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Knowledge: the good, the bad, and the ways for designer creativity
Abstract
Design is a highly nonlinear chaotic dynamic process with many possible solutions, some of which can be creative. The chaotic nonlinearity of design dynamics triggers mental stresses in designers, whose creativity happens only when their mental stresses are at an optimal level. Following a deductive approach, this paper investigates how knowledge can contribute to designer creativity by uncovering knowledge's (good and bad) roles in the design process, based on which three ways are recommended to use knowledge properly in design. The assumption is that all designs follow one governing equation, which is a recursive integration of three basic design activities: formulation, evaluation and synthesis. The difference between designs of various fields and different kinds (routine, innovative and creative) lies in the range, content, size and nature of the design space in which the design governing equation works. The design governing equation implies a nonlinear chaotic design dynamics, whose solutions are sensitive to its initial conditions and can be routine, innovative or creative. The design governing equation is solved and reformulated by the designer's creativity capability. Therefore, design researchers, practitioners and educators should cohesively look at both designer's knowledge/experience and the designer's creative thinking process.
... The goal of the design is to change the current environment (⊕ 0 ) into a new environment (⊕ 1 ) by designers, where the result can be creative. The design process follows a recursive nonlinear chaotic dynamic (Nguyen and Zeng, 2012;Yang et al., 2022;Zeng, 2001), with initial conditions determined by the designer's creativity capability, as shown in Figure 1. Design creativity, mostly focused on the novelty and usefulness of a product, can be assessed by many ways (Sakar and Chakrabarti, 2011). ...
... In this paper, instead of considering if a product is creative in the context of the professional knowledge, we consider an individual's creative process by looking at how a designer designs a product that is in a field different from the designer's training. The designer's creativity capability dictates how the design process can generate design solutions through the recursive formulation of the design states (Nguyen and Zeng, 2012;Yang et al., 2022). Different designers could produce distinctive design solutions for the same design problem, and even the same designer could produce distinctive design solutions at different times for the same design problem. ...
... Proper knowledge use during the design process can lead to optimal mental effort and designer creativity . Design creativity relates to the designer's mental stress through an inverse U-shaped curve (Nguyen and Zeng, 2012;Yang et al., 2022). The mental capacity of designers, especially knowledge, skill, and affect, plays a vital role in knowledge use during the design process. ...
Design is a highly nonlinear chaotic dynamic process with many possible solutions, which requires enormous knowledge for designers. This paper investigates how environment-based design (EBD) methodology can help designers use only necessary knowledge for their creativity based on three methods: information search, knowledge acquisition and knowledge application. The methods are applied in an aircraft pylon design, which is evaluated by two aerospace design specialists. The paper discussed the different roles of EBD for novice and expert designers in regard to overcoming emotion and knowledge barriers to achieving designer creativity.
... Creativity undoubtedly stands as one of humanity's most complex and advanced cognitive tasks [10][11][12], engaging both mental and physical activities [6,13]. It operates as a recursive, complex, and nonlinear cognitive process, encompassing tasks like problem understanding, idea generation, and idea evolution [14][15][16]. Despite numerous theoretical investigations, there are unexplored facets of creativity, including assessment methods and human-machine collaboration, which necessitate exploration [17,18]. ...
... Creativity may spontaneously emerge even if one does not intend to conduct a creative design, whereas creative design just may not come out no matter how hard one tries. Moreover, it is conceivable that a designer may lack creativity, while the product itself demonstrates creative attributes, and conversely, a designer may exhibit creativity, while the resulting product does not [16]. ...
The advancement of artificial intelligence (AI) has enabled researchers to apply this effective tool to several complex cognitive processes, one of which is creativity. Different applications such as creativity assessment, human-AI co-creation, and team creativity enhancement are examples of AI applications to creativity. Although several studies have reported AI applications being effective in the field of creativity, there are major shortcomings and open questions from different aspects which should be addressed. In this chapter, we introduce these applications, then review related recent studies, and finally open a discussion to point out the gaps and available research areas for future studies. We believe that the present chapter can shed light on AI-based creativity studies and boost researchers’ understanding of that.
... Designers can implement these design representations using a variety of design and prototyping tools, and these tools can be digital or physical (Camburn et al., 2017;Pei et al., 2011). One of the primary roles of design representations is to facilitate the application of domain knowledge (Yang et al., 2023) in different stages of the design process. In an observational study (Henderson, 1991), highlights the importance of sketches in the early design stages as a tool for rapid visualization and communication of ideas. ...
... Firstly, the TRIZ model is complex and abstract, making it difficult for beginners to learn and apply (Souchkov 2007). Secondly, TRIZ emphasises systematic and structured innovation methods (Yang, Quan, and Zeng 2022). For enterprises and individuals, TRIZ may need to be combined with other more intuitive and innovative methods (Terninko, Zusman, and Zlotin 1998). ...
... Imagination is an important thinking skill for designers (Colombo et al. 2020;Lawson 2006), and a good design process is the foundation of creative design (Liu et al. 2011;Yang, Quan, and Zeng 2022). In recent years, artificial intelligence and neurocognitive sciences have played a huge role in the study of creativity (Goldschmidt 2019). ...
... According to Pahl et al. [76], one important part of the design process is the conceptual design. This process consist of identifying the problems through abstraction, turning them into functions, and connecting the working principles and the basic solutions to elaborate a principle solution [77]. Normally, the design concept generation can occur by searching to fulfill functional requirements and generating a combined concepts design [78,79]. ...
This article presents an original research methodology that combines insights from patents and academic research, offering a unique perspective on energy recovery technologies for trucks equipped with refrigeration units. The purpose of the study is to perform a functional analysis of existing solutions and to suggest a mechanism for exposing unexplored areas and opportunities for innovation. To achieve this goal, a systematic opportunity scan is presented, investigating patents and conducting a state-of-the-art search of existing technologies. This scan classifies a diverse range of solutions, elucidating their interconnections and providing an overview of the existing technological area, covering system components and technical trends. Thus, the main functions and components are listed, as well as the system requirements. Once the functions have been surveyed, a morphological matrix is proposed, and five main functions are analyzed. This methodology makes it possible to list the majority of the possible solutions for the functions analyzed, taking into account the components observed in the literature review and patents, including new components raised by the research group. Finally, with the morphological matrix structure, it was possible to combine unexplored elements, achieving innovative solutions.
... The purpose of knowledge recommendation in engineering design is to trigger the creativity of designers and thus generate innovative ideas (Yang, Quan, and Zeng 2022). Predominantly adopted approaches of knowledge recommendation encompass user preferencebased approaches, expert systems, knowledge graphs (KGs) and representation learning techniques. ...
Since innovation in complex product design hinges on thorough engineering knowledge application, high-quality patent recommendations foster innovation in engineering design. However, many patent knowledge recommendation studies perform patent analysis without comprehensive exploration and proper organisation of knowledge, causing a superficial understanding of patents and returning arbitrary results. To mitigate this issue, a deep learning-based approach for patent representation learning and knowledge recommendation is proposed. First, a four-dimensional patent knowledge model is defined to formalise the patent attributes that critically affect the engineering design outcomes, namely patents’ domain(D), function(F), technology(T) and citation(C). Second, to exploit patent knowledge from their content and citation relationships, a representation learning approach integrating Bidirectional Encoder Representations from Transformers(BERT) and Graph Attention Network(GAT) is introduced. Thereafter a patent knowledge space is established in which each patent is characterised by the function, technology, and citation embeddings. Third, a knowledge requirement space is also constructed by vectorising a designer’s search query via BERT model and linking it to a requirement-representing patent based on similarity. Finally, a recommender prototype is developed and showcased by the knowledge recommendation in sealing structure design tasks. Comparative experiments and application cases validate the effectiveness of our method in patent representation learning and knowledge recommendation.
