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Journal articles on the topic 'Design models'

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Published: 4 June 2021
Last updated: 5 February 2022

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1

Southgate, D. A. T. "Design models." British Journal of Nutrition 73, no. 1 (January 1995): 1–2. http://dx.doi.org/10.1079/bjn19950003.

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2

Budgen, David. "‘Design models’ from software design methods." Design Studies 16, no. 3 (July 1995): 293–325. http://dx.doi.org/10.1016/0142-694x(95)00001-8.

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3

Beard, Alan N. "Fire models and design." Fire Safety Journal 28, no. 2 (March 1997): 117–38. http://dx.doi.org/10.1016/s0379-7112(96)00082-3.

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4

Hershenson, M. "Models of good design." IEE Review 49, no. 6 (June 1, 2003): 38. http://dx.doi.org/10.1049/ir:20030612.

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5

Rodd, M. G. "Logic models of design." Engineering Applications of Artificial Intelligence 1, no. 4 (December 1988): 335. http://dx.doi.org/10.1016/0952-1976(88)90059-0.

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6

Parkinson, A. "Robust Mechanical Design Using Engineering Models." Journal of Mechanical Design 117, B (June 1, 1995): 48–54. http://dx.doi.org/10.1115/1.2836470.

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This paper examines how engineering models can be used to develop robust designs—designs that can tolerate variation. Variation is defined in terms of tolerances which bracket the expected deviation of model variables and/or parameters. Several methods for robust design are discussed. The method of transmitted variation is explained in detail and illustrated on a linkage design problem and a check valve design problem.
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7

Parkinson, A. "Robust Mechanical Design Using Engineering Models." Journal of Vibration and Acoustics 117, B (June 1, 1995): 48–54. http://dx.doi.org/10.1115/1.2838676.

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This paper examines how engineering models can be used to develop robust designs—designs that can tolerate variation. Variation is defined in terms of tolerances which bracket the expected deviation of model variables and/or parameters. Several methods for robust design are discussed. The method of transmitted variation is explained in detail and illustrated on a linkage design problem and a check valve design problem.
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8

Wijesinha, Manel Cooray, and Andre I. Khuri. "Robust designs for first-order multiple design multivariate models." Communications in Statistics - Theory and Methods 20, no. 9 (January 1991): 2987–99. http://dx.doi.org/10.1080/03610929108830682.

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9

Irbīte, Andra, and Aina Strode. "DESIGN THINKING MODELS IN DESIGN RESEARCH AND EDUCATION." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 4 (May 26, 2016): 488. http://dx.doi.org/10.17770/sie2016vol4.1584.

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Design thinking has become a paradigm that is considered to be useful in solving many problems in different areas: both in development of design projects and outside of traditional design practice. It raises the question - is design thinking understood as a universal methodology in all cases? How it is interpreted in design education? The analysis of theoretical and design related literature indicates different basic and contextual challenges facing design today: increasing scale of social, economic and industrial borders; complexity of environment and systems; requirements in all levels. As specialists and researchers in the field of design have concluded, here are multiple disconnects betweenwhat the graduate design schools are teaching at the level of methods and what skills is already needed. The problems have been found also in interdisciplinary cooperation and research. In the context of design thinking models and problem solving methods, the analysis shows that design education implementers in public higher education institutions in Latvia are ready for local and global challenges.
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10

Park, Inho. "Understanding Complex Design Features via Design Effect Models." Korean Journal of Applied Statistics 28, no. 6 (December 31, 2015): 1217–25. http://dx.doi.org/10.5351/kjas.2015.28.6.1217.

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11

Ruecker, Stan. "Concept models for design practice." Bitácora Urbano Territorial 27, no. 4Esp (December 1, 2017): 11–18. http://dx.doi.org/10.15446/bitacora.v27n4esp.63544.

