1. Read for intent
The Word document supplied the syllabus objective, mathematical language and question evidence. Each item was analysed for the concept, representation and likely misconception it could reveal.
Extension of the number system from real numbers to complex numbers
What is groundbreaking here?
Instead of presenting i as a rule to memorise, the activity makes the historical extension from natural numbers to complex numbers visible as a connected system. Learners move between number sets, algebraic notation and coordinates before they are asked to generalise.
The AI did not merely generate answers. It translated a static assessment document into an instrumented learning progression: learners predict, attempt, receive misconception-specific feedback, open a visual tutorial, retry, and leave semantic evidence that a teacher can inspect.
The six-stage learning journey
- RecogniseIs every integer also a complex number?
- DistinguishHow should zero be classified?
- SimplifyWhat is the real part of 2i + 5i²?
- Interpret notationWhich statement is correct for z = 3 + 4i?
- ClassifyWhere does −3i belong?
- ExplainA number z = a + bi is both real and purely imaginary. What must z be?
From a Word document to an expert learning experience
2. Add a learning-design prompt
Build a six-stage misconception-first journey from nested number sets to a+bi. Require a visible number-system map, exact notation, translation between z and its real and imaginary components, no answer reveal before Check, and a visual tutorial after an attempt.
3. Build for the SLS frame
The payload is self-contained and responsive, with touch targets, keyboard access, read-aloud support, closed overlays on launch and no dependency on a network library.
4. Preserve proven xAPI know-how
The supplied reference ZIP was treated as a contract. lib/xapiwrapper.min.js, lib/xAPI.js and the injected xAPI head block were copied byte-for-byte; only the learning payload was redesigned.
How a teacher can use it
Ask learners to name the smallest number set containing each example, then justify why a new set is needed before introducing i.
- Use stages 1–2 for diagnosis before formal teaching.
- Ask students to narrate what changes in the visual model before they calculate.
- Use the tutorial and retry trail as evidence of self-correction, not just the final score.
- Upload the accompanying ZIP directly as an SLS interactive resource when xAPI evidence is required.
Quality evidence
Every activity was checked at desktop, mobile and narrow-phone sizes; incorrect-feedback, visual-tutorial and correct-retry paths were exercised; and the package validator confirmed six stages, root-level ZIP entries, offline assets and byte-identical xAPI integration.
MathematicsComplex NumbersAI GeneratedSLSNumber Systems