... Design methodologies aim to address the intricate and iterative nature of the design process, often described as the zig-zag process (Suh, 1990), which is considered an ill-defined or wicked problem (Simon, 1973). Design is a dynamic, recursive, and open-ended process with problems, solutions, and knowledge co-evolving (Dorst & Cross, 2001;Maher et al., 1996;Yang et al., 2022;Zeng, 1991). The co-evolution model illustrates how design information can trigger design processes (Cash & Milene, 2017;Crilly, 2021). ...
In response to evolving societal and technical demands, this research explores the dynamic landscape of product evolution, focusing on the case study of braking systems. Acknowledging the critical role of product evolution analysis in design phases, the study introduces the Environment-Based Design (EBD) methodology. EBD emphasizes environmental analysis before delving into product specifics, employing tools like Recursive Object Model (ROM) diagrams and questioning-and-answering analyses. The paper systematically unfolds with a literature review highlighting various design methodologies, followed by the EBD application in a braking system evolution analysis. Trends in environment components are dissected, emphasizing the increasing influence of the human environment. The discussion underlines the significance of analyzing environment components in product evolution and asserts EBD’s applicability. Despite limitations, such as the exclusive focus on braking systems, the study contributes to understanding product evolution dynamics and advocates for the continued exploration of EBD across diverse products and cultural contexts.
... Untuk desain produk, teknologi ini menciptakan variasi-desain sesuai konsep, memudahkan pemilihan desain yang menarik. Dalam pembuatan logo, desainer deskripsikan elemen-elemen yang diinginkan, teknologi menghasilkan variasi logo yang sesuai merek (Yang, 2022). Dalam desain web, deskripsi tampilan menghasilkan variasi-desain yang menarik dan responsif di berbagai perangkat. ...
OpenAI DALL-E 2 untuk meningkatkan kreativitas desainer grafis dalam komunitas desain grafis di Indonesia. Menggunakan metode penelitian kualitatif, 15 anggota aktif dari komunitas desain grafis yang telah memanfaatkan teknologi ini, diwawancarai secara mendalam. Hasilnya mengungkap potensi teknologi dalam merangsang ek-splorasi kreatif dengan menghasilkan variasi-desain yang beragam dan unik ber-dasarkan deskripsi yang diberikan. Selain itu, teknologi ini juga meningkatkan efisiensi dan kecepatan proses desain, memungkinkan desainer fokus pada pengem-bangan ide dan konsep desain. Meski demikian, tantangan seperti keterbatasan pemahaman deskripsi pengguna dan isu etika serta hak kekayaan intelektual, perlu diperhatikan. Penelitian ini merekomendasikan pengembangan panduan penggunaan yang sesuai dan kolaborasi aktif antara desainer untuk memaksimalkan manfaat teknologi ini. Dengan memahami keterbatasan dan mengatasi tantangan tersebut, teknologi OpenAI DALL-E 2 dapat menjadi alat berharga dalam memperkaya krea-tivitas desainer grafis dan meningkatkan kualitas desain grafis di Indonesia.
... In the context of engineering design, design representations can take several forms, including sketches, CAD models, and prototypes [23]. One of the primary roles of design representations in engineering design is to facilitate the application of domain knowledge [24] in different stages of the design process. In an early observational study, Henderson [25] highlights the importance of sketches in the early design stages as a tool for rapid visualization and communication of ideas. ...
The emergence of additive manufacturing (AM) processes has resulted in the subsequent development of digital design tools and methods. These design tools and methods are intended to help designers leverage the capabilities of AM through design for AM (DfAM). The rapid advancement of these digital design tools calls for designers to rethink their use of various design representations in the design process. For example, designers can now automate concept generation through tools such as generative design, potentially reducing designers’ reliance on conceptual sketches. However, little research has explored how designers use design representations in the face of constantly evolving DfAM methods. In this research, we aim to explore this gap through an experimental study with fourth-year engineering students. Specifically, participants were given one hour to complete a DfAM task, and their use of the various design representations was assessed using eye-tracking. Their design representation strategies (e.g., transitions between different representations) were qualitatively compared between designers that generated solutions of high vs low creativity and high vs low performance. From our results, we see that designers who generate solutions of high creativity tend to spend a significant amount of time generating CAD models of their solutions, especially in the later stage of the design task. We also see that designers who generate high-performing solutions (i.e., low build time and material) tend to spend more time sketching their solutions. These findings suggest that designers must employ different design representation strategies depending on the desired outcomes (i.e., high creativity vs high performance). These results provide an essential first step toward creating a generalized framework for designers to employ different design representations when designing for AM.
... However, since the design process is dynamically complicated, design activities are dominated by instability, iterative problem-solving approaches and uncertainty of design outcomes, making it challenging for design teams to quickly and efficiently solve design problems [5]. Scholars believe that a designer's knowledge is the core of a creative design process, and exploring the knowledge embedded in the design process can effectively improve designers to deeply understand design problems [6,7]. Existing studies mostly concentrate on explicit knowledge, also known as know-how knowledge, to analyze and describe the behaviors of designers [8][9][10]. ...
What do designers actually do while they are designing? How about their ideas and intentions toward a specific design activity? These issues are still urgently in need of resolution since designers play such a crucial role in the design process. However, existing research primarily concentrates on the explicit knowledge representation of designers' activities, but ignores tacit information that is underlying the motivation behind those activities. Fortunately, as a psychology-based inner cognitive representation of external reality, mental models take us a glimpse into explaining and driving designer activities. Based on the above, this paper proposed a novel framework with Latent Dirichlet Allocation and Word2Vec integrated harmoniously to capture the designer' activities. Additionally, both the know-how and know-why knowledge were represented by eliciting knowledge structure and belief structure of mental models respectively. Based on the distribution values of these two structures, the using opportunities of designer's ideas are further explored to reveal their potential for being adopted, improved, explored, or discarded during the design process. Then the detailed design process is characterized by mental models to express the designers actions, ideas, and intentions for the artifact that they are designing. Finally, the experimental results performed a practical design case demonstrating that our proposed framework is applicable and helpful for designing.
This article exexamines the role of knowledge in the innovation process, highlighting knowledge creation as a key factor in successful innovation. Current economic realities underscore the importance of knowledge as a fundamental resource for creating unique competitive advantage. The relationship between innovation and the knowledge creation process, which is often overlooked or underestimated, is explored.
The article presents different approaches to defining and classifying innovation and knowledge creation models. The authors propose a classification approach for knowledge-based innovations based on parameters such as the type of knowledge according to novelty level (completely new knowledge vs. use of existing knowledge), knowledge creation (market knowledge vs. empirical knowledge), and knowledge characteristics (explicit vs. implicit). Empirical research on knowledge-based innovation has allowed us to complement the classification approach with information on the source of knowledge acquisition for innovation creation - a critical feature for company managers.
The conclusion underlines the importance of knowledge creation and integration for the successful implementation of innovation.
Background
Key Performance Indicators (KPIs) are crucial for guiding employees towards organizational goals and providing stakeholders with insights into goal achievement. Developing effective KPIs is particularly challenging for startups due to dynamic environments and limited resources, often requiring extensive domain expertise.
Methods
This study proposes an effective KPI development process using the Environment-Based Design (EBD) methodology. The approach systematically converts an organization's mission statement into KPIs through three steps: generating questions and answers, identifying a performance network, and extracting KPIs. It employs tools like the Recursive Objective Model (ROM) and structured question-asking techniques to aid knowledge acquisition and performance network integration.
