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Yayın A proposal for a computational design and ecology based approach to architectural design studio(Springer, 2022-03) Karadağ, Derya; Tüker, ÇetinUsing computational design methods, this study aims to analyze the effects of an integrated design process model on the ecological awareness of architectural students, and on their ability to incorporate ecological issues in their design work. To this end, two studies have been carried out. The first one involves a survey about how ecology-related and computational design courses complement the architectural design studio at different universities in Turkey. The second one, which is the main study of this paper, presents the results of an ecology-based computational design workshop. According to the results of the first study, computer-based design courses in Turkey usually lack the dimension of “computational thinking”, focusing only on computer-aided design tools. Moreover, we have also found out that ecology courses in Turkish architectural education are mostly elective, and hence, have only very indirect connection to the architectural design studio. In the second study, we have demonstrated how incorporating computational thinking into the design process increase students’ awareness of the ecological dimension and their ability to make this dimension an integral part of their projects. The paper concludes by elaborating on the importance of computational methods in architectural education.Yayın AI in architectural education: rethinking studio culture(Atatürk Üniversitesi, 2025-09-20) Karadağ, DeryaThis article examines the pedagogical transformations emerging in architectural education through a conceptual and critical perspective focused on human–AI co-creativity. Co-creativity specifically refers to collaborations between human designers and artificial intelligence, in contrast to broader notions of collaborative creativity. The paper argues that AI functions not merely as a technical instrument, but as a co-creative partner that reshapes studio culture, authorship, and creative work. Drawing on selected studio-based cases, the study explores how AI-supported workflows influence ideation, representation, critique culture, prompt literacy, and ethical reasoning. Thematically, it engages with concepts such as cognitive augmentation and conceptual ambiguity to demonstrate how design pedagogy is evolving in response to intelligent systems. Rather than viewing AI as a generative tool alone, the article positions it as an epistemic and ethical agent that prompts a rethinking of studio environments as cultural and pedagogical spaces. Methodologically, the study adopts a casebased approach, analyzing selected 16 design studios in which AI was integrated into early-stage ideation, feedback sessions, and conceptual development. These cases extent strategies from prompt-driven speculation to hybrid critique practices, revealing a dynamic landscape of experimentation and adaptation. The findings suggest that AI can foster deeper conceptual inquiry, student reflection, and new modalities of authorship and collaboration. Eventually, the study underscores the need for reflexive pedagogical frameworks that integrate AI meaningfully enhancing, rather than displacing, human creativity.Yayın Computational design tools in architectural education(Get It Published, 2018-05) Karadağ, Derya; Bolca, PelinArchitecture is a discipline that continuously produces information through research in the field of education and professional practice. This process of ‘knowledge generation’ is also influenced significantly by the act of developing new technology and digital tools as well as by an interdisciplinary approach to architecture. In the framework of digital technologies, ‘Computational design’ provides an innovative alternative to design researches. This method makes it possible to design innovative forms and building systems based on environmental data and also helps us understand the architectural/historical outcomes within a different perspective by using digital tools. These tools are also useful for obtaining and processing the data gathered from direct and indirect sources. According to architectural design ontology, the cognitive process of design is defined by the interaction between the designer and the phenomenon or artefact that she is working on. This interaction is explained by a loop system consisting of the phases of designer’s perception and her decision of intervention. The loop system can be done in a logical way only if the data is processed correctly in a controllable way by the designer. Computational design methods make it possible to achieve this goal and to control the outcomes by different parameters provided by its dataset. Digital tools influence today’s architecture, from the design process to investigating materials and from collecting environmental data to understanding relevant sources. Thus, this method makes the designer think in a more integrated framework with simulation, visualization and the spatialization of outcomes. The reflection of this interaction in architectural education is inevitable. Besides, in architectural education, analysis-oriented design studies that are compatible with the built and natural environment are essential phases. But, such studies can only be possible with a holistic view. An architectural education based on this method allows us to understand the qualitative and quantitative results of a design process. In other words, such studies in architectural education give the future architects the possibility to design with a holistic view. In short, the aim of this paper is twofold; the first one is to introduce the ‘Computational Design’ as a methodology. And the second one is to investigate the pros and cons of this methodology on the architectural education.Yayın Comparing conventional and AI-aided approaches to architectural visuals: a pedagogical evaluation(Springer, 2025-10-20) Ünal, Faruk Can; Karadağ, Derya; Pitts, Gregory; Sedrez, MayconThe rise of AI in architectural design is changing traditional workflows, especially in tasks related to visualization and the refinement of incomplete architectural visuals. This chapter presents a comparative study between conventional digital editing methods and AI-aided completion tools within the context of architectural education. The aim is to understand how the integration of AI tools influences the process and its outcomes, specifically in terms of efficiency, accuracy, and usability for the production of architectural visuals. The research involves two groups of students completing the same tasks under identical constraints and objectives. The first group manually edits and completes architectural visuals using conventional Photoshop editing tools. The second group utilizes Photoshop Generative Fill tool that automates parts of the image completion process using AI-driven algorithms that generate detailed and contextually refined outputs. A reflexive thematic analysis-driven evaluation framework is employed to assess each group’s results, emphasizing qualitative insights while incorporating quantitative user ratings for complementary analysis. This comparative study explores how these tools impact students’ learning, creative decision-making, and ability to tackle complex real-world design challenges. By examining the outcomes of this pedagogical experiment, the study contributes to ongoing discussions about the role of AI in architectural education and practice.