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Los modelos conceptuales son guías para la vida. Algunos han sido desarrollados y validados en otros campos, y adoptados por los diseñadores para su uso. Los modelos conceptuales sirven para tomar decisiones y actuar, y aquellos validados, hacen que la toma de decisiones y la acción sean más rápidas, eficientes y exitosas. No es necesario que los modelos conceptuales estén completos para ser útiles, pero sí que los elementos que contienen sean relevantes para la actividad a desarrollar y que el modelo sea una representación lo suficientemente precisa para ser predictiva. Sin embargo, el diseño, al igual que muchas otras disciplinas inventivas (la arquitectura, la arquitectura del paisaje, la planificación urbana, la ingeniería, la informática) no se ha ocupado tradicionalmente del desarrollo y la validación de modelos conceptuales más allá de los aplicables a un proyecto único. En este artículo, argumentamos que ha llegado el momento de que las disciplinas inventivas produzcan cada vez más sus propios modelos conceptuales para beneficiar a sus profesionales en diferentes tipos de proyectos, al igual que en otras disciplinas donde la producción del conocimiento es secuencial (gran parte de las ciencias exactas) o agregativa (como en muchas de las humanidades).
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12

Ishibuchi, Hisao. "Design of Understandable Fuzzy Models." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 17, no. 1 (2005): 31–33. http://dx.doi.org/10.3156/jsoft.17.31.

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13

Saidani, M., and D. A. Nethercot. "Detailed design models and connections." Journal of Constructional Steel Research 46, no. 1-3 (April 1998): 252. http://dx.doi.org/10.1016/s0143-974x(98)80027-8.

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14

Akin, Ömer. "Researching Descriptive Models of Design." Automation in Construction 7, no. 2-3 (January 1998): 97–100. http://dx.doi.org/10.1016/s0926-5805(97)80432-3.

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15

Rowan, Stuart J., and Jeremy KM Sanders. "Enzyme models: design and selection." Current Opinion in Chemical Biology 1, no. 4 (December 1997): 483–90. http://dx.doi.org/10.1016/s1367-5931(97)80042-7.

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16

Fjeldstad, Øystein D., and Charles C. Snow. "Business models and organization design." Long Range Planning 51, no. 1 (February 2018): 32–39. http://dx.doi.org/10.1016/j.lrp.2017.07.008.

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17

Schmekel, Hans, and G. Sohlenius. "Functional Models and Design Solutions." CIRP Annals 38, no. 1 (1989): 129–32. http://dx.doi.org/10.1016/s0007-8506(07)62667-5.

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18

JESSOP, ALAN. "MODELS AND DESIGN IN ENGINEERING." Civil Engineering and Environmental Systems 16, no. 1 (March 1999): 1–17. http://dx.doi.org/10.1080/02630259908970248.

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19

Merz, Kenneth M., Gianni De Fabritiis, and Guo-Wei Wei. "Generative Models for Molecular Design." Journal of Chemical Information and Modeling 60, no. 12 (December 28, 2020): 5635–36. http://dx.doi.org/10.1021/acs.jcim.0c01388.

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20

Stewart, Mark G., and Robert E. Melchers. "Checking Models in Structural Design." Journal of Structural Engineering 115, no. 6 (June 1989): 1309–24. http://dx.doi.org/10.1061/(asce)0733-9445(1989)115:6(1309).

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21

McDonnell, Janet. "Descriptive models for interpreting design." Design Studies 18, no. 4 (October 1997): 457–73. http://dx.doi.org/10.1016/s0142-694x(97)00012-4.

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22

Badke-Schaub, Petra, Kristina Lauche, and André Neumann. "Team mental models in design." CoDesign 3, no. 1 (March 2007): 1–3. http://dx.doi.org/10.1080/15710880601170743.

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23

Wintle, Claire. "Models as cross-cultural design." Journal of the History of Collections 27, no. 2 (October 16, 2014): 241–56. http://dx.doi.org/10.1093/jhc/fhu052.

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24

Hoover, Stephen P., James R. Rinderle, and Susan Finger. "Models and abstractions in design." Design Studies 12, no. 4 (October 1991): 237–45. http://dx.doi.org/10.1016/0142-694x(91)90039-y.

