our hypothesis is that leaders’ instructions can have significant effects on followers’ ideation capacity . We investigated the effect of an instruction given by a leader to his team to generate as many original ideas to a particular creative task, either using solution or novelty-oriented approaches. Results confirmed that solution-oriented instructions activated knowledge bases in fixation, while solution-oriented instructions inhibited these knowledge bases. These results give us new sights into novel models of “less-expert” creative leadership.

Hicham Ezzat, Marine Agogué, Pascal Le Masson, Benoit Weil

A Protocol Study of Cognitive Chunking in Free-Hand Sketching During Design Ideation by Novice Designers

This paper reports a human-subject protocol study aimed to study (1) cognitive chunking during free-hand sketching of design ideas in engineering and (2) correlation between chunks and the functions of the design perceived by the designer. Voluntary participants are presented with a previously unfamiliar design problem and asked to (1) identify the intended functionality of the solution, (2) draw concept sketches of the solution structure, and (3) label the sketches. The data is captured by a smart pen: a computerized pen that records pen strokes and surrounding audio in sync . Time study of these pen strokes and naming of components reveal clear evidence of temporal clustering of pen strokes during the first two tasks, indicating that the physical structure of the design solution is perceived by the designer in small chunks, rather than in continuous streams. Further data suggest that the chunks formed during ideation are based on functional needs perceived by the designer.

Omar M. Galil, Kirill Martusevich, Chiradeep Sen

A Systematic Review of Protocol Studies on Conceptual Design Cognition

This paper reports the first systematic review and synthesis of protocol studies on conceptual design cognition. 47 studies from the domains of architectural design, engineering design, and product design engineering were reviewed towards answering the following question: What is our current understanding of the cognitive processes involved in conceptual design tasks carried out by individual designers? Studies were found to reflect three viewpoints on the cognitive nature of designing: design as search; design as exploration; and design activities. Synthesising the findings of individual studies revealed ten categories of executive and non-executive function studied across the viewpoints: visual perception; mental imagery; semantic association; long term memory; working memory; selective attention; creative thinking; evaluation and decision making; externalisation; and reasoning and problem solving. The review highlights several avenues for future research, centering on the need for general formalisms, more objective methods to supplement protocol analysis, and a shared ontology of cognitive processes.

Laura Hay, Chris McTeague, Alex H. B. Duffy, Laura M. Pidgeon, Tijana Vuletic, Madeleine Grealy

Design Support


Is Biologically Inspired Design Domain Independent?

Current theories of biologically inspired design assume that the design processes are domain independent. But is this assumption true? Design Study Library (DSL) is a digital library of eighty-three cases of biologically inspired design collected from a senior-level interdisciplinary class at Georgia Tech over 2006–2013. We describe a preliminary analysis of the DSL case studies. We posit that the assumption about the domain independence is questionable. In particular, some of the parameters in the domains of physiology and sensing appear to be different from the more common domains of mechanics and materials.

Ashok K. Goel, Christian Tuchez, William Hancock, Keith Frazer

A Meta-Analytic Approach for Uncovering Neural Activation Patterns of Sustainable Product Preference Decisions

This paper explores the use of neuroimaging data to inform results from a preference decision study involving product sustainability. Neurosynth, a meta-analytic database of functional magnetic resonance imaging (fMRI) studies, was used to extract regions of interest (ROIs) for cross comparison with an empirically collected fMRI dataset. The tasks for the empirically collected fMRI dataset were product preference decisions involving sustainability. In particular, participants were engaged in preference judgments separated into two conditions; one with and one without calculated environmental impact values displayed alongside each design alternative. Extracted meta-analytic ROIs were generated based upon keywords (moral, emotion, etc.) from hypotheses on the ways individuals formulate opinions regarding the environment. Furthermore, additional keywords were seeded based on the results of a whole-brain fMRI analysis. Results indicate the important role of moral reasoning and theory of mind processing in product evaluations within social choice domains, such as sustainability.

