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

109-1 280189 設計思考與資料科學 1 3.0 3 ★ 王聖銘互動所
設計博所 14 0 日,職碩,博班合開/排進修部教室/上限為15人

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
109-1	280189	設計思考與資料科學	1	3.0	3	★	王聖銘	互動所設計博所	14	0	日,職碩,博班合開/排進修部教室/上限為15人

教學大綱與進度：

教師姓名王聖銘

Email ryan5885@gmail.com

最後更新時間 2020-07-19 11:08:04

課程大綱 As the user-center design is becoming the core of most interaction design (IxD), it has become a popular belief that it is no longer the product that leads but users and user preferences that's leading the game. This is where design thinking steps in, where IxD uses their sensibility and methods to match users' need in a way that is technologically feasible and viable enough to generate user value and tap market opportunity. Suggested by some studies, brought in vogue by the popular design firm IDEO, design thinking when combined with decision science results in an infusion of empathy with engineering. This not only ensures a practical and creative resolution of problems but also puts the user at the center of applications and at the starting point to develop new designs and solutions. Meanwhile, ensuring design in analytics projects from the initial stages can lead to the right blend of sensibility, technical feasibility, business viability, and consumer needs. The idea is, design thinking puts user and their needs as the starting point of developing new product and solution and ask questions like for whom are we designing, what is the problem user is experiencing, how to improve the performance and achieve scalability, among others. Data scientist and analyst can make up for great professionals in design thinking, given the right set of tools that is at their disposal. Thus, the main objectives of this course provide: 1. Creating a vital user-centered design process. 2. Work with high-quality data, design artifacts can be created, addressing the needs of the real user. 3. Encourage the student to mix these two together in IxD to reap design benefits and opportunities. The most important objective is to ensure the quality of user-centricity of user experience. 本課程的核心主軸，將利用史丹佛大學d.School所提出設計思考的方法，針對資料科學的關鍵知識進行跨領域的盤點、整理與設計，以創造其具人本設計(Human-Centered Design)的創新價值。本課程將採用專案/問題導向(Project/Problem-Based Learning)的學習與互動模式。因為是跨系選修的課程，將於課堂上組成跨領域的學習團隊，鼓勵跨領域的學生從不同的情境模式，連結「資料探勘」之核心課程。「類神經網路」與「深度學習」的進階課程，及「語音辨識與人機互動」的應用課程等相關內容。並同時應用於探討資料科學有關資料蒐集、建構、過濾、品質驗證、分類處理、模式應用、資料視覺化處理、及分析敘事的核心知識。並於課程操作過程中，透過「資料導向敘事(Data-Driven Storytelling)」的方法，呈現跨領域創新學習的成果。

課程進度 Week01 Development of Human-Centric Artificial Intelligent 1. The basic of AI 2. Value of Human-centered Design) The trend of inter-disciplinary integration and development Week02 Design Thinking and the Values of Data Collecting and Generation 1. The five steps of design thinking 2. Data visualization and innovation Week03 Data Analysis and Story Telling 1. Data, Information and Knowledge generation 2. Case studies and concepts of data-driven storytelling Week04 Exploration on Data-Driven Storytelling Technologies 1. Data-Driven Storytelling 2. The method and structure of Storytelling Week05 Data Processing and Data Visualization Design Data processing and analysis 1. The basic principle of Data visualization 2. Data visualization case studies Week06 Data Science Design Thinking Workshop (I) 1. Define the problems 2. User data analysis 3. Data plan and survey Week07 Data Science Design Thinking Workshop (II) 1. Data list and analysis methods 2. User experience design and analysis 3. The basic and applications of Quality Function Deployment(QFD) method Week08 Industrial Field Trip：Practical Experience and Experiment Week09 Midterm Project Presentation and Review Week10 Design Thinking with Five Design Sheets Week11 Design Thinking World Caf Workshop on midterm project amendment. Week12 Speech：The Integration and Practice of Spatial Analysis and Deep Learning Week13 Co-working with Industrial Domain Experts： Spatial Data Processing and Analysis Week14 Data Science Design Thinking Workshop (III) 1. Persona 2. User Journey Map 3. Service Blueprint Week15 Data Science Design Thinking Workshop (IV) 1. The value-added analysis of innovation (Kano Model) 2. The Honey Comb User Experience Week16 Data Science Design Thinking Project Prototype Demo and Evaluation 1. Prototype function analysis 2. User Experience Analysis 3. Evaluation of Innovation value created Week17 Term Project presentation and Review Week18 Final Report due and Panel Discussion

評量方式與標準 1. Attendance Rate 2. Midterm Report 3. Project Presentation 4. Final Project Report

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：是
1. Data-Driven Storytelling, Edited by Nathalie H. Riche, Christophe Hurter, Nicholas Diakopoulos, and Sheelagh Carpendale, CRC Press, Taylor & Francis, 2018. 2. Five Design-Sheets: Creative Design and Sketching for Computing and Visualization, by Jonathan C. Roberts, Christopher J. Headleand, Panagiotis D. Ritsos, Springer, 2017.