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25

Gonçales, Lucian José, Kleinner Farias, Toacy Cavalcante De Oliveira, and Murilo Scholl. "Comparison of Software Design Models." ACM Computing Surveys 52, no. 3 (July 27, 2019): 1–41. http://dx.doi.org/10.1145/3313801.

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26

EMORI, Ichiro. "Scale Models and Engineering Design." Journal of the Society of Mechanical Engineers 91, no. 833 (1988): 303–7. http://dx.doi.org/10.1299/jsmemag.91.833_303.

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27

Karvanen, Juha. "Study Design in Causal Models." Scandinavian Journal of Statistics 42, no. 2 (August 11, 2014): 361–77. http://dx.doi.org/10.1111/sjos.12110.

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28

REITHOFER, J. RACZKOWSKY W. "DESIGN OF CONSISTENT ENTERPRISE MODELS." Cybernetics and Systems 29, no. 5 (July 1998): 525–52. http://dx.doi.org/10.1080/019697298125614.

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29

THOMPSON, G. "Mathematical Models and Engineering Design." Water and Environment Journal 7, no. 1 (February 1993): 18–23. http://dx.doi.org/10.1111/j.1747-6593.1993.tb00805.x.

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30

Volkert, Wynn. "Animal models in radiotracer design." International Journal of Nuclear Medicine and Biology 12, no. 1 (January 1985): 75. http://dx.doi.org/10.1016/0047-0740(85)90020-8.

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31

Magliaro, Susan G., and Neal Shambaugh. "Student Models of Instructional Design." Educational Technology Research and Development 54, no. 1 (February 2006): 83–106. http://dx.doi.org/10.1007/s11423-006-6498-y.

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32

Volkert, Wynn. "Animal models in radiotracer design." International Journal of Applied Radiation and Isotopes 36, no. 2 (February 1985): 173. http://dx.doi.org/10.1016/0020-708x(85)90242-x.

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33

McGree, J. M., and J. A. Eccleston. "Investigating design for survival models." Metrika 72, no. 3 (March 25, 2009): 295–311. http://dx.doi.org/10.1007/s00184-009-0254-3.

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34

Kumar, Muruganandan, and Johnny Wong. "Transaction models for design environments." Journal of Systems and Software 16, no. 3 (November 1991): 219–28. http://dx.doi.org/10.1016/0164-1212(91)90016-y.

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35

Brown, Alan S. "Role Models." Mechanical Engineering 121, no. 07 (July 1, 1999): 44–49. http://dx.doi.org/10.1115/1.1999-jul-1.

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This article focuses on the fact that by inserting digital humans into that virtual world—or stepping into it themselves—engineers have found new ways to test designs for ergonomics, manufacturability, maintainability, safety, and style. The goal, of course, is to design better, higher quality products faster and cheaper by getting everyone from manufacturing and quality through safety and maintenance involved in the process before settling on a design. The approach, called concurrent engineering, has been talked about since the quality revolution in the 1980s. Digital humans provide important insights into the design of production and assembly equipment. By simulating the task with large digital populations, safety engineers can determine before a machine goes into production whether anyone is likely to circumvent its safety features. One way to overcome behavior barriers is to put real people in simulations.
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36

Smoak, Robert A., and Xavier R. Ollat. "Construction of control design models from engineering simulation models." Mathematical and Computer Modelling 14 (1990): 413–17. http://dx.doi.org/10.1016/0895-7177(90)90218-c.

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37

Smith, Thomas J. "The Evolution of Design – Models and Modes." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 440–44. http://dx.doi.org/10.1177/1541931213601099.