Kosa Goucher-Lambert, Jarrod Moss, Jonathan Cagan

Second Guessing: Designer Classification of Problem Definition Fragments

Engineering designers progressively develop their own understanding of ill-defined problems through a process of abstraction, decomposition, completion, enhancement, classification and conflict resolution. We have developed a computational aid to support problem formulation in which designers input problem definition fragments into different categories as free form text. We used natural language processing to determine if designers had misplaced problem fragments in inappropriate categories. In this paper, we present our work on how this problem can be addressed by looking for keywords in design descriptions and extracting knowledge from text ontologies using these keywords. We collected data from a group of students who used the Problem Formulator testbed to express their understanding of the given design problem. For each of the six categories in the Problem Formulator ontology, we identified classes using existing ontologies and tools that closely define them. In our method, we first parsed the user inputs to extract the keywords depending on the category in which they were entered. We then associated these keywords to the previously identified classes and categorized them into the correct category.

Meghna Polimera, Mahmoud Dinar, Jami Shah

The Analysis and Presentation of Patents to Support Engineering Design

This paper explores the role of patents in engineering design, and how the extraction and presentation of patent data could be improved for designers. We propose the use of crowdsourcing as a means to post tasks online for a crowd of people to participate and complete. The issues of assessment, searching, clustering and knowledge transfer are evaluated with respect to the literature. Opportunities for potential crowd intervention are then discussed, before the presentation of two initial studies. These related to the categorization and interpretation of patents respectively using an online platform. The initial results establish basic crowd capabilities in understanding patent text and interpreting patent drawings. This has shown that reasonable results can be achieved if tasks of appropriate duration and complexity are set, and if test questions are incorporated to ensure a basic level of understanding exists in the workers.

Gokula Vasantha, Jonathan Corney, Ross Maclachlan, Andrew Wodehouse

Design Grammars


Classifications of Shape Grammars

Since shape grammars were first described about forty five years ago, several types of grammars have emerged. The goal of this paper is to provide a framework that gathers together the main existing types of grammars. The categorization is preceded by a glossary of 19 terms related to shape grammars. Then, 44 types are placed into 13 chronologically-ordered categories. Each type is characterized with its name, a short description, the reference to the original paper, three examples of existing grammars of the type, and simple illustrative grammars. The types are organized using a classification guide in the form of a checklist, which is filled according to an existing shape grammar as an example.

Sara Garcia

From Shape Computations to Shape Decompositions

This is a third paper in a series on shape decompositions, which are seen here as a means to grasp computations with shapes. That is, decompositions that arise in computations with shapes and may serve to explain them are investigated. Due to certain isomorphisms, computations with discrete and topological decompositions are carried out in parallel with shape computations thus providing insights into the latter. In particular, discrete decompositions grasp the transition of intuitive spatial computations envisioned by the designers into symbolic ones that could be carried out by a computer. Some counting has been done showing that even simple spatial computations require a great many symbols in order to be turned into the symbolic ones. It is interesting to explore the converse: turning complex symbolic computations with vast numbers of symbols into the simpler spatial ones with shapes. This may prove promising in tackling big data problems.

Djordje Krstic

Automated Induction of General Grammars for Design

Grammars are useful for representing systems of design patterns, however formulating good grammars is not straightforward in many contexts due to challenges of representation and scope. This challenge has been identified as one of the 3 goals for computerized use of shape grammars: grammar inference. This work introduces a highly flexible mechanism for inducing viable general grammars from a computational representation of a designed context. This mechanism is evaluated with several common types of devised media of increasing complexity based on dimensionality: 1D (e.g., text), 2D (e.g., PCB layout, building plans), many dimensional (which in abstract can generally be used to represent product, system, platform or service designs), and, against a set of grammar properties necessary for a grammar acquisition method to be useful: accuracy, variability, repeatability and conciseness. This work shows complete enumeration over possible grammars in the 1D case and a continuum of approaches for higher dimension data sets that are demonstrative of grammars in design .

Mark Whiting, Jonathan Cagan, Philip LeDuc

Generative Shape Design Using 3D Spatial Grammars, Simulation and Optimization

Advancements in 3D printers are challenging engineers to design ever more complex, customizable and unique products. This paper presents a method that facilitates design by combining 3D spatial grammars, structural simulation and optimization. The proposed method is generic and illustrated here through the design of wheels for inline skates since they have both aesthetic and functional requirements. A new spatial grammar for wheel spoke design is described that integrates constraints from additive manufacture such that the wheels can be directly fabricated. Next, the necessary adjustments to enable automated FE simulation with invariant boundary conditions are shown. The design selection process during generation is driven by simulated annealing optimization and a spatial grammar specific neighborhood definition is introduced for shape modification. Results presented for the case of the inline skate wheel show promise both in automatically generating many different yet valid concepts and in obtaining a structurally optimized design .