Results
The methodology was validated using Flybe's case, Europe's largest regional airline. Two graduate student designers with no aviation experience developed KPIs that were comparable to those in Flybe's 2018 Annual Report, while also addressing additional operational aspects like route attractiveness.
Conclusion
The EBD guided approach reduces reliance on prior domain knowledge, making KPI development accessible to non-experts and enhancing repeatability for experts. Although the study is limited to the airline industry and English-speaking countries, it demonstrates the potential for broader application. Future research should explore the approach in diverse organizational contexts and cultural settings to further validate its effectiveness and adaptability.
Creative design has become the core of competitiveness for enterprises, and the design process is an activity based on multi-domain knowledge. Designers need to have a lot of interdisciplinary knowledge in this activity, and there may be a burden on understanding. To alleviate understanding burden and promote knowledge integration, a dual-layer concept network is established based on complex networks. Knowledge association in the network originates from the perspective of innovation and product design, facilitating in providing designers with creative and content-related knowledge. This paper takes function, invention principle and scientific principle as the label to build a creative attribute network, and uses the semantic similarity between knowledge texts to build a semantic association network. Combining creative attributes and content semantics of knowledge, a novel knowledge management and browsing method based on a dual-layer concept network is proposed. Meanwhile, due to the ambiguity and uncertainty of design activity and knowledge demand, designers repeatedly query knowledge based on a dual-layer concept network. During this process, designers’ think of diverges and associates, which inspire them to integrate knowledge and generate creative ideas. Finally, this paper takes the problem of vibrating screens as an example to verify the practicability and effectiveness of this method. The methodology is expected to be served as an essential supporting tool for sparking innovation.
This chapter delves into the inherent role of energy within the proposed theoretical framework, communication dynamics, which draws inspiration from Shannon’s communication theory. Beginning with the foundational understanding of atoms as quintessential carriers of energy, especially evident in electron orbital structures, we explore the centrality of energy in varying computational models, from classical mechanics to quantum mechanics. A pivotal observation reveals the confluence of information and energy, suggesting that in many systems, particularly in quantum realms, information transfer necessitates energy interactions. Further, we probe the energy implications within particle-wave duality, indicating dual energy manifestations for entities. By emphasizing energy’s universality, we argue for its role as a bridge in the multi-scale model integration of communication dynamics with diverse scientific fields. We posit that for the holistic success of this new framework, a coherent understanding and representation of energy across multiple scales and domains is imperative.
Brain dynamics associated with design creativity tasks are largely unexplored. Despite significant strides, there is a limited understanding of the brain-behavior during design creation tasks. The objective of this paper is to review the concepts of creativity and design creativity as well as their differences, and to explore the brain dynamics associated with design creativity tasks using electroencephalography (EEG) as a neuroimaging tool. The paper aims to provide essential insights for future researchers in the field of design creativity neurocognition. It seeks to examine fundamental studies, present key findings, and initiate a discussion on associated brain dynamics. The review employs thematic analysis and a forward and backward snowball search methodology with specific inclusion and exclusion criteria to select relevant studies. This search strategy ensured a comprehensive review focused on EEG-based creativity and design creativity experiments. Different components of those experiments such as participants, psychometrics, experiment design, and creativity tasks, are reviewed and then discussed. The review identifies that while some studies have converged on specific findings regarding EEG alpha band activity in creativity experiments, there remain inconsistencies in the literature. The paper underscores the need for further research to unravel the interplays between these cognitive processes. This comprehensive review serves as a valuable resource for readers seeking an understanding of current literature, principal discoveries, and areas where knowledge remains incomplete. It highlights both positive and foundational aspects, identifies gaps, and poses lingering questions to guide future research endeavors.
Improving existing products plays a vital role in enhancing customer satisfaction and coping with changes in the market. Analyzing user experience (UX) to find the deficiencies of existing products and establishing improved schemes is the key to UX-driven product improvement, especially at the conceptual design stage. Although some tools used in conceptual design, such as requirements analysis and knowledge reasoning, have advanced recently, they lack targeted goals and sufficient efficiency in identifying insufficient product attributes and improving existing functions and structures. The challenge lies in considering the influence imposed on design activities by the original product features (including attributes, functions, and structure). In this study, a knowledge-enabled approach and framework that integrates the conceptual design process, online reviews for UX, and knowledge is proposed to support product improvement. Specifically, a decision-making algorithm based on UX analysis is proposed to identify to-be-improved product attributes. Then, through optimizing the previous knowledge application model from knowledge requirement transformation, knowledge modeling, and knowledge reasoning, a smart knowledge reasoning model is established to push knowledge for functional solving of the to-be-improved attributes. A knowledge configuration method is used to modify product features to generate an improved scheme. To demonstrate the feasibility of the proposed approach, a case study of improving an agricultural sprayer is conducted. Through discussion, this study can help to regulate design activities for product improvement, enhance data and knowledge application, and promote divergent thinking during scheme modification.
Additive Manufacturing (AM) is often considered to increase opportunities for creativity in design compared to traditional manufacturing methods. At the same time, it is suggested that regulated work can have a negative effect on engineers’ creative abilities, which are linked to three components of creativity (expertise, motivation, and creative thinking skills). Due to the ‘newness’ of AM, engineers need to broaden their expertise to fully exploit their creative potential while using AM. Previous research has presented support tools to assist engineers to understand the complexity of AM. A majority of such studies focus on novice engineers, rather than providing an understanding of how AM is involved in industrial practices. This paper follows three case studies from the space industry, a regulated industry, that aims to re-design a product for AM over a 21-month time period. The purpose is to explore how restrictions affect engineers’ opportunities to build AM expertise for creativity in a regulated industry. Results show the importance that case-specific aspects have on an engineer’s learning path for adopting AM. Engineers find themselves in a complex situation, with a conflict between being ‘safe’ or innovative, where innovation within such regulated industries is often compared to innovating ‘in a box’.
Technology is essential to innovation and economic prosperity. Understanding technological changes can guide innovators to find new directions of design innovation and thus make breakthroughs. In this work, we construct a technology fitness landscape via deep neural embeddings of patent data. The landscape consists of 1,757 technology domains and their respective improvement rates. In the landscape, we found a high hill related to information and communication technologies (ICT) and a vast low plain of the remaining domains. The landscape presents a bird’s eye view of the structure of the total technology space, providing a new way for innovators to interpret technology evolution with a biological analogy, and a biologically-inspired inference to the next innovation.
Project-based design method is widely used in engineering design education. However, it is time-consuming to develop design thinking skills through projects. This paper proposes that learning methodology and projects will significantly improve students’ learning experience and outcomes. The TASKS framework is used to analyze the pros and cons of three different learning methods: methodology-based learning, project-based learning, and methodology-driven project practice. According to the TASKS framework, perceived Task workload and mental capacity (including Affect, Skills, and Knowledge) affect mental Stress. Mental stress has an inverse U-shaped curve relationship with mental effort. Since the mental capability can be assumed constant for a short period, human performance in a task is related to the mental effort that can be put into the task. Methodology-based learning method requires students to be comfortable using an abstract methodology, which is often not the case. On the other hand, while project-based learning can engage students effectively, a high number of projects are needed to equip students with the necessary design thinking skills. The methodology-driven project practice would integrate the advantages of both previous methods. This paper conducted a detailed analysis of the three learning methods using the TASKS framework.
Objective
A beta version (2018) of International Classification of Diseases, 11th Revision for MMS (ICD-11), needed testing. Field-testing involves real-world application of the new codes to examine usability. We describe creating a dataset and characterizing the usability of ICD-11 code set by coders. We compare ICD-11 against ICD-10-CA (Canadian modification) and a reference standard dataset of diagnoses. Real-world usability encompasses code selection and time to code a complete inpatient chart using ICD-11 compared with ICD-10-CA.