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Objective: To address the evolution of design from the perspective of human factors/ergonomics (HF/E), with a focus on the phenomenon of performance-design interaction that supports such evolution. Method: Six different models of design evolution are reviewed, four of which have evident parallels with patterns of natural evolution. Result: All of these models implicitly or explicitly emphasize performance-design interaction as a central HF/E feature of design evolution. Yet the different models also display a distinct lack of consistency insofar as underlying assumptions about exactly how design evolution proceeds. Conclusion: A context specificity interpretation for the latter observation is offered, namely that new designs evoke new patterns of behavior, leading in turn to newer designs, suggesting that design evolution may display more than one trajectory and therefore may conform to more than one model. Application: The critical role of human work in guiding and facilitating the evolution of design is emphasized.
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38

Kobashi, Takanori, Nobukazu Yoshioka, Haruhiko Kaiya, Hironori Washizaki, Takano Okubo, and Yoshiaki Fukazawa. "Validating Security Design Pattern Applications by Testing Design Models." International Journal of Secure Software Engineering 5, no. 4 (October 2014): 1–30. http://dx.doi.org/10.4018/ijsse.2014100101.

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Software developers are not necessarily security experts, confirming potential threats and vulnerabilities at an early stage of the development process (e.g., in the requirement- and design-phase) is insufficient. Additionally, even if designed software considers security at an early stage, whether the software really satisfies the security requirements must be confirmed. To realize secure design, this work proposes an application to validate security patterns using model testing. Its method provides extended security patterns, which include requirement- and design-level patterns as well as a new model testing process using these patterns. After a developer specifies threats and vulnerabilities in the target system during an early stage of development, this method can validate whether the security patterns are properly applied and assess if these vulnerabilities are resolved.
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39

Rowles, C. D., and C. Leckie. "A design automation system using explicit models of design." Engineering Applications of Artificial Intelligence 1, no. 4 (December 1988): 258–68. http://dx.doi.org/10.1016/0952-1976(88)90044-9.

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40

Zhao, Lihuan, Silu Liu, and Xiaoming Zhao. "Big data and digital design models for fashion design." Journal of Engineered Fibers and Fabrics 16 (January 2021): 155892502110190. http://dx.doi.org/10.1177/15589250211019023.

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The demand for fashion, and for virtual fitting and personalized fashion among customers, is changing the design and consumption of fashion. To meet such challenges, fashion design models are being developed based on big data and digitization, in which fashion is designed based on data, virtual fitting, design-support systems, and recommendation systems. This paper reviews the fashion design models proposed in recent years and considers future development directions for fashion design. Using big data and digital processing technologies, fashion designers identify the characteristics of popular fashions in the market, predict fashion trends, and create designs accordingly. The virtual fitting of scanatar, parametric mannequin, or even real human bodies, enables customers to quickly and easily find fashion that best meets their tastes and requirements. On consumer design-support platforms, consumers can freely select styles, colors, materials, and other fashion aspects and view the design output. Furthermore, fashion recommendation systems, guided by fashion design experts, have greatly improved consumer satisfaction with fashion design. Yet, current fashion design systems do not fully consider the performance of textile materials and do not involve functional fashion design, let alone comfort. Such limitations provide directions future research in fashion design.
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41

Torning, Kristian. "A Review of Four Persuasive Design Models." International Journal of Conceptual Structures and Smart Applications 1, no. 2 (July 2013): 17–27. http://dx.doi.org/10.4018/ijcssa.2013070103.

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This paper reviews the emerging persuasive design models by systematically analysing their robustness by employing common design criterions from the tradition of design science i.e., Information Systems (IS), User Centred Design (UCD) and Technology Enhanced Learning (TEL). Light is thus shed on the relation between the persuasive design models that claim to offer advice in regards to persuasion and robust design guidelines from more mature fields of research. The results of this comparison can be used when selecting models for designs, in addition to concurrently serving as an offset for creating new models or improving existing ones.
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42

Yang, Min, Bin Zhang, and Shuguang Huang. "Optimal designs for generalized linear models with multiple design variables." Statistica Sinica 21, no. 3 (June 1, 2011): 1415–30. http://dx.doi.org/10.5705/ss.2009.115.

