Layer 1: Capability engine
Mathematical mastery calculation and prerequisite relationships.
Learning decisions
Understand automated decision-making (ADM), explore an example and request a human review.
Scoring, mastery and progression are determined by server-side rules. AI can explain an idea or offer a hint, but it cannot award mastery, grant progression or override a decision.
How decisions are made
The Five-Layer Architecture separates authoritative learning rules from AI assistance. This page supports transparency and review under the Australian Privacy Act.
Layer 2: Pedagogy configuration
Teaching strategies, scaffolding and progression rules.
Layer 3: Content and scoring
Versioned lessons and deterministic scoring rules.
Layer 4: Presentation
Reading level, vocabulary and visual preferences.
Layer 5: AI assistance
Non-authoritative hints, explanations and feedback. AI does not score answers or grant access to learning content.
Explore an example
These illustrative calculations do not represent a learner result. Changing the inputs does not update any learning record or grant access to content.
1 to 10. Use arrow keys, select a position on the track, or use the decrease and increase buttons.
0 to 4. Use arrow keys, select a position on the track, or use the decrease and increase buttons.
1 to 10. Use arrow keys, select a position on the track, or use the decrease and increase buttons.
Example formula:Mastery = min(1.0, (Correct / Attempts) × (0.8 + 0.04 × DifficultyBand))
Example result
- Raw accuracy
- 75.0%
- Difficulty scaling
- 1.00×
In this example, 3 of 4 answers are correct at difficulty band 5. The formula produces the result shown above.
Request human review
Ask for a review of an automated scoring, mastery or progression decision. Required fields are labelled “required”. You can also contact info@fornito.com.