Methods and results
A random sample of inpatient records previously coded using ICD-10-CA was selected from hospitals in Calgary, Alberta (N = 2896). Nurses examined these charts for conditions and healthcare-related harms. Clinical coders re-coded the same charts using ICD-11 codes. Inter-rater reliability (IRR) and coding time improved with ICD-11 coding experience (23.6 to 9.9 min average per chart). Code structure comparisons and challenges encountered are described. Overall, 86.3% of main condition codes matched. Coder comments regarding duplicate codes, missing codes, code finding issues enabled improvements to the ICD-11 Browser, Coding Tool, and Reference Guide. Training is essential for solid IRR with 17,000 diagnostic categories in the new ICD-11. As countries transition to ICD-11, our coding experiences and methods can inform users for implementation or field testing.
A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords derived from these research questions led to 975 records initially retrieved from 7 scientific search engines. Finally, 86 articles were selected for inclusion in the review. As the primary research finding, we identified 15 ML-based requirement elicitation tasks and classified them into four categories. Twelve different data sources for building a data-driven model are identified and classified in this literature review. In addition, we categorized the techniques for constructing ML-based requirement elicitation methods into five parts, which are Data Cleansing and Preprocessing , Textual Feature Extraction, Learning, Evaluation, and Tools . More specifically, 3 categories of preprocessing methods, 3 different feature extraction strategies, 12 different families of learning methods, 2 different evaluation strategies, and various off-the-shelf publicly available tools were identified. Furthermore, we discussed the limitations of the current studies and proposed eight potential directions for future research.
Background
Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive information regarding all aspects of patient care, offering a valuable complement to administrative data. Harnessing the rich clinical data in EMRs offers a unique opportunity to improve detection, identify possible risk factors of AE and enhance surveillance. However, the methodological tools for detection of AEs within EMR need to be developed and validated. The objectives of this study are to develop EMR-based AE algorithms from hospital EMR data and assess AE algorithm’s validity in Canadian EMR data.
Methods
Patient EMR structured and text data from acute care hospitals in Calgary, Alberta, Canada will be linked with discharge abstract data (DAD) between 2010 and 2020 (n~1.5 million). AE algorithms development. First, a comprehensive list of AEs will be generated through a systematic literature review and expert recommendations. Second, these AEs will be mapped to EMR free texts using Natural Language Processing (NLP) technologies. Finally, an expert panel will assess the clinical relevance of the developed NLP algorithms. AE algorithms validation: We will test the newly developed AE algorithms on 10,000 randomly selected EMRs between 2010 to 2020 from Calgary, Alberta. Trained reviewers will review the selected 10,000 EMR charts to identify AEs that had occurred during hospitalization. Performance indicators (e.g., sensitivity, specificity, positive predictive value, negative predictive value, F1 score, etc.) of the developed AE algorithms will be assessed using chart review data as the reference standard.
Discussion
The results of this project can be widely implemented in EMR based healthcare system to accurately and timely detect in-hospital AEs.
Additive Manufacturing (AM) has become an established discipline in both research and education. However, to achieve its full potential AM requires a step-change in design thinking, which makes Design for AM (DfAM) education and training crucial. This paper reports results from the first attempt to investigate the uptake of DfAM in higher education. This research required the development and administration of an articulated online survey, in which educators worldwide who teach AM and DfAM have participated. The results show that DfAM is taught in a considerable number of courses. However, the survey revealed that DfAM is seldom recognised as a distinct course or topic and the relevance attributed and proportion of teaching dedicated to DfAM within wider AM is typically marginal. DfAM is being mostly taught in North America and Europe and is also typically taught in institutions that are research active in AM or specifically DfAM, suggesting the subject has not yet reached maturity or diffusion into mainstream design and engineering curricula. It was interesting to find that currently, the contents of courses do not differ significantly between engineering and design programmes. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Existing theories and frameworks generally have regarded creativity as inhering in a person, a task, a situation, or a combination of 2 of these 3 elements. After reviewing these approaches, and frameworks that are based on the interaction of more than 2 components, we propose a Person × Task × Situation synergistic paradigm, according to which creativity is dynamic and can be fully understood only as an interaction of all 3 of the elements. Building on the strengths of existing frameworks, our P × T × S proposal highlights: (a) the need to include the other 2 elements as moderators, regardless of which element is the central or starting point of the analysis, (b) the idea that the extent to which each element influences the others and the degree of overlap among elements can vary, and (c) the dynamic aspect of creativity, associated with changes in different persons across the lifespan, for different creative tasks, and for different situations. In addition to contributing an integrative theoretical account, this framework has significant, pragmatic implications for both the assessment and the development of creativity. We end with a call for both researchers and practitioners who test for or teach for creativity to specify the range of persons, tasks, and situations to which their assessments or training generalize.
The dynamic creativity framework (DCF) represents a new theoretical perspective for studying the creativity construct. This framework is based on the dynamic definition of creativity, and it has both theoretical and empirical implications. From a theoretical point of view, we review the characteristics of the dynamic creative process and its extension into the dynamic universal creative process, encompassing creativity at different layers of complexity. We discuss the key concept of creative potential, considering individual, sociocultural, and material viewpoints, and we show how the DCF is instrumental in clarifying the relationship between creativity and intelligence, between creativity and anticipation, as well as in introducing the concept of ‘organic creativity’. From the empirical perspective, we focus on the dynamic creative process broken down into four phases: i) drive, ii) information, iii) idea generation, iv) idea evaluation. We review results obtained through investigations accounting for the dynamic interplay between emotional and cognitive components defining creative performance for each. Experiments were conducted to measure the role of emotions and attention in driving the dynamic process, considering the processing of apparently irrelevant information and the interaction between idea generation and idea evaluation, always taking into account individual differences as measured through personality traits, performance variables, or lifetime achievement. Neurophysiological evidence is considered in discussing dynamic effects in divergent thinking, such as the serial order effect, as well as the possibility to enhance creative potential through neurofeedback. Finally, we report on the effects of different environments on the creative process, highlighting the dynamics produced by context-embeddedness.
This article explores the advantages of viewing intelligence not as a fixed trait residing within an individual, but rather as a person × task × situation interaction. The emphasis in the article is on the role of persons solving tasks embedded in situations involving learning, intellectual abilities, and competencies. The article opens with a consideration of the role of situations in intelligent behavior. The article then discusses how intelligence is more similar to creativity and wisdom, in terms of the role of situations, than many psychologists have realized. Then the article reviews the role of situations in identity-based and irrational thinking and in conspiratorial thinking and cults. Next the article discusses the demonstrated importance of situations in assessment, but also notes the difficulties in sampling situations. Finally, the article draws conclusions, in particular, that, given our lack of situation-based tests, we need to be more modest in our interpretations results from conventional tests of intelligence.
Unplanned design iterations are considered one of the reasons for the high failure rate of new product development (NPD) projects. Generally, organisations employ ‘proactive risk management’ (PRM) and ‘reactive fast learning’ (RFL) to manage unplanned design iterations. This paper aims to explore how organisations employ PRM and RFL approaches to manage unplanned design iterations in the NPD process. To that end, a cross-sectional interview study was conducted in eight organisations. The interview transcripts were analysed as a primary data source using thematic qualitative text analysis technique. For PRM approach, results demonstrate that the design teams were more active in risk monitoring in the design phase as compared to risk identification in the concept development phase. Generally, design teams reduced the likelihood of unplanned design iteration risks by employing learning methods in addition to risk mitigation strategies. For RFL approach, results reveal that organisations lacked a structured approach to select suitable learning methods for fast resolution of unplanned design iterations and to convert new knowledge into organisational learning. We conclude that PRM is more established as compared to RFL in managing unplanned design iterations. We develop recommendations of how organisations can use RFL approaches more efficiently alongside PRM approaches.
