03 Bina Bilgi Modelleme İle Erken Tasarım Aşamasında Karar Verme Süreçlerinin Sürdürülebilirlik Bağlamında Değerlendirilmesi Keywords: Collective Intelligence, Design Education, Cartography, Public Space. Research Article Received: 01.07.2022 Accepted: 08.09.2022 Corresponding Author: aheyik@yildiz.edu.tr Heyik, M. A. & Erdoğan, M. (2022). Collective intelligence model for design studio. JCoDe: Journal of Computational Design, 3(2), 27-58. https://doi.org/10.53710/jcode.1138 820 27 Collective Intelligence Model for Design Studio Muhammet Ali Heyik 1 , Meral Erdoğan 2 ORCID NO: 0000-0002-7008-2721 1 , 0000-0003-1537-9351 2 JCoDe | Vol 3 No 2 | September 2022 | Design Studios and Computation| Heyik M. A., Erdoğan, M. While current literature has addressed significant potential of collective intelligence (CI) for collaboration, social learning, decision-making, prediction, knowledge sharing, and distributed problem-solving, there is a lack of research on how effective CI models can be generated for diverse and complex tasks within different contexts of design studios. The pandemic period, in which the institutional infrastructure, educators, and students in architectural education underwent a rapid adaptation, has brought the patterns of the recent past which seem impossible back up for discussion. This research aims to develop a CI model and improve the design process against the main difficulties, especially, in the online and hybrid learning ecosystem. To explore and illustrate how interactions take place in diverse studio contexts, three modules have been created through the consecutive design phases. This study was conducted to understand the significant differentiations and effects according to key factors and attributes that are intrinsically connected with methodological reflections and to explore the role of the CI model on strengthening architectural education. The methodology is comprised of the development and integration of modules, elaborating factors for design studios, and measuring their effects through six experimental studies with the participation of students. Here, cartography-based platforms provide collaboration in module 1 (field study), the interaction among groups in module 2 (design proposals), and consensus in module 3 (user participation). The study integrated and tested CI modules and cartography-based platforms in different contexts (online & hybrid education, urban & rural context, synchronous & asynchronous tools, etc.) to tease out different aspects of their adaptability. The research results based on the process, outputs, and participant experiences reveal the significant effects of the CI modules. Each module has the potential to turn crisis conditions into opportunities, especially during the pandemic period, but also has limitations. On the other hand, the identified limitations such as individualism among students, digital competency, or usability of platforms’ interfaces can be eliminated through ongoing experimental applications. But first of all, like the pandemic period, actual demands from practice will be decisive. To employ holistically from the CI model in the design studio, the experimental practices must be repeated in different contexts through the key factors (group size, task diversity, the usability of tools, pedagogical perspectives, etc.) related to productive, interactive, and systematic design process. The paper contributes a practical model of CI in design education. 1, 2 Yıldız Technical University, Faculty of Architecture, Department of Architecture, Istanbul, Turkey