Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	357330	Case Study of Innovation Service	1	3.0	3	★	Sheng Ming Wang	GIMD IDI	6	0	Joint class for Daytime Master’s and International Master’s students. PBL classroom; limited to 40 students.

Course Plan：

Instructor	Sheng Ming Wang　Office Hours
Email	ryan5885@gmail.com
Last Updated	2025-12-19 01:08:00
Course Objective	This course explores the intersection of service design thinking and advanced technology through the rigorous lens of case study analysis. Students will move beyond surface-level observation to deconstruct complex service ecosystems. The curriculum focuses on how emerging technologies—specifically AI, VR, and advanced HCI—are reshaping services in critical sectors such as elderly healthcare, smart living, and education. By the end of the course, students will possess the analytical tools to evaluate existing services and the creative framework to propose innovative, human-centered service solutions. By the completion of this course, students will be able to: 1. Master Case Study Methodology: Apply rigorous qualitative and quantitative methods to dissect service models, identifying core value propositions and operational flows. 2. Apply Service Design Principles: Utilize tools such as service blueprints, stakeholder maps, and customer journey maps to visualize and improve service experiences. 3. Critically Evaluate Technology: Assess the ethical, practical, and experiential impact of AI, VR, and IoT in real-world service scenarios. 4. Innovate: Synthesize analysis and theory to propose a redesign or a completely new service model for a complex societal challenge.
Course Schedule	Phase I. Principles of Case Study Analysis 1, Methodology: Introduction to Robert K. Yin’s and Stake’s approaches to case study research. 2. Data Triangulation: Combining interviews, observations, and artifact analysis. 3. Deconstruction: How to reverse-engineer a service to understand its backend logic and frontend experience. Phase II. Service Design Principles 1. The 5 Principles of Service Design: User-centered, Co-creative, Sequencing, Evidencing, and Holistic. 2. Systemic Thinking: Understanding services as living ecosystems rather than static products. 3. Touchpoint Orchestration: Aligning digital and physical interactions. Phase III. Advanced Application Domains (Thematic Deep Dives) 1. AI in Elderly Healthcare: Predictive monitoring, companion robots, and ethical data usage. 2. Smart Living: Ambient intelligence, IoT ecosystems, and seamless home automation. 3. HCI & VR: Immersive training, therapeutic VR, and novel interaction modalities. 4. Education: Personalized AI tutors, gamified learning platforms, and hybrid classrooms.
Evaluation and grading policy	Attendance 10% Workshop Participation 10% Midterm Presentation and Report 30% Term Project/Paper 40% Rubric: Case Analysis, Application of Service Design, Innovation & Tech Integration, Communication & Presentation KWL+SIFR Personal Report 10%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes 1. Case Study Methodology Essential Book: Yin, Robert K. (2018). Case Study Research and Applications: Design and Methods (6th Edition). SAGE Publications. Why: The gold standard for case study research. Focus on Chapter 2 (Designing Case Studies) for the distinction between single vs. multiple-case designs. Academic Paper: Flyvbjerg, B. (2006). "Five Misunderstandings About Case-Study Research." Qualitative Inquiry, 12(2), 219-245. Why: Critical for postgraduate students to defend the validity of qualitative case studies against quantitative criticism. 2. Service Design Principles Essential Book: Stickdorn, M., et al. (2018). This Is Service Design Doing: Applying Service Design Thinking in the Real World. O'Reilly Media. Why: It provides the practical "How-to" for Blueprints and Journey Maps. Framework: The Double Diamond Design Process (Design Council UK). Why: A standard industry framework to help students structure their innovation projects (Discover, Define, Develop, Deliver). II. Thematic Deep Dives (Weeks 5-9) Topic 1: AI in Elderly Healthcare Academic Readings: Paper: Khadraoui, et al. (2025). "Exploring Older Adults' Perspectives and Acceptance of AI-Driven Health Technologies: Qualitative Study." JMIR Aging. Key Concept: Analyzing the "resistance" factor—why elderly users reject technically superior solutions due to lack of trust or human touch. Paper: Moyle, W., et al. "Socially Assistive Robots for People with Dementia: A Systematic Review." Key Concept: Ethical considerations of "deception" in care (e.g., is it ethical for a patient to believe a robot loves them?). Real-World Case Examples: Case A: Paro the Therapeutic Seal Service Model: Non-pharmacological therapy. Analysis Point: How a "low-tech" looking AI (zoomorphic design) bypasses the uncanny valley to provide emotional support. Case B: StoriiCare (Care Management Software) Service Model: B2B platform for care homes that connects staff, families, and residents. Analysis Point: How AI aids "invisible care" (backend logic) by predicting falls or health declines before they happen, changing the service flow from reactive to proactive. Topic 2: Smart Living & IoT Academic Readings: Paper: Harper, R. "The Connected Home: The Future of Domestic Life." (Reviewing how "smart" homes often fail due to social friction rather than technical failure). Paper: Strengers, Y. "Smart Energy Technologies in Everyday Life." Real-World Case Examples: Case A: Songdo International Business District (South Korea) Service Model: Ubiquitous City (U-City). Analysis Point: A macro-level service design case. Analyze the friction between "efficient data collection" (waste disposal, traffic) and "lived human experience" (privacy, community feeling). Case B: Amazon Sidewalk / Ring Ecosystem Service Model: Neighborhood-as-a-Service. Analysis Point: How individual product purchases (doorbells) transform into a community surveillance service, and the ethical design implications of "opt-out" models. Topic 3: Advanced Human-Computer Interaction (HCI) Academic Readings: Paper: Ishii, H., & Ullmer, B. "Tangible Bits: Towards Seamless Interfaces between People, Bits and Atoms." Key Concept: Moving UI beyond the screen—critical for designing services for the elderly or visually impaired. Paper: Amershi, S., et al. "Guidelines for Human-AI Interaction." (Microsoft Research). Key Concept: The specific 18 guidelines for designing services where AI is a partner, not just a tool. Real-World Case Examples: Case A: Google Project Jacquard (Levi's Commuter Trucker Jacket) Service Model: Wearable ambient computing. Analysis Point: &quo
The access to curricular consultation	1. Use the course social platform for a quick consultation. 2. Send an email for a setup time slot for consultation during or not during the announced office hours. email: ryan5885@mail.ntut.edu.tw
The course corresponds to the SDGs	SDG3：良好健康和福祉（Good Health and Well-being） SDG4：優質教育（Quality Education） SDG11：永續城市與社區（Sustainable Cities and Communities）
Does the course incorporate 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）
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