Luca Zimmermann, Tian Chen, Kristina Shea

Design Cognition—Design Behaviors


Comparing Two Approaches to Studying Communications in Team Design

This paper explores intragroup communication in team design using data collected from a protocol study. Two units of analysis are introduced, (1) at a coarse level: turn-taking of utterances during conversations, and (2) at a fine level: design issues on the basis of the FBS ontologically-based coding scheme. These basic elements of team design activities (i.e., conversational turns and design issues) are then interconnected using Goldschmidt’s Linkography method. The proposed two methods are demonstrated and compared through a case study of product design meeting. Results indicate that, for the purpose of structure-based analysis, the measurements derived from the turn-taking model are able to largely resemble the measurements derived from the FBS-based model, though the former model could be achieved with much less labor than the latter model. However, content-based analysis could only be conducted by using the more sophisticated FBS-based method.

Hao Jiang, John S. Gero

Individual Differences in Tendency for Design Fixation

Not all individuals may be equally susceptible to design fixation. We sought to identify characteristics that could predict individual tendency for design fixation, and explored the use of Kruglanski’s Need for Closure Scale for this purpose. We devised an experiment to determine whether correlations exist between participants’ score on this scale and the degree of fixation in concepts elicited. Specifically, engineering-student participants were asked to complete the Need for Closure Scale as well as develop concepts for which an example solution was provided. Two statistical techniques, the Mann-Whitney U test and ordinal logistic regression, showed that participants’ Need for Closure scores correlated significantly with degree of fixation in generated concepts.

Song Liang Lai, L. H. Shu

Functional Thinking: A Protocol Study to Map Modeling Behavior of Designers

Function modeling is a tool used to map functional requirements of a design problem to the solution space. Research has been done on various representations and uses of function modeling, however, there is a lack of research on how designers think about function modeling. This paper presents a protocol study which was used to analyze modeling behaviors and further the understanding of how designers create function models and subsequently understand how designers cognitively process function models. The experimental setup used for the study, the data collection, and the analysis of participant generated models are provided in this paper. Preliminary results suggest that designers mostly use forward chaining when modeling function structures, with some nucleation and almost no backward chaining. Moving forward, this study will be expanded to include a larger participant pool in order to provide substantial evidence for the conclusions. Additionally, other patterns that exist in designer activity will be explored and investigated from a cognitive perspective.

Ashwinraj Thiagarajan, Apurva Patel, Steven O’Shields, Joshua D. Summers

To Copy or Not to Copy: The Influence of Instructions in Design Fixation Experiments

Design fixation experiments often require participants to solve a design problem whilst being exposed to an example solution and instructions for how to treat that example. However, little is known about the influence of such instructions, leading to difficulties in interpreting results and understanding how the introduction of examples affects idea generation. In our experiment, participants were all provided with the same design problem and example solution, but were presented with different instructions, ranging from strongly encouraging copying the example to strongly discouraging copying. Analyses of participants’ work indicated that only the instructions encouraging copying had an effect. When encouraged to copy, participants tended to only copy the structural features of the example rather than the underlying concept. By contrast, the number of features copied was not reduced when participants were discouraged from copying. These findings suggest that there are subtle interactions between instructions and stimuli that influence design fixation.

Luis A. Vasconcelos, Chih-Chun Chen, Eloise Taysom, Nathan Crilly

Design Processes


A Self-Organizing Map Based Approach to Adaptive System Formation

Multi-agent systems are considered to be potential solutions to complex tasks. Cellular self-organizing (CSO) multi-agent systems have been proposed that take a field-based approach to regulate agent behaviors. One difficulty in designing CSO systems is to generate rules to map given tasks to agent behaviors. This paper proposes an approach for adaptive system formation based on a field analysis and self-organizing map (SOM) algorithm. The tasks are captured as multiple task fields. The relationship among the agents is translated into a social field. Each agent has multiple function modes corresponding to the task fields. SOM and a function mode selection algorithm are devised to match the social field of the system with the task fields. Computer simulations have demonstrated the effectiveness of this approach and its potential in designing CSO systems for solving system formation tasks.

