Grade 8
Students move from using digital tools to directing how a product is built. In the personal website unit, students act as designers and project managers: they write a brief, direct AI to write code, test the result, and choose what to improve. Later units extend their work into physical computing, interactive information design, and Python.
Unit 1 · Sep–Oct "Who I Am" v3 — AI-Assisted Personal Website
ABCD - Key Concept
- Communication
- Related Concepts
- Function, Aesthetics
- Global Context
- Personal and Cultural Expression
- Statement of Inquiry
- The web works because form (design) and function (code) cooperate within shared standards.
- Inquiry Questions
- Factual: What belongs in a website project brief? How do you describe a change clearly enough for AI to implement it? Conceptual: How do purpose, audience, and identity shape a website? Debatable: Does adding more features make a website better?
- Skills / Tools
- Define the site's purpose, audience, identity, content, and features. Turn a brief into clear instructions for an AI developer. Save and open website versions, test what changed, and use FIX / ADD / TRY to plan revisions. Improve visual hierarchy and consistency, and remove distractions.
- AI Integration
- Students act as designers and project managers while AI writes the HTML, CSS, and JavaScript. They describe what they want, inspect the result in a browser, identify what works or needs changing, and give specific revision instructions. Students explain their design decisions and judge whether the result serves the brief.
- Summative Assessment
- Personal website developed from a project brief, with handouts documenting experiments, planned changes, and evaluation. Design folder emphasis on A (purpose, audience, research, and brief) and B (requirements, design choices, and justified improvements), with a record of AI use.
- Budget Note
- 0 RMB. Free editors; hosting on GitHub Pages or Netlify (VPN may be needed — have a local fallback plan).
Unit 2 · Nov–Jan First Physical Computing — Micro:bit or Arduino Reaction Timer
ABCD - Key Concept
- Systems
- Related Concepts
- Function, Logic
- Global Context
- Scientific and Technical Innovation
- Statement of Inquiry
- Physical systems are designed by combining hardware components under logical program control.
- Inquiry Questions
- Factual: What is a microcontroller? What is input/output? Conceptual: How does abstraction make complex systems usable? Debatable: Should every student learn to solder?
- Skills / Tools
- micro:bit MakeCode OR Arduino IDE with C-like Arduino language. Breadboard fundamentals. Buttons, LEDs, buzzer, simple sensors. Pair programming. Debugging by elimination.
- AI Integration
- AI as a circuit and code helper. Students use DeepSeek to: (1) explain what a component does ("what's a pull-down resistor and why do I need one?"), (2) debug code from the Arduino IDE (paste error, ask AI to interpret), (3) generate skeleton code from a description ("write Arduino code to blink an LED when a button is pressed") which students then modify. Wiring diagrams are always sketched by hand first. Critical lesson: AI will happily suggest wiring that looks right but destroys components — always verify pin numbers and voltages against the component datasheet.
- Summative Assessment
- Working reaction-timer or dice-simulator device + design folder emphasis on C (wiring diagram, code listing, plan, changes log) and D (measured accuracy / latency tests, evaluation, improvements) + AI Use Log.
- Budget Note
- First hardware purchase. See Part 5 budget plan.
Unit 3 · Feb–Apr "Campus Problem" v3 — Interactive Info Solution
ABCD - Key Concept
- Communities
- Related Concepts
- Communication, Innovation
- Global Context
- Fairness and Development
- Statement of Inquiry
- Communities benefit when designers understand needs before proposing innovative solutions.
- Inquiry Questions
- Factual: What is user research? What is a persona? Conceptual: How do we design for someone unlike ourselves? Debatable: Does an "innovative" solution always beat a conventional one?
- Skills / Tools
- Structured user interviews. Persona building. Affinity mapping. Low-fi then higher-fi mockups in Figma or Penpot. Analysis of existing kiosks / apps solving similar problems. Introduction to the Python / JSONPlaceholder API work (light touch — "what could a real version use?").
- AI Integration
- AI for user research acceleration. Students use DeepSeek or Kimi to: (1) draft structured user interview question banks and refine them, (2) suggest personas based on a user description — students then validate by talking to real users, (3) summarize affinity maps into insight statements. Strong emphasis in this unit: AI personas are hypotheses, not data. After real interviews students compare AI-predicted needs vs actual user needs in the design folder. This is the first unit where the gap between AI speculation and real data is surfaced explicitly.
- Summative Assessment
- Interactive kiosk OR app mockup (clickable prototype in Figma / Penpot) addressing a campus problem + design folder emphasis on A (thorough field research, user interviews, 3+ existing product analysis, design brief) and B (specification with measurable success criteria, 3+ ideas, justified chosen design with full mockup set) + AI Use Log.
- Budget Note
- 0 RMB. Figma has a free education tier; Penpot is open-source and self-hostable if VPN issues arise.
Unit 4 · Apr–Jun Code Meets Data — Python API Project with AI Pair-Programming
ABCD - Key Concept
- Systems
- Related Concepts
- Logic, Resources
- Global Context
- Globalization and Sustainability
- Statement of Inquiry
- Data from global systems can be transformed into useful information through programmed logic, with AI as a pair-programmer.
- Inquiry Questions
- Factual: What is an API? What is JSON? What are AI code suggestions made of? Conceptual: What is the difference between data and information? When should you trust AI code? Debatable: Who owns the data your apps produce? Who owns the code AI writes?
- Skills / Tools
- Python basics (variables, lists, functions, loops). JSONPlaceholder or similar free API. Requests library. Printing formatted output. Reading and interpreting JSON. AI pair-programming workflow: plan → prompt → read → test → modify.
- AI Integration
- This unit centers AI pair-programming explicitly. Students use DeepSeek (which is strong at code) to: (1) plan program structure via conversation before writing, (2) get code suggestions for specific functions, (3) explain unfamiliar library calls, (4) generate test cases. Required workflow: students must (a) write a plan first in their own words, (b) write pseudocode themselves, (c) only then ask AI for actual Python help, (d) type AI code themselves rather than copy-paste, (e) be able to explain every line verbally. Tests must be written without AI. Discussion when it arises: hallucinated library functions and incorrect API syntax — the AI will sometimes invent functions that don't exist.
- Summative Assessment
- Working Python script that fetches and formats real data (e.g., weather for 5 cities, random useful facts, a mock social feed reader) + design folder emphasis on C (flowchart plan, code quality with AI contributions documented, version iteration log) and D (testing for edge cases, evaluation against specification, impact on target user) + expanded AI Use Log.
- Budget Note
- 0 RMB. Python + repl.it or local install.
Every strand of every criterion is assessed at least twice per year — summatively in the emphasis units (●) and formatively elsewhere (○).