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43

Biedermann, Stefanie, Holger Dette, and Wei Zhu. "Optimal Designs for Dose–Response Models With Restricted Design Spaces." Journal of the American Statistical Association 101, no. 474 (June 1, 2006): 747–59. http://dx.doi.org/10.1198/016214505000001087.

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44

KAWAKITA, Takeo, and Mai AKAMATSU. "COMPARATIVE ANALYSIS OF THREE MODELS THROUGH EXPERIMENTAL DESIGN : Design models which represent activity Part 1." Journal of Architecture and Planning (Transactions of AIJ) 72, no. 614 (2007): 97–103. http://dx.doi.org/10.3130/aija.72.97_1.

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45

Abilov, Marat, and Jorge Marx Gómez. "Incremental Synchronization of Organizational Models, Requirements Models and Object-oriented Software Design Models." Procedia Technology 16 (2014): 659–66. http://dx.doi.org/10.1016/j.protcy.2014.10.014.

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46

Proença, Joaquin Jose Carvalho. "INNOVATION PROGRAMS MODELS: Design and management." Revista Estudos e Pesquisas em Administração 3, no. 3 (December 31, 2019): 15. http://dx.doi.org/10.30781/repad.v3i3.9243.

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Projetos de inovação podem desenhar, desenvolver e implementar uma abordagem prática e estruturada, com o objetivo de criar um modelo gerencial de inovação. As deficiências nas habilidades de gerenciamento de pequenas empresas (em gestão econômica, financeira ou humana) ou as limitações de recursos não são uma questão de inovação nem o setor o a indústria da empresa. É a falta de processos estruturados que integram inovação de produtos, serviços, processos, marketing e modelos de negócios e, ao mesmo tempo, criam os recursos que capacitam os líderes de negócios a agirem sobre inovação. Os programas de inovação praticados em pequenas empresas enfatizaram o como fazê-lo em duas experiências no Peru e na Colombia. A inovação de produtos e serviços foi baseada em metodologias em quatro eixos; contexto empresarial, aprendizado por imersão, gamificação, lean e design thinking. Embora a inovação do modelo de negócios baseada nos mesmos processos e metodologias exigisse recursos e ferramentas adicionais. Isso pode envolver estrutura de modelos de inovação, ferramentas de desenho de modelos de negócios, rede de valor de parceria, todos focados no contexto de negócios (tendências e tecnologias), usuários como co-criadores de valor, plataformas digitais e ecossistemas.
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47

Ushakova, L. A., and A. G. Kosikov. "Cartographic design of multimeasuring geographic models." Geodesy and Cartography 894, no. 12 (January 20, 2015): 30–38. http://dx.doi.org/10.22389/0016-7126-2014-894-12-30-38.

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48

Twum, Stephen, and Elaine Aspinwall. "Models in design for reliability optimisation." American Journal of Scientific and Industrial Research 4, no. 1 (February 2013): 95–110. http://dx.doi.org/10.5251/ajsir.2013.4.1.95.110.

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49

Ibrahim, Hesham, and Ramin Sedaghati. "Approximate Models for Crashworthiness Design Optimization." International Conference on Applied Mechanics and Mechanical Engineering 14, no. 14 (May 1, 2010): 1–12. http://dx.doi.org/10.21608/amme.2010.37669.

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50

Tepavčević, Bojan. "Design thinking models for architectural education." Journal of Public Space 2, no. 3 (December 9, 2017): 67. http://dx.doi.org/10.5204/jps.v2i3.115.

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<p>Technology advancements have profound impact on design thinking in architecture, professional practice and architectural education. New models of representation, along with computational design thinking and innovative approaches in digital fabrication bring new demands for the rethinking of educational pedagogy for the new generation of architects in the digital age. While learning by making has been deeply rooted in the process of architectural education, digital modes of design, representation and manufacturing reconcile the dual nature of design process that has traditionally oscillated between drawing and making, visual and material. In this paper, the relationship between making process in design-led research and other aspects that challenge architectural education are analyzed and described. Along with emerging trends in this topic, current design-led research position and strategies at some Australasia schools of architecture are presented.</p>
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