Dizhou Lu, Yan Jin

Utilizing Markov Chains to Understand Operation Sequencing in Design Tasks

Design often involves searching for a final design solution by iteratively modifying and adjusting a current design. Through this process designers are able to improve the quality of the current design and also learn what patterns of operations are most likely to lead to the quickest future improvements. Prior work in psychology has shown that humans can be adept at learning how to apply short sequences of operations for maximum effect while solving a problem. This work explores the sequencing of operations specifically within the domain of engineering design by examining the results of a human study in which participants designed trusses. A statistical analysis of the data from that study uses Markov Chains to show with high confidence that meaningful operation sequences exist. This work also uses an agent-based modeling framework in conjunction with Markov Chain concepts to simulate the performance of teams with and without the ability to learn sequences. These computational studies offer confirmation for the conclusion that sequence-learning abilities are helpful during design.

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

Designerly Pick and Place: Coding Physical Model Making to Inform Material-Based Robotic Interaction

To study how designers explore ideas when making physical models we ran an experiment in which architects and undergraduate students constructed a dream house made of blocks. We coded their interactions in terms of robotic pick and place actions: adding, subtracting, modifying and relocating blocks. Architects differed from students along three dimensions. First, architects were more controlled with the blocks; they used fewer blocks overall and fewer variations. Second, architects appear to think less about house features and more about spatial relationships and material constraints. Lastly, architects experiment with multiple block positions within the model more frequently, repeatedly testing block placements. Together these findings suggest that architects physically explore the design space more effectively than students by exploiting material interactions. This embodied know-how is something next generation robots will need to support. Implications for material-based robotic interaction are discussed.

Daniel Smithwick, David Kirsh, Larry Sass

Knowledge Distribution and the Effect of Design Tools on the Design Process

This paper compares the cognitive performance of architecture students when designing tasks using one of the three design tools: pencil and paper, software Sketch Up and Rhinoceros 3D. It questions if a design tool can affect when knowledge is generated and used in the duration of design activity. This is explored through a protocol ‘think aloud’ study for which a new coding scheme was developed. The methodology is grounded on the theory of Distributed Cognition and Zhang and Norman’s (Cognit Sci 18(1):87–122, 1994) method of ‘representational analysis’, based on which, knowledge is either ‘internal’ in that it is actively memorized by the designer or is ‘external’ in that it is implicitly made available via a stimuli like a design tool. Using an Analysis of Variance (ANOVA) test, for the five participants of this study, external knowledge generated significantly earlier on within the process when using Sketch Up compared to the other two tools.

Mina Tahsiri, Jonathan Hale, Chantelle Niblock

Design Synthesis


A Heuristic Approach for the Automated Generation of Furniture Layout Schemes in Residential Spaces

A variety of heuristic methods and algorithms have been developed for space layout planning problems. Recent efforts to generate furniture layout schemes in existing spatial configurations have mostly relied on exhaustive search and are likely to produce dysfunctional or counter-intuitive solutions. In this paper, we propose a heuristic approach for the automated generation of furniture layout schemes, with specific focus on residential spaces. First, we present an operational definition for furniture entities, space configurations, and space entities. Then we introduce a heuristic algorithm for generating furniture layout schemes based on a set of space subdivision rules, object-object relations, and object-space relations. Using Grasshopper, we generate a group of possible schemes for a sample residential living space. A discussion follows, outlining current limitations, expanding the context of the study, and possibilities for development.

Sherif Abdelmohsen, Ayman Assem, Sherif Tarabishy, Ahmed Ibrahim

3DJ: An Analytical and Generative Design System for Synthesizing High-Performance Textures from 3D Scans

This paper presents “3D Sampling” as a new creative design process. Analogous to sample-based music, 3D Sampling provides conceptual and technical tools for hacking, mixing, and re-appropriating the material behavior, performance features, and structures of real world objects. Building on previous research, this paper demonstrates a new 3D Sampling design system—“3DJ”. 3DJ implements user-guidance features within an evolutionary design process to synthesize new texture designs from 3D scans. A case study demonstrates the use of 3DJ to generate novel designs for a site-specific architectural canopy from 3D scanned textures.