Implementation is ubiquitous. The identification of barriers to implementation is critical for achieving implementation success. This paper introduces and discusses a deductive theory-based framework, TASKS, to guide the identification of implementation barriers. The TASKS framework deals with the relationships between a Task and the task implementer’s Affect, Skills, and Knowledge, based on the inversed U-shaped mental Stress-mental effort relation. The TASKS framework classifies implementation barriers into four categories: 1) emotion barriers, 2) logic barriers, 3) knowledge barriers, and 4) resources barriers. The TASKS framework detects barriers to implementation following three steps, 1) identifying the ideal TASKS components, 2) modelling the implementer’s mental capability, and 3) detecting barriers to implementation. The TASKS framework can be applied to a wide range of disciplines for effective and efficient task implementation.
Engineering design processes are often defined as beginning with a problem and diverging to generate possible solutions; however, design processes can start with a newly developed technological solution, followed by a divergent search for potential problem applications it can solve, termed ‘solution mapping'. Building on previous research where engineering practitioners described their successful strategies for solution mapping, we created a tool to support solution mapping and tested its impact with engineering students. In a single session, graduate and advanced undergraduate engineering students were presented with a novel technology and worked to identify potential problem applications for it. Comparing students using the Solution Mapping Design Tool to two control groups, more diverse problem applications were produced when using the tool. Considering diverse options is an important feature of design processes shown to promote creativity and innovation. With this successful proof of concept, future work on solution mapping will identify how to support engineers seeking problem applications by making use of new technologies.
Functional models represent a form independent blueprint of a product. As with any blueprint or schematic, a consistent language or coding system is required to ensure others can read it. This paper introduces such a design language, called a functional basis, where product function is characterized in a verb-object (function-flow) format. The set of functions and flows is intended to comprehensively describe the mechanical design space. Clear definitions are provided for each function and flow. The functional basis is compared to previous functional representations and is shown to subsume these attempts as well as offer a more consistent classification scheme. An example is provided for using the functional basis to form a functional model. Applications to the areas of product architecture development, function structure generation, and design information archival and transmittal are discussed.
Many neurocognitive studies endeavor to understand neural mechanisms of basic creative activities in strictly controlled experiments. However, little evidence is available regarding the neural mechanisms of interactions between basic activities underlying creativity in such experiments. Moreover, strictly controlled experiments might limit flexibility/freedom needed for creative exploration. Thus, this study investigated the whole-brain neuronal networks’ interactions between three modes of thinking: idea generation, idea evolution, and evaluation in a loosely controlled creativity experiment. The loosely controlled creativity experiment will provide a degree of flexibility/freedom for participants to incubate creative ideas through extending response time from a few seconds to 3 min. In the experiment, participants accomplished a modified figural Torrance Test of Creative Thinking (TTCT-F) while their EEG signals were recorded. During idea generation, a participant was instructed to complete a sketch that was immediately triggered by a sketch stimulus at first sight. During idea evolution, a participant was instructed to complete a sketch that is radically distinctive from what was immediately triggered by the sketch stimulus. During the evaluation, a participant was instructed to evaluate difficulties of thinking and drawing during idea generation and evolution. It is expected that participants would use their experience to intuitively complete a sketch during idea generation while they could use more divergent and imaginative thinking to complete a possible creative sketch during idea evolution. Such an experimental design is named as a loosely controlled creativity experiment, which offers an approach to studying creativity in an ecologically valid manner. The validity of the loosely controlled creativity experiment could be verified through comparing its findings on phenomena that have been effectively studied by validated experimental research. It was found from our experiment that alpha power decreased significantly from rest to the three modes of thinking. These findings are consistent with that from visual creativity research based on event related (de)synchronization (ERD/ERS) and task-related power changes (TRP). Specifically, in the lower alpha band (8–10 Hz), the decreases of alpha power were significantly lower over almost the entire scalp during idea evolution compared to the other modes of thinking. This finding indicated that idea evolution requires less general attention demands than the other two modes of thinking since the lower alpha ERD has been reported as being more likely to reflect general task demands such as attentional processes. In the upper alpha band (10–12 Hz), the decreases of alpha power were significantly higher over central sites during the evaluation compared to idea evolution. This finding indicated that evaluation involves more task-specific demands since the upper alpha ERD has been found as being more likely to reflect task-specific demands such as memory and intelligence, as was defined in the literature. In addition, new findings were obtained since the loosely controlled creativity experiment could activate multiple brain networks to accomplish the tasks involving the three modes of thinking. EEG microstate analysis was used to structure the unstructured EEG data to detect the activation of multiple brain networks. Combined EEG-fMRI and EEG source localization studies have indicated that EEG microstate classes are closely associated with the resting-state network as identified using fMRI. It was found that the default mode network was more active during idea evolution compared to the other two modes of thinking, while the cognitive control network was more active during the evaluation compared to the other two modes of thinking. This finding indicated that idea evolution might be more associated with unconscious and internal directed attention processes. Taken together, the loosely controlled creativity experiment with the support of EEG microstate analysis appears to offer an effective approach to investigating the real-world complex creativity activity.
Professional Identity (PI) is a social- and self-perceptive construct that describes how people understand themselves as professionals. PI guides professional development by shaping professionalism, role assumptions, responsibilities, values, and behaviour; and is a critical factor in professional performance and wellbeing. As such, PI has significant implications for how we support engineering designers in professional development and direct their social- and self-understanding. However, no current research provides a complete picture of PI elements important for Designers’ Professional Identity (DPI). This study aims to review and synthesise PI elements, currently discussed separately in the design literature, in order to propose a holistic understanding of DPI. Based on an extensive literature review, we find that DPI consists of two distinct sets of elements: Personal Attributes (PA) and Design Skills (DS). We present these two sets of elements in terms of meaning, possible relations between them, and their influence on DPI development. In addition, we propose multiple directions for future research.
This article investigates how Big Five personality traits are related to creative achievements and lawbreaking behavior in a large sample (N = 1669) of Polish adults. Structural equation modelling with personality modelled as a bi-factor structure demonstrated a weak, yet significant link (r = .21) between latent factors of creative achievements and lawbreaking behavior. A general factor of personality was unrelated to creative achievement, but negatively linked to lawbreaking behavior. Lawbreaking behavior was also negatively predicted by conscientiousness and agreeableness, while only openness positively predicted creative achievement. A person-centered analysis illustrated three distinct personality profiles: resilient, undercontrolled, and overcontrolled that differed in both lawbreaking behavior and creative achievements.
In his book 'Thinking, Fast and Slow' Daniel Kahneman presented a model of human cognition based on two modes or “systems” of thinking: system 1 thinking that is fast and intuitive, and system 2 thinking that is slow and tedious. This paper proposes a framework for applying Kahneman’s model to designing, based on the function-behaviour-structure (FBS) ontology. It casts four instances of designing in this framework: design fixation, case-based design, pattern language-based design, and brainstorming.
A significant body of knowledge exists on inverse problems and extensive research has been conducted on data-driven design in the past decade. This paper provides a comprehensive review of the state-of-the-art methods and practice reported in the literature dealing with many different aspects of data-informed inverse design. By reviewing the origins and common practice of inverse problems in engineering design, the paper presents a closed-loop decision framework of product usage data-informed inverse design. Specifically reviewed areas of focus include data-informed inverse requirement analysis by user generated content, data-informed inverse conceptual design for product innovation, data-informed inverse embodiment design for product families and product platforming, data-informed inverse analysis and optimization in detailed design, along with prevailing techniques for product usage data collection and analytics. The paper also discusses the challenges of data-informed inverse design and the prospects for future research.
