https://youtu.be/1LoJiQ7gzUI?list=TLGGfY_XJum7NJcyNjA4MjAyNQ The Future of Design, Data, and Computational Design Condensed Briefing Summary (≈2000 characters) This lecture, aimed at first-year design students, emphasizes the crucial role of data, coding, and computational design thinking in shaping the future of design. Drawing on professional experience in the data industry, the speaker provides motivation and strategies to prepare for a rapidly evolving era. We live in an age of exploding information where smartphones, the internet, and the metaverse dominate daily life. Future competitors will be younger generations fluent in English, math, and coding. The key material of this era is data—and the ability to collect, process, analyze, and apply it defines competitiveness. For designers, data is now as fundamental as traditional materials like glass or fabric. Just as written language advanced human communication, coding is the next leap. Coding is not just technical know-how but a new problem-solving language. It supports computational thinking, helping designers transform abstract ideas into explicit, actionable processes. Computational thinking means approaching problems like a computer: Decomposition (breaking problems down), Pattern Recognition (finding repeatable structures), Abstraction (focusing on essentials), Algorithm Design (sequences, branching, iteration). This mindset trains designers to convert vague, implicit ideas into structured solutions. Coding empowers designers by: Automating repetitive tasks → more room for creativity. Turning ideas into working prototypes. Allowing optimization of outcomes. Enabling data-driven methodologies. Coding does not replace traditional methods—it complements them, giving designers new tools to expand their practice. Design is a sequence of decisions, and data provides evidence for them. Urban data, image data, and personal data can fuel innovative outcomes. Computational design already impacts architecture, optimization, VR/AR, and motion graphics. Designers with coding skills can collaborate more deeply with engineers and explore new creative directions. Students should start coding with languages relevant to their tools (e.g., JavaScript for After Effects, Python for 3ds Max/Maya). Approaching tools by data type (vector/bitmap, surface/polygon) is more effective than by brand. Math should be reframed as a visualization tool for geometry, not just abstract problem-solving. Online resources and self-learning are essential. Students should pursue what excites them personally, not just socially imposed goals. Failure should be seen as compressed growth, not a dead end. To thrive, designers must: Build unique strengths to raise personal barriers of entry. Connect diverse knowledge and experiences for new insights. Set long-term goals and stay consistent. The lecture stresses that data, coding, and computational design are no longer optional. They are the foundations for future-ready designers to expand beyond traditional roles, pioneer new domains, and create meaningful impact. Students are encouraged to overcome fear, embrace continuous learning, and carve out their own distinctive paths in the evolving landscape of design. 1. Data as the New Material2. Coding as a New Language3. Computational Thinking4. Why Designers Need Coding5. Computational Design – Fusing Data & Design6. Learning Strategies7. Motivation and MentalityConclusion