課程諮詢管道

課程對應SDGs指標

備註

教師姓名	王聖銘
Email	ryan5885@gmail.com
最後更新時間	2020-07-19 11:08:04
課程大綱	As the user-center design is becoming the core of most interaction design (IxD), it has become a popular belief that it is no longer the product that leads but users and user preferences that's leading the game. This is where design thinking steps in, where IxD uses their sensibility and methods to match users' need in a way that is technologically feasible and viable enough to generate user value and tap market opportunity. Suggested by some studies, brought in vogue by the popular design firm IDEO, design thinking when combined with decision science results in an infusion of empathy with engineering. This not only ensures a practical and creative resolution of problems but also puts the user at the center of applications and at the starting point to develop new designs and solutions. Meanwhile, ensuring design in analytics projects from the initial stages can lead to the right blend of sensibility, technical feasibility, business viability, and consumer needs. The idea is, design thinking puts user and their needs as the starting point of developing new product and solution and ask questions like for whom are we designing, what is the problem user is experiencing, how to improve the performance and achieve scalability, among others. Data scientist and analyst can make up for great professionals in design thinking, given the right set of tools that is at their disposal. Thus, the main objectives of this course provide: 1. Creating a vital user-centered design process. 2. Work with high-quality data, design artifacts can be created, addressing the needs of the real user. 3. Encourage the student to mix these two together in IxD to reap design benefits and opportunities. The most important objective is to ensure the quality of user-centricity of user experience. 本課程的核心主軸，將利用史丹佛大學d.School所提出設計思考的方法，針對資料科學的關鍵知識進行跨領域的盤點、整理與設計，以創造其具人本設計(Human-Centered Design)的創新價值。本課程將採用專案/問題導向(Project/Problem-Based Learning)的學習與互動模式。因為是跨系選修的課程，將於課堂上組成跨領域的學習團隊，鼓勵跨領域的學生從不同的情境模式，連結「資料探勘」之核心課程。「類神經網路」與「深度學習」的進階課程，及「語音辨識與人機互動」的應用課程等相關內容。並同時應用於探討資料科學有關資料蒐集、建構、過濾、品質驗證、分類處理、模式應用、資料視覺化處理、及分析敘事的核心知識。並於課程操作過程中，透過「資料導向敘事(Data-Driven Storytelling)」的方法，呈現跨領域創新學習的成果。
課程進度	Week01 Development of Human-Centric Artificial Intelligent 1. The basic of AI 2. Value of Human-centered Design) The trend of inter-disciplinary integration and development Week02 Design Thinking and the Values of Data Collecting and Generation 1. The five steps of design thinking 2. Data visualization and innovation Week03 Data Analysis and Story Telling 1. Data, Information and Knowledge generation 2. Case studies and concepts of data-driven storytelling Week04 Exploration on Data-Driven Storytelling Technologies 1. Data-Driven Storytelling 2. The method and structure of Storytelling Week05 Data Processing and Data Visualization Design Data processing and analysis 1. The basic principle of Data visualization 2. Data visualization case studies Week06 Data Science Design Thinking Workshop (I) 1. Define the problems 2. User data analysis 3. Data plan and survey Week07 Data Science Design Thinking Workshop (II) 1. Data list and analysis methods 2. User experience design and analysis 3. The basic and applications of Quality Function Deployment(QFD) method Week08 Industrial Field Trip：Practical Experience and Experiment Week09 Midterm Project Presentation and Review Week10 Design Thinking with Five Design Sheets Week11 Design Thinking World Caf Workshop on midterm project amendment. Week12 Speech：The Integration and Practice of Spatial Analysis and Deep Learning Week13 Co-working with Industrial Domain Experts： Spatial Data Processing and Analysis Week14 Data Science Design Thinking Workshop (III) 1. Persona 2. User Journey Map 3. Service Blueprint Week15 Data Science Design Thinking Workshop (IV) 1. The value-added analysis of innovation (Kano Model) 2. The Honey Comb User Experience Week16 Data Science Design Thinking Project Prototype Demo and Evaluation 1. Prototype function analysis 2. User Experience Analysis 3. Evaluation of Innovation value created Week17 Term Project presentation and Review Week18 Final Report due and Panel Discussion
評量方式與標準	1. Attendance Rate 2. Midterm Report 3. Project Presentation 4. Final Project Report
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：是 1. Data-Driven Storytelling, Edited by Nathalie H. Riche, Christophe Hurter, Nicholas Diakopoulos, and Sheelagh Carpendale, CRC Press, Taylor & Francis, 2018. 2. Five Design-Sheets: Creative Design and Sketching for Computing and Visualization, by Jonathan C. Roberts, Christopher J. Headleand, Panagiotis D. Ritsos, Springer, 2017.
課程諮詢管道
課程對應SDGs指標
備註