A properly designed product-system platform seeks to reduce the cost and lead time for design and development of the product-system family. A key goal is to achieve a tradeoff between economy of scope from product variety and economy of scale from platform sharing. Traditionally, product platform planning uses heuristic and manual approaches and relies greatly on expertise and intuition. In this paper, we propose a data-driven method to draw the boundary of a platform-system, complementing other platform design approaches and assisting designers in the architecting process. The method generates a network of functions through relationships of their co-occurrences in prior designs of a product or systems domain and uses a network analysis algorithm to identify an optimal core-periphery structure. Functions identified in the network core co-occur cohesively and frequently with one another in prior designs, and thus are suggested for inclusion in the potential platform to be shared across a variety of product-systems with peripheral functions. We apply the method to identify the platform functions for the application domain of spherical rolling robots, based on patent data.
How can we account for the sudden appearance of such dazzling artists and scientists as Mozart, Shakespeare, Darwin, or Einstein? How can we define such genius? What conditions or personality traits seem to produce exceptionally creative people? Is the association between genius and madness really just a myth? These and many other questions are brilliantly illuminated in The Origins of Genius. Dean Simonton convincingly argues that creativity can best be understood as a Darwinian process of variation and selection. The artist or scientist generates a wealth of ideas, and then subjects these ideas to aesthetic or scientific judgment, selecting only those that have the best chance to survive and reproduce. Indeed, the true test of genius is the ability to bequeath an impressive and influential body of work to future generations. Simonton draws on the latest research into creativity and explores such topics as the personality type of the genius, whether genius is genetic or produced by environment and education, the links between genius and mental illness (Darwin himself was emotionally and mentally unwell), the high incidence of childhood trauma, especially loss of a parent, amongst Nobel Prize winners, the importance of unconscious incubation in creative problem-solving, and much more. Simonton substantiates his theory by examining and quoting from the work of such eminent figures as Henri Poincare, W. H. Auden, Albert Einstein, Marie Curie, Charles Darwin, Niels Bohr, and many others. For anyone intrigued by the spectacular feats of the human mind, The Origins of Genius offers a revolutionary new way of understanding the very nature of creativity.
The concept of emotion is closely related to affect, which is an encompassing term, consisting of emotions, feelings, moods, and evaluations. Organizations, conferences, and special issues related to emotion and design in human factors and ergonomics have been burgeoning. Core affect is object-free without being directed at anything, that is, no emotional associations, whereas affective quality is related to or belongs to the product and has the ability to cause a change in core affect during the human-product interaction process so that the product is attributed with creating emotional associations. Quality function deployment is a method that first transforms qualitative customer needs into quantitative parameters, then deploys the functions to form product quality, and then translates product quality into design elements, and finally to specific manufacturing processes. Emotional design has been well recognized in the domain of human factors and ergonomics. The chapter reviews related models and methods of emotional design.
Specific design knowledge (SDK) plays a crucial role in engineering design, as it enables designers to define a system structure that can fulfil the required functions through its behaviour. A variety of modelling methods aim at supporting the gain of this knowledge. However, they are usually evaluated concerning the designs produced rather than the knowledge generated in the process. Also, established operationalisations of SDK are missing. This results in a lack of understanding of the generation of SDK. Hence, an experimental study is conducted to investigate the impact of an exemplary modelling method on the generation of SDK. The study is set up with 35 participants, who analyse two technical systems. Intuitive approaches are compared with the application of the modelling method. On the system level, SDK is assessed through relations of structure and behaviour. On the detail level, function-critical system areas and function-relevant system states, are investigated. Results show, that the modelling method increases SDK at the system level compared to intuitive approaches. At the detail level, no statement about statistically significant differences could be derived. The presented study design can provide a baseline for investigations of similar modelling methods or other design methods supporting the generation of SDK.
The traditional practice of value-driven engineering and systems design is mainly based on net present values (NPVs). It is essentially enacted as a budgetary technique that neglects the future risk and strategic flexibility of a design project. Incorporating real options theory in value-driven decision models can improve the inability of NPV analysis in dealing with the upside potential of managerial flexibility and operational uncertainty over the design project life. This paper examines the critical issues and research opportunities for establishing a theoretical foundation of value-driven multiplayer game decision making in large complex engineering and systems design projects. This paper envisions a research framework for value-driven cooperative negotiation by synthesising the mathematical foundations of utility theory, real options theory and game theory into a coherent framework of design decision analysis. Fundamental issues and research directions are discussed to develop a variety of new methods for enhancing the formulation of value models for value-driven design with decision support to achieving equilibrium solutions with optimal value allocation among multiple decision agents involved in engineering and systems design.
Usability and emotionality are fundamental aspects of user experience. However, the actual creation of an equally usable and emotionally appealing product design is still challenging for product developers, not least because of competing objectives during such equal consideration of both aspects. In order to make a user-oriented decision between a more usable or more emotional product design, product developers need a profound understanding of what matters to the user in different usage situations. By conducting 22 semi-structured interviews, we contribute to this aim by identifying and examining factors that influence a user’s perceived importance of usability and emotionality in product design. In total, 29 influencing factors were identified with the purpose of use, the type of product and other people’s attitudes towards a product being most relevant for both emotionality and usability. Nine influencing factors from the literature were additionally examined in terms of their strength and direction in which they influence the importance of emotionality and usability. Hereby, considerable differences within individual expressions of the influencing factors were revealed. Furthermore, the perceived importance of emotionality varied much more than that of usability.
This paper proposes a novel framework for building semantic networks from a seed design statement using Recursive Object Modeling (ROM), Word2Vec language modelling, and vector semantic-based method. Semantic Scholar API was used to retrieve abstracts of scientific papers to build ROM-based Semantic Networks to address the design problem implied in the seed design statement, following Environment Analysis from Environment-Based Design (EBD) methodology. The proposed framework was applied to construct the semantic network for a project to design aircraft braking systems, which demonstrates the framework's efficiency. The presented research makes two major contributions: a ROM-based phrase extractor and a domain-specific language model, which is trained on the automatically collected literature abstracts. Using a manually created and assessed truth set containing 100 pairs of abstract-key phrases, the phrase extractor was evaluated by benchmarking it with two existing off-the-shelf key phrase extraction algorithms: TextRank and Rake. The ROM-based phrase extractor extracted most key phrases from target domains and showed higher precision, recall, and F-1 scores than other methods. Meanwhile, the trained project-specific language model was evaluated using the NASA thesaurus. We randomly sampled 457 pairs of connected domain-specific terms related to aircraft braking and landing knowledge. Our Skip-gram model was compared with Google's pre-trained word2vec model and a baseline word2vec model. The results demonstrated that our language model could detect the most pairs of concepts from the NASA thesaurus. The generated semantic network can be applied to design information retrieval, computer-aided design idea generation, cross-domain communication support system, and designer training tool.