Sayjel V. Patel, Mark K. M. Tam, Caitlin T. Mueller

Automated Best Connected Rectangular Floorplans

As part of a larger research aimed at developing design aids for architects, this paper presents the “automated” generation of the “best connected” rectangular floor plans, satisfying given topological and dimensional constraints. It has been seen that architects, knowingly or unknowingly, have often used either the golden rectangle or the Fibonacci rectangle in their works throughout history. But it was hard to find any specific reason for such use, other than aesthetic. In 2015, Shekhawat showed that they are among the best connected rectangular arrangements (dimensionless rectangular floor plans) and that this may well be another reason for their frequent use in architectural design. In this work, an alternative algorithm is presented which generates n − 3 best connected rectangular arrangements, being n the number of rooms. Then, this concept is further extended for constructing the best connected dimensioned rectangular floor plans. The goal is to provide an optimal solution for the rectangular space allocation problem, while satisfying given topological and dimensional requirements.

Krishnendra Shekhawat, José P. Duarte

Individual Coffee Maker Design Using Graph-Based Design Languages

Graph-based design languages are used in this work to implement individualized mass customization. Using coffee machines as examples, the individualization of the product architecture and geometry is demonstrated. Combined with a user interface, a “coffee maker language” is shown to automate the design process including topological and parametric product variations by user inputs. The automatically generated processing result is an “individualized” creation of a digital coffee maker design which satisfies all implemented geometrical, physical and functional constraints.

Claudia Tonhäuser, Stephan Rudolph

Design Activity


Translating Analytical Descriptions of Cities into Planning and Simulation Models

With the increase in urban complexity, plausible analytical and design models became highly valued as the way to decode and reconstruct the organization that makes urban systems. What they lacked is a mechanism by which an analytical description of urban complexity could be translated into a design description. An attempt to define such a mechanism is presented in this paper, where knowledge is retrieved from the natural organization that cities settle into, and devised in a procedural model to support urban planning at the problem definition stage. The model comprises two automated modules, giving preference to street accessibility. The first module implements plausible spatial laws to generate street structures. The performance criteria of these structures are measured against accessibility scores and clustering patterns of street segments. In the second module, an Artificial Neural Networks model (ANNs) is trained on Barcelona’s data, outlining how street width, building height, block density and retail land use might be dependent on street accessibility. The ANNs is tested on Manhattan’s data. The application of the two computational modules is explored at the problem definition stage of a urban planning in order to verify how far deterministic knowledge-based models are in the transition from analysis to design. Our findings suggest that the computational framework proposed could be instrumental at generating simplified representation of an urban grid, whilst being effective at forecasting form-related and functional attributes within a minimum resolution of 200 m. It is finally concluded that as design progresses, knowledge-based models may serve as to minimize uncertainty about complex urban planning problems.

Kinda Al-Sayed, Alan Penn

Exploring the Cognitive Dynamics of Product Appreciation

Understanding users’ choices is the key to both plan and design a product having higher chances of market success. Designers and marketing professional adopt different approaches for such investigation and the lack of a shared perspective between them can represent, by itself, one of the causes of no success in the market arena. This paper presents an approach that aims at focusing on how customers/users interpret product features and link them to their own needs. The theoretical framework behind the proposed approach is based on the latest updates of the situated FBS framework. An illustrative application in the field of sport shoes clarifies strengths and weaknesses of the proposal.

Niccolò Becattini, Gaetano Cascini, Francesca Montagna

A Means to Characterise and Measure the Information Processes of Engineers Using Eye Tracking

How engineers use and process information during design has primarily been investigated using “think-aloud” studies. However, self-reporting thought process affects a task and introduces several associated biases that lead to a general lack of commensurability. Some of these issues can be addressed by using passive observation techniques, such as eye tracking, and standardised information sources to investigate information processing behaviour. Eye tracking is a powerful research tool, from which inferences about information processing can be made based on someone’s gaze. In this paper a series of fundamental information processes based on gaze, Information Operations, are characterised and evaluated in an eye tracking experiment with 42 trainee engineers. It has been demonstrated that Information Operations are distinguishable using gaze and can be used to characterise information processes of engineers. The findings and corresponding operations offer a potentially novel means for real-time support of information activities, compliance checking, and characterising information use.

