MYP Design Curriculum · MYP Year 3

Grade 8

Pivot year. Students move from "using" tools to "building" with code and electronics. First hardware purchases go here — a class kit of micro:bits or Arduino Nano clones lives in the Design classroom for the next three grades. Text-based coding (HTML/CSS, Python) replaces pure block coding as the default.

Unit 1 · Sep–Oct

"Who I Am" v3 — Hand-Coded 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 is HTML, CSS, HTTP? What is the DOM? Conceptual: How do constraints of the medium shape what can be expressed? Debatable: Is a website a document or a building?
Skills / Tools
HTML structure, CSS styling, basic responsive techniques. View-source of real sites. Comparative analysis of portfolio websites. VS Code or an online editor. Git concepts (optional introduction).
AI Integration
AI as code tutor and reference. Students use DeepSeek to: (1) explain HTML and CSS concepts when stuck ("what does display: flex actually do?"), (2) debug broken code by pasting it in and asking what's wrong, (3) suggest CSS for a specific visual effect they want. The rule: students must write the initial version themselves, AI can help fix or explain. Students must be able to verbally explain any code in their final site — teacher spot-checks this. Discussion: AI will sometimes give code that works but uses patterns you haven't learned yet; that's a flag to either learn the pattern or find a simpler way.
Summative Assessment
Hand-coded multi-page personal website + design folder emphasis on A (analysis of 3+ existing personal sites, user needs research, brief) and B (specification, 3 design directions with mockups, justified choice with wireframes) + AI Use Log.
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.
IB compliance

Strand Coverage

Every strand of every criterion is assessed at least twice per year — summatively in the emphasis units (●) and formatively elsewhere (○).

Strand U1 WebsiteU2 ArduinoU3 KioskU4 Python
A.i Explain/justify need
A.ii Prioritize research
A.iii Analyze existing products
A.iv Develop design brief
B.i Design specification
B.ii Range of feasible ideas
B.iii Present/justify chosen design
B.iv Planning drawings/diagrams
C.i Logical plan
C.ii Technical skills
C.iii Follow plan / functioning solution
C.iv Justify changes to plan
D.i Testing methods
D.ii Evaluate against specification
D.iii Explain improvements
D.iv Impact on client/audience