The topic of uncertainty has not received the attention it deserves. This chapter develops the view that uncertainty is a part of all creative efforts, first by going into some detail about how creativity is defined, then turning to several kinds of research on creativity that support that view. The first section about the definition of creativity is a bit abstract but draws from respected theories of associative processes and problem solving. The next section is more concrete and practical, with material on education and testing. Next is a discussion of some lessons learned from studies of physics and creativity, as well as implications of recent studies of politics and creativity. The final section might be the simplest because it discusses Future Studies, and of course the future is an uncertain thing. The role of creative thinking for the future is explored immediately before the concluding comments.KeywordsUncertainty principleSchrödinger’s catCreative potentialPsychoeconomicsPolitics of creativityConservatismLiberalism
Additive manufacturing (AM) presents designers with unique manufacturing capabilities while imposing several limitations. Designers must leverage AM capabilities – through opportunistic design for AM (O-DfAM) – and accommodate AM limitations – through restrictive (R-) DfAM – to successfully employ AM in engineering design. This dual DfAM approach – comprising O- and R-DfAM – starkly contrasts traditional, limitation-based design for manufacturing (DfM). Therefore, designers must transition from a restrictive DfM mindset towards a ‘dual’ design mindset. Designers’ prior experience, especially with DfM could inhibit their ability to transition towards dual DfAM. On the other hand, experienced designers’ auxiliary skills (e.g. with computer-aided design) could help them implement DfAM in their solutions. However, little research has studied the influence of prior experience on DfAM use in the later design stages (i.e. embodiment and detail design), and we explore this research gap. Specifically, we conducted an experimental study comprising a task-based DfAM educational intervention with first-year student designers and upper-level student designers. Participants’ DfAM self-efficacy and their integration of DfAM in their solutions were compared between the two groups. From our results, we see that experienced designers report higher baseline self-efficacy with R-DfAM but not O-DfAM. We also see that experienced designers demonstrate a greater use of certain DfAM concepts (e.g. part and assembly complexity) in their designs. These findings suggest that introducing designers to O-DfAM early could help develop a dual design mindset; however, having more engineering experience might be necessary for them to implement DfAM into their designs.
Past research in design typically postulates a relationship between divergent thinking and ideation, but little or no empirical evidence is available to critically assess the connection between the two. Using protocol analysis of 35 design experiments, this paper constructs a detailed investigation of the ways divergent thinking and ideation occur in the design process. Two measures are extracted from the protocol data – a divergency index (D) and an ideation index (I) – and quantitative comparisons are constructed between the two. Thereafter four types of individual design processes are identified and discussed. The paper concludes that, within the limits of the method used, there is clear evidence connecting divergent thinking and production of ideas.
Facing an increasing demand and market competition for personalization, more and more service enterprises need to offer personalized service products to enhance customer satisfaction and the service level in a cost-effective manner. Service products are inherently coupled with service operations in order to leverage service satisfaction upon operations costs. This requires that design of personalized service products must be coordinated with service operations planning (SOP) within a coherent framework of joint optimization. This study proposes a hierarchical joint optimization (HJO) model for personalized service product family (SPF) design considering crowdsourcing of service operations by taking advantage of service resource family (SRF). A nested genetic algorithm (NGA) is developed to solve the HJO model and find a scheme of a personalized service product, based on which SPF design is derived along with the corresponding SRF. A case study of personalized tourism product family design and tourism operations planning is reported to illustrate the feasibility and potential of the proposed joint optimization method.
Five frames for experience are explored: dynamic, balanced, sudden, interdependent, emergent, moving beyond a reductionist view to consider examples honoring a nonlinear chaos and complexity context. This interfaces with aware, present, healthy, open and creative ways of being in the world, separately and together. Discussion looks at a potential shift in worldview and view of self-in-world. (Keywords: everyday creativity, chaos, complexity, nonlinear, emergence, worldview)
As sustainability becomes increasingly important, product design is taking a proactive role in producing products that are both useful and sustainable. This paper introduces and discusses a tool named Environment-based life cycle decomposition (eLCD) to adapt the Environment-based Design (EBD) methodology to sustainable design. The eLCD brings to EBD three major features: 1) a holistic environment structure for sustainable conceptual design, 2) an effective and efficient tool for collecting information for sustainability decision-making, and 3) an analysis tool that takes sustainability as an integral part of the design rather than as a burden. The environment of a product is everything except the product itself, which can be defined in three dimensions, namely, environment types, life cycle events, and life cycle time. The environment types are designated as natural, built (including physical artifact and digital artifact), economic, and social environment. The eLCD provides an effective template for information collection to support the design decision-making process. The effectiveness of eLCD is demonstrated by its application to the upscaling of a wind turbine, where an energy storage system is introduced to make full use of wind energy with the least waste in serving the electricity demand.
This article is an edited version of a Keynote Address provided for the 2021 Creativity Conference hosted by Southern Oregon University. The talk opens with the following question: “What role does our experience with uncertainty play in our creative thoughts and actions?” The remainder of the talk is focused on addressing this question, starting with the assertion that there is no creativity without uncertainty and several other operating assumptions aimed at establishing a basis for this assertion. Next a model of creativity under uncertainty is introduced. The model outlines how encounters with uncertainty in a particular socio-cultural and historical moment can be experienced as epistemologically and ontologically destabilizing, and thereby, result in a state of genuine doubt. This state of doubt, when perceived as actionable, can open-up a horizon of new possibilities for creative activity. The model further outlines how taking creative action in the face of uncertainty can (temporarily) resolve our state of doubt and re-stabilize our experiences. Implications for inviting uncertainty into educational learning environments are also discussed.
We propose a large scalable engineering knowledge base as an integrated knowledge graph, comprising sets of (entity, relationship, entity) triples that are real-world engineering ‘facts’ found in the patent database. We apply a set of rules based on the syntactic and lexical properties of claims in a patent document to extract entities and their associated relationships that are supposedly meaningful from an engineering design perspective. Such a knowledge base is expected to support inferencing, reasoning, recalling in various engineering design tasks. The knowledge base has a greater size and coverage in comparison with the previously used knowledge bases in the engineering design literature.
EEG alpha synchronization, especially in posterior parietal cortical regions of the right hemisphere, is indicative of high internal processing demands that are typically involved in divergent thinking (DT). During the course of DT, as ideation proceeds, ideas tend to become more creative, being more likely to be drawn from new conceptual categories through the use of the cognitive mechanism of flexibility. The present study investigated whether EEG alpha synchronization can be modulated by flexibility in DT by comparing cortical activation patterns during the switch of category (switching) and the stay in the same category (clustering). Twenty participants were required to generate alternative uses of everyday objects during EEG recording. Differential results were specifically found in the lower alpha band (8-10 Hz): whereas clustering showed synchronization typically lateralized in the right posterior parietal areas, switching induced posterior parietal synchronization over both right and left hemispheres. These findings indicate that the two distinct cognitive mechanisms subsuming flexibility (switching and clustering) are associated with a different hemispheric modulation of lower alpha activity, as switching, in comparison to clustering, is related to higher power in the lower alpha band over the left hemisphere. Switching in comparison to clustering may thus require a larger investment of cognitive resources due to the exploratory process of moving from one semantic conceptual category to another in the course of creative ideation.
This paper aims to addresses three questions related to conceptual design: 1) Why is environment important? 2) What is environment? and 3) How to analyze environment? Unlike product-, function (affordance)-, or user-centered methodologies, it is argued that the known environment of a product to be designed must be the first thing to be looked at in a conceptual design. The environment can be categorized into three types: the natural, the built and the human. A complete set of environment for a design is implied in the lifecycle of a product to be designed, which can be further defined by lifecycle activities in terms of time. The analysis of environment consists of three activities: 1) determine decision directions by asking design questions based on a design problem statement; 2) clarify the design problem statement by answering questions following the decision direction; and 3) formulate an environment system from a design problem statement. The process is driven by asking the right questions by analyzing the ROM diagram of the design problem statement. The answers to the questions follow the lifecycle analysis of the product and its environment components. This paper completes a detailed procedure for Environment Analysis, which is the one of the three activities in Environment-Based Design (EBD).
