Design principles
- Each week combines concepts, demonstration, hands-on practice, and reflection.
- Each week includes a concrete deliverable so learners build personal templates and workflows.
- The later part of the course expands into projects and governance rather than stopping at tool use.
Sourcebook capability arc
- Weeks 1 to 2: reframe AI, identify the real problem, and learn how to ask better.
- Weeks 3 to 4: decompose tasks and place AI into realistic teaching situations.
- Weeks 5 to 7: extend the course into research, workflows, and interactive services.
- Week 8: emphasize validation, judgment, governance, and final presentation.
Source Mapping
Chapter-to-week alignment
The teaching plan now aligns more explicitly with AI時代，我與它的對話 and CH1 to CH7.
CH4 + Introduction
Supports Week 1
Technology shifts, generative AI foundations, multimodal logic, and human-AI collaboration.
Prompt Engineering Chapters
Supports Week 2
Roles, few-shot prompting, chain-of-thought reasoning, system instructions, and vibe coding.
Workspace / NotebookLM / Gemini
Supports Week 3
Tool choice expands into source handling, summarization, and platform integration differences.
CH1, CH3, CH5, CH6
Support Weeks 6-7
GAS, Google Sheets, Sites, LINE Bot, Gemini API, and AI agent integration.
Week 1
Generative AI and human-AI collaboration
Focus: what AI is, where it helps, and where it fails.
Deliverable: a short reflection and personal AI use map.
Related unit: Unit 1
Week 2
Prompt design and dialogue strategy
Focus: roles, tasks, constraints, and output format.
Deliverable: reusable prompt templates.
Related unit: Unit 2
Week 3
Choosing platforms and tools
Focus: matching tools to tasks and contexts.
Deliverable: a comparative tool guide.
Related unit: Unit 3
Week 4
AI in instructional design
Focus: lesson planning, materials, feedback, and classroom support.
Deliverable: an AI-enhanced lesson design.
Related unit: Unit 4
Week 5
AI for academic research
Focus: literature organization, question framing, and writing support.
Deliverable: a research workflow brief.
Related unit: Unit 5
Week 6
Workflow and cloud integration
Focus: turning repeated work into structured AI-enabled processes.
Deliverable: a workflow blueprint.
Related unit: Unit 6
Week 7
Agents, bots, and service design
Focus: service entry points, logic, boundaries, and fallback paths.
Deliverable: an interactive service concept.
Related unit: Unit 7
Week 8
Ethics, governance, and presentation
Focus: quality, safety, documentation, and responsible publication.
Deliverable: a final presentation with an AI use statement.
Related unit: Unit 8
Suggested assessment
| Category | Weight | Notes |
|---|---|---|
| Participation and in-class practice | 25% | Includes activities, discussion, and peer feedback. |
| Weekly tasks | 35% | Checks whether learners can turn AI use into concrete outputs. |
| Final project | 30% | Encourages solutions grounded in real teaching, research, or workplace needs. |
| Reflection on AI use | 10% | Assesses judgment, ethics, and awareness of limits. |
