查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

115-1 366071 數據啟發設計思考 1 3.0 3 ★ 陳靜儀創新所 15 0 　

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
115-1	366071	數據啟發設計思考	1	3.0	3	★	陳靜儀	創新所	15	0

教學大綱與進度：

教師姓名陳靜儀

Email cic@ntut.edu.tw

最後更新時間 2026-06-03 16:19:19

課程大綱 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 open 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. 「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，透過開放數據，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啟發的設計方法，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。

課程進度 Week 01: Course Introduction 課程介紹 Week 02: Data-Informed Design Thinking and Types of Data Visualization 數據啟發設計思考與視覺化類型 Week 03: Introduction to the Design Context, Open Data Platforms, Topic Selection and Discussion; Team Formation 介紹場域、開放數據平台、以及主題選擇與討論；分組 Week 04: Design Concept Development and Familiarization with Visualization Tools and Platforms 設計概念發展 & 熟悉工具平台 Week 05: Urban Dynamic Data Visualization I 都市動態資料視覺化 I Week 06: Urban Dynamic Data Visualization II 都市動態資料視覺化 II Week 07: Field Trip – Visit to the City Science Lab @ Taipei Tech 校外教學－參觀城市科學實驗室 Week 08: Field Research and Site Investigation 場域田野調查（校外） Week 09: Progress Review Presentation I 第一次執行現況報告 Week 10-13: Design Studio – Team Project Development 小組專題實作 Week 14: Progress Review Presentation II 第二次執行現況報告 Week 15: Team Discussion, Refinement, and Iteration 小組討論與調整 Week 16: Final Project Presentation 期末報告 Week 17-18: Video / Short Production 製作成品宣傳影片 3-5 分鐘以及 30秒短影音，並上傳至指定空間。

評量方式與標準 Midterm report: 25% Class Assignment: 20% Final Project: 40% Video: 10% Attendance: 5%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：否
自編教材

課程諮詢管道 cic@mail.ntut.edu.tw

延伸教學與資源 ● 數位科技融入 (Digital Technology Integration)
運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。
Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
● 數位教材資源應用 (Application of Digital Resources)
採用影音多媒體或具開放授權之資源（如OCW、開放教科書）作為主要或輔助教材。
Adopts multimedia or open-licensed resources (e.g., OCW, Open Textbooks) as primary or supplementary teaching materials.
● 參與式創新教學 (Participatory & Innovative Teaching)
強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。
Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.

課程對應SDGs指標 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）

課程是否導入AI ● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process）
● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction）
● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）

備註　

教師姓名	陳靜儀
Email	cic@ntut.edu.tw
最後更新時間	2026-06-03 16:19:19
課程大綱	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 open 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. 「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，透過開放數據，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啟發的設計方法，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。
課程進度	Week 01: Course Introduction 課程介紹 Week 02: Data-Informed Design Thinking and Types of Data Visualization 數據啟發設計思考與視覺化類型 Week 03: Introduction to the Design Context, Open Data Platforms, Topic Selection and Discussion; Team Formation 介紹場域、開放數據平台、以及主題選擇與討論；分組 Week 04: Design Concept Development and Familiarization with Visualization Tools and Platforms 設計概念發展 & 熟悉工具平台 Week 05: Urban Dynamic Data Visualization I 都市動態資料視覺化 I Week 06: Urban Dynamic Data Visualization II 都市動態資料視覺化 II Week 07: Field Trip – Visit to the City Science Lab @ Taipei Tech 校外教學－參觀城市科學實驗室 Week 08: Field Research and Site Investigation 場域田野調查（校外） Week 09: Progress Review Presentation I 第一次執行現況報告 Week 10-13: Design Studio – Team Project Development 小組專題實作 Week 14: Progress Review Presentation II 第二次執行現況報告 Week 15: Team Discussion, Refinement, and Iteration 小組討論與調整 Week 16: Final Project Presentation 期末報告 Week 17-18: Video / Short Production 製作成品宣傳影片 3-5 分鐘以及 30秒短影音，並上傳至指定空間。
評量方式與標準	Midterm report: 25% Class Assignment: 20% Final Project: 40% Video: 10% Attendance: 5%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：否自編教材
課程諮詢管道	cic@mail.ntut.edu.tw
延伸教學與資源	● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment. ● 數位教材資源應用 (Application of Digital Resources) 採用影音多媒體或具開放授權之資源（如OCW、開放教科書）作為主要或輔助教材。 Adopts multimedia or open-licensed resources (e.g., OCW, Open Textbooks) as primary or supplementary teaching materials. ● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.
課程對應SDGs指標	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）
課程是否導入AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 使用生成式AI進行課堂即時互動（Use generative AI for real-time classroom interaction） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
備註