This paper explores the relationship between design logic and reasoning and the methodological and epistemological positioning of design-based knowledge production. Examining the relevant literature, we propose that the naturalistic logic of the American pragmatist philosopher John Dewey offers a potentially useful contextualisation of how logic, reasoning, method and, ultimately, knowledge can be understood as arising from, and be responsive to, context. This is considered in relation to the long-term delivery of a design research programme—termed Experience Labs—which was seen to undergo a gradual methodological shift in response to contextual concerns. It is our core argument that Dewey’s logic can function as a valuable theoretical device, mediating between design and the necessity of methodological and epistemological explication in research.
The study of surprising product features is crucial for designing products that potentially trigger attention and curiosity. Through a tailored questionnaire, this study gathered reactions from 100 respondents to solutions which were considered to be surprising. The data about surprise emergence and its modalities were processed using a situated FBS-based cognitive framework, shifted to the perspective of the user/observer. Data analysis shows that FBS variables and the related cognitive processes are suitable for describing similarities and differences in the reasoning path of users when surprise emerges. This confirms that individually pre-conceived expectations are crucial to surprise emergence and that these expectations relate to functional, behavioural or structural variables with similar mechanisms that depend on thinking processes triggered by product features.
Herbert Simon's classic work on artificial intelligence in the expanded and updated third edition from 1996, with a new introduction by John E. Laird.
Herbert Simon's classic and influential The Sciences of the Artificial declares definitively that there can be a science not only of natural phenomena but also of what is artificial. Exploring the commonalities of artificial systems, including economic systems, the business firm, artificial intelligence, complex engineering projects, and social plans, Simon argues that designed systems are a valid field of study, and he proposes a science of design. For this third edition, originally published in 1996, Simon added new material that takes into account advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action.
Simon won the Nobel Prize for Economics in 1978 for his research into the decision-making process within economic organizations and the Turing Award (considered by some the computer science equivalent to the Nobel) with Allen Newell in 1975 for contributions to artificial intelligence, the psychology of human cognition, and list processing. The Sciences of the Artificial distills the essence of Simon's thought accessibly and coherently. This reissue of the third edition makes a pioneering work available to a new audience.
Fast development of IT and ICT facilitate customers to post a large volume of their concerns and expectation online, which are widely accepted to be a valuable resource for product designers. However, it is found that only a small number of small and medium-sized enterprises (SMEs) have capabilities to leverage customer online insights for design innovation, which often demonstrate a significant share in national economies growth. To discover the beneath reasons regarding the barrier that prevent them to make effective utilization, in this study, as a concrete example, manufacturing SMEs in the South Wales and Greater Manchester industrial areas of the UK are focused and their potential motivations for using and knowledge of big data-based customer analytics are investigated. An exploratory survey was conducted in terms of the type of customer data they have, the storage approaches, the volume of customer data, etc. Next, a carefully devised exploratory study was undertaken to understand how SMEs perceive the relations between customer data and product design, how about their expectations from big customer data analytics and what really challenges SMEs to exploit the value of big customer data. Besides, a demonstration platform is developed to present SMEs an automatic process of analysing customer online reviews and the capacity on customer insights acquisition and strategic decision making. Finally, findings from two focus groups indicate the different managerial and technical considerations required for SMEs considering implementing big data and customer analytics. This study encourages SMEs to welcome big customer data and suggests that a cloud-based approach may be the most appropriate way of giving access to big data analytics techniques.
Knowledge acquisition is a well-acknowledged bottleneck in the building of knowledge-based systems. Documents are a useful source of knowledge from experts. This paper targets the reuse of knowledge from the assembly phase of a product in the design and planning phases. Issues, their causes and the parameters involved are necessary to be acquired for reusing the knowledge so acquired. This paper discusses a method for knowledge acquisition, as a pipeline of existing tools in natural language understanding and processing. The acquired knowledge is expected to help in the decision making for a smart manufacturing system. The process of knowledge acquisition involves recognising the presence of issues and their causes using a combination of sentiment analysis and text patterns. The causes are then dissected to identify the constraints and constituent parameters. These pieces of knowledge are then reconstructed to form rules in a knowledge base. This paper demonstrates progress towards realising the method, by developing the cause dissection and rule-writing components, and validation of the issue-cause acquisition component with human subjects. A discussion is then presented on the potential integration and validation of the overall knowledge acquisition pipeline with a smart manufacturing system.
The construction industry is facing a severe shortage of skilled workforce. Higher education is challenged to develop innovative strategies to help college students develop career-specific competency and accelerate the transition from novice to expert. Technology innovations such as virtual reality (VR) and mixed reality (MR) have been successfully integrated into learning and training programs to create authentic learning experiences within simulated virtual learning environments to facilitate tacit knowledge acquisition and workplace expertise development, which traditionally takes years of empirical experience and apprenticeship training. This study aims to explore potential VR and MR interventions in construction education and workforce development. It is directed at enhancing understanding of key differences between novices and experts and how VR and MR may facilitate tacit knowledge acquisition and expertise development to address the current skills gap in the construction industry. A simulation of accessibility design review and assessment for a tiny house was conducted via VR and MR mock-ups with the participation of both student novices and professional experts to collect behavioral and perceptual data using instruments that included a think-aloud protocol, a pair of pre-and postsurvey questionnaires, and audio/video recordings. Comparative analyses were conducted, and the results indicated that student novices, despite their lack of expertise, demonstrated comparable patterns of behaviors and achieved design review outcomes similar to those of professional experts with the VR and MR mock-ups. The findings of this study contribute to the body of knowledge by providing preliminary evidence of learning affordances of VR and MR in bridging experience-related gaps and suggesting opportunities for accelerating workplace expertise development among college students via technology intervention. These findings also have the potential to inform instructional design and pedagogical approaches that integrate VR and MR technology in undergraduate construction and engineering curricula.
In this chapter we introduce the Dynamic Universal Creativity Process (DUCP), defined as the active ensemble of all creativity episodes in the evolution of our cosmos. It is shown how this construct descends naturally through a shift in the leading perspective in creativity studies: from a focus on static creative achievements to the consideration of dynamic processes, which even transcend their agents. Four mechanisms for the dynamic extension in time and space of creativity episodes are presented: continued exploration, concatenation, estimation, and exaptation. The concepts of wide-sense and strict-sense creativity are introduced to allow the consideration of four layers of existence in the DUCP: material, biological, psycho-social, and artificial. The theoretical and practical implications of these definitions are discussed, also in view of contributing to the mending of the cultural fracture between science and the arts, under the flag of creativity studies. A description of the creativity mechanisms characterizing the material, biological, psycho-social, and artificial layers is provided, highlighting intra- and inter-layer concatenation potential and achievements. Among other concepts, complex systems, biological evolution, bipedalism, neoteny, individual and social mind-based behaviour, as well as artificial intelligence, all find an integrated place in the framework of creativity studies, under the DUCP umbrella. Implications on educational systems of the future are drafted in the final discussion.
The subject of creativity has been neglected by psychologists. The immediate problem has two aspects. (1) How can we discover creative promise in our children and our youth, (2) How can we promote the development of creative personalities. Creative talent cannot be accounted for adequately in terms of I.Q. A new way of thinking about creativity and creative productivity is seen in the factorial conceptions of personality. By application of factor analysis a fruitful exploratory approach can be made. Carefully constructed hypotheses concerning primary abilities will lead to the use of novel types of tests. New factors will be discovered that will provide us with means to select individuals with creative personalities. The properties of primary abilities should be studied to improve educational methods and further their utilization. (PsycINFO Database Record (c) 2012 APA, all rights reserved)