Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 345157 Data-informed Design Thinking 1 3.0 3 ★ Ching-I Chen GID 11 0 上限15人

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	345157	Data-informed Design Thinking	1	3.0	3	★	Ching-I Chen	GID	11	0	上限15人

Course Plan：

Instructor Ching-I Chen　Office Hours

Email cic@ntut.edu.tw

Last Updated 2024-12-13 13:33:16

Course Objective 「數據啟發設計思考（Data-informed Design Thinking）」課程旨在結合數據分析與設計思考，通過實踐項目提升學生在現代設計環境中的問題解決能力。本課程將引導學生掌握如何從數據中提取關鍵洞察，並結合設計思考中的使用者需求、創意思考與解決方案原型的開發。學生將學習如何有效地應用數據，來支持設計決策與創新。課程以 Project-Based Learning 為教學模式，學生將在實際設計項目中探索如何將數據與設計思考相結合，最終交付一個完整的數據驅動設計解決方案與數據視覺化。課程將以臺北市選定的社區為研究場域，透過交通數據、人流分析、空間設計及環境相關數據，探索都市社區面臨的挑戰，並提出創新且實際的解決方案。學生將學習如何運用數據驅動的設計方法，發展出具未來性與可行性的設計概念，並與專家及業界代表交流。 The "Data-informed Design Thinking" course aims to combine data analysis and design thinking to improve students' problem-solving abilities in modern design environments through practical projects. This course will guide students in how to extract key insights from data, combining user needs, creative thinking and solution prototype development in design thinking. Students will learn how to effectively apply data to support design decisions and innovation. The course uses Project-Based Learning as the teaching model. Students will explore how to combine data with design thinking in actual design projects, and ultimately deliver a complete data-driven design solution and data visualization. The course will use selected communities in Taipei City as the research site. Through traffic data, people flow analysis, spatial design and environment-related data, it will explore the challenges faced by urban communities and propose innovative and practical solutions. Students will learn how to use data-driven design methods to develop futuristic and feasible design concepts, and communicate with experts and industry representatives.

Course Schedule Week 01: Course Introduction 課程介紹 Week 02: Field introduction and data types 場域介紹與數據類型 Week 03: Grouping and topic selection and discussion 分組與主題選擇與討論 Week 04: Data-informed design thinking 數據啟發設計思考 Week 05-08: Design Studio: Design concept development & familiarity with tool platform 設計概念發展 & 熟悉工具平台 Week 09: Midterm Report: Special project report Week 10-15: Design Studio: Project Implementation 專題實作 Week 16: Presentation I: Implementation status report 執行現況報告 Week 17: Group Discussion & Fine-tune 小組討論與調整 Week 18: Final presentation 期末報告

Evaluation and grading policy Midterm report: 30% Class Assignment: 20% Final Project: 45% Attendance: 5%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
自編教材

The access to curricular consultation Mail: cic@mail.ntut.edu.tw
Website: http://cic-lab.design

The course corresponds to the SDGs SDG4：優質教育（Quality Education）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
SDG11：永續城市與社區（Sustainable Cities and Communities）

Note
本課程與城市科學實驗室 (City Science Lab) 合作。

Instructor	Ching-I Chen　Office Hours
Email	cic@ntut.edu.tw
Last Updated	2024-12-13 13:33:16
Course Objective	「數據啟發設計思考（Data-informed Design Thinking）」課程旨在結合數據分析與設計思考，通過實踐項目提升學生在現代設計環境中的問題解決能力。本課程將引導學生掌握如何從數據中提取關鍵洞察，並結合設計思考中的使用者需求、創意思考與解決方案原型的開發。學生將學習如何有效地應用數據，來支持設計決策與創新。課程以 Project-Based Learning 為教學模式，學生將在實際設計項目中探索如何將數據與設計思考相結合，最終交付一個完整的數據驅動設計解決方案與數據視覺化。課程將以臺北市選定的社區為研究場域，透過交通數據、人流分析、空間設計及環境相關數據，探索都市社區面臨的挑戰，並提出創新且實際的解決方案。學生將學習如何運用數據驅動的設計方法，發展出具未來性與可行性的設計概念，並與專家及業界代表交流。 The "Data-informed Design Thinking" course aims to combine data analysis and design thinking to improve students' problem-solving abilities in modern design environments through practical projects. This course will guide students in how to extract key insights from data, combining user needs, creative thinking and solution prototype development in design thinking. Students will learn how to effectively apply data to support design decisions and innovation. The course uses Project-Based Learning as the teaching model. Students will explore how to combine data with design thinking in actual design projects, and ultimately deliver a complete data-driven design solution and data visualization. The course will use selected communities in Taipei City as the research site. Through traffic data, people flow analysis, spatial design and environment-related data, it will explore the challenges faced by urban communities and propose innovative and practical solutions. Students will learn how to use data-driven design methods to develop futuristic and feasible design concepts, and communicate with experts and industry representatives.
Course Schedule	Week 01: Course Introduction 課程介紹 Week 02: Field introduction and data types 場域介紹與數據類型 Week 03: Grouping and topic selection and discussion 分組與主題選擇與討論 Week 04: Data-informed design thinking 數據啟發設計思考 Week 05-08: Design Studio: Design concept development & familiarity with tool platform 設計概念發展 & 熟悉工具平台 Week 09: Midterm Report: Special project report Week 10-15: Design Studio: Project Implementation 專題實作 Week 16: Presentation I: Implementation status report 執行現況報告 Week 17: Group Discussion & Fine-tune 小組討論與調整 Week 18: Final presentation 期末報告
Evaluation and grading policy	Midterm report: 30% Class Assignment: 20% Final Project: 45% Attendance: 5%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No 自編教材
The access to curricular consultation	Mail: cic@mail.ntut.edu.tw Website: http://cic-lab.design
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG11：永續城市與社區（Sustainable Cities and Communities）
Note	本課程與城市科學實驗室 (City Science Lab) 合作。