Duncan Boa, Ben Hicks

Personalised Specific Curiosity for Computational Design Systems

The Personalised Curiosity Engine (PQE, pronounced “pique”) is a framework for computational design systems that models the curiosity of an individual user. This model is then used to synthesise designs that stimulate that user’s curiosity. PQE extends our previous research in modelling surprise and curiosity by adding a model of a specific user to generate designs that are personally creative for that user: novel and valuable for them, but not necessarily for society. We describe PQE as a framework, and then describe Q-chef: a design system applying PQE in the domain of recipe generation with a goal of diversifying its user’s diet over time. We evaluate our framework with several simulations of Q-chef components that serve as a proof-of-concept of the role of personalised curiosity modelling in computational design.

Kazjon Grace, Mary Lou Maher, David Wilson, Nadia Najjar

Design Knowledge


Traversing the Barriers to Using Big Data in Understating How High School Students Design

The context of this paper is a “large learner data” project that seeks to respond to existing challenges by introducing educational data mining and learning analytics into K-12 engineering design research. To probe deeply into student learning, we are developing and refining computational techniques to analyze large process analytics datasets generated through a CAD-based software, Energy3D, that logs design process data as students complete an assigned design challenge, such as a net-zero energy efficient building. We are combining these process analytics with demographic data and pre/post-tests of science and design knowledge. In this paper, we revisit three illustrative research cases to reflect on our experiences and lessons learned with navigating big data, generating useful data visualizations, and integrating process analytics with traditional performance assessment methods to relate design actions to knowledge and learning outcomes.

Robin S. Adams, Molly Goldstein, Şenay Purzer, Jie Chao, Charles Xie, Saeid Nourian

Generalizability of Document Features for Identifying Rationale

One of the challenges in using statistical machine learning for text mining is coming up with the right set of text features. We have developed a system that uses genetic algorithms (GAs) to evaluate candidate feature sets to classify sentences in a document. We have applied this tool to find design rationale (the reasons behind design decisions) in two different datasets to evaluate our approach for finding rationale and to see how features might differ for the same classification target in different types of data. We used Chrome bug reports and transcripts of design sessions. We found that we were able to get results with less overfitting by using a smaller set of features common to the set optimized for each document type.

Benjamin Rogers, Connor Justice, Tanmay Mathur, Janet E. Burge

The Topology of Social Influence and the Dynamics of Design Product Adoption

This paper presents the results of studies on how the dynamics of design product adoption is affected by the topological structure of social communication and influence between consumers, without any changes in the designed product. The dynamics of product adoption are studied over random, modular small world, and scale free social network structures, under local rules of communication. Results show global behaviors emerging from these local agent communication rules, including states where populations completely accept or reject products, starting from similar initial states, as well as regimes and cycles of synchronized behaviors of adoption and rejection. It is claimed that without modeling consumer interactions, understanding and modeling of innovation in design will remain inadequate. Since there could be fundamental limitations to the predictability of adoption behaviors under social influence, innovation strategies could fare better when they focus on the quality, novelty, and technological advances they could bring instead of being guided only by social popularity and influence.

Somwrita Sarkar, John S. Gero

Using Graph Complexity Connectivity Method to Predict Information from Design Representations: A Comparative Study

The objective of this research is to compare the value of information in a design representation used in product development. Two representations are explored in this study: assembly models and function structures. These representations are used to predict assembly time and market value for electromechanical products. This works builds on previous work on using complexity connectivity method to predict assembly time. The precision error is used as a metric to understand how valuable a representation is in answering a specific question. By measuring the value of a representation, designers can select between different representations and monitor the information accumulation in the design project.

C. V. Sri Ram Mohinder, Amaninder Gill, Joshua D. Summers

Identifying Sentiment-Dependent Product Features from Online Reviews

This paper presents a method to correlate relevant product features to the sales rank data. Instead of going through the labor-intensive surveys, online product reviews have become an efficient source to gather consumer preferences. The contribution of the paper is to relate the content of reviews to a product’s sales rank that implicitly reflects the motivation behind what drives customers to purchase the product. After using part-of-speech tagging to extract the relevant feature and opinion pairs from the reviews, the extracted data along with the review ratings and price become the variables to explain the sales rank. An experiment is run for wearable technology products to illustrate the methodology and interpret the result. The result indicates that the positive opinion for battery and negative opinion for sleep tracker are significant towards sales rank, while price is not.

Dedy Suryadi, Harrison M. Kim


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