Learning that Adapts to You
Traditional EdTech often acts as an academic hurdle rather than a learning aid for special education students in unaccommodated settings. Without built-in accessibility, these rigid systems force neurodivergent or physically impaired learners to adapt to the software, frequently causing frustration, task abandonment, and widening performance gaps.
Noggin is a 100% free, open-source web application built to change that. Using real-time adaptive logic and custom AI orchestration, it actively transforms interfaces and lessons to match each student's unique cognitive, sensory, and motor profiles.
Noggin is and always will be free for classrooms, teachers, and parents. If you believe in democratizing accessible education, you can support us in two major ways:
- 🌟 Star this repository to help more educators and special education advocates discover us.
- 🚀 Sign up for Noggin Tutoring Services (COMING SOON) to directly fund our mission of keeping core classroom tools free for everyone.
Noggimigo is our built-in, local Python AI tutor designed specifically for special education workflows.
Unlike standard conversational models that hand out answers, Noggimigo acts as a patient, scaffolded coach. It asks friendly, guiding questions, breaks down complex topics into micro-concepts, and uses clear, encouraging language to help students learn at their own pace without cognitive fatigue.
Noggin is built using a modern, scalable, and highly performant split architecture:
| Layer | Technology | Purpose |
|---|---|---|
| Frontend & App Interface | Next.js (React) + TypeScript | Handles lightning-fast, reactive state modifications and dynamic UI shifts. |
| Database & Auth Engine | Supabase / PostgreSQL | Structured relational schema logging student baselines and active PerformanceLogs. |
| AI Orchestration Layer | Python Serverless Scripts | Low-cost, highly optimized prompt mechanics powering Noggimigo's custom tuning logic. |
- 🔒 AI Assessment Gatekeeper: A mandatory onboarding evaluation game that maps student baselines across speed, input accuracy, and error types before unlocking core content.
- 📈 True Adaptive Pacing: Automated micro-difficulty adjustments that scale based on live input tracking, response velocity, and error patterns.
- 🚫 Zero Sensory Overload: Fluid interface layout transforms that actively minimize cognitive strain, strip complex hovering actions, and completely eliminate flashing animations.
- ♿ WCAG-Compliant Engineering: Native integration for high-contrast color matrices, screen-reader accessibility hooks, and single-tap text-to-speech toggles.
- 📱 Touchscreen Optimized Layouts: Large interactive click and touch targets (minimum 80px) designed natively to accommodate motor challenges on standard classroom tablets.
[1. Gatekeeper] ➔ [2. Profiling] ➔ [3. Database Sync] ➔ [4. Tailored Delivery]
Onboarding assessment Tracks response speeds, Metrics populate the Lessons unlock with fully
game maps student input errors, and sensory student's unique database individualized UI styling
core abilities. triggers dynamically. profile schema. and dynamic AI tracking.
Get your local development environment up and running in under five minutes.
- Node.js (v18 or higher)
- npm or yarn
- A local Python 3.10+ environment (for the Noggimigo module)
# Clone the repository
git clone https://github.com
# Enter the project directory
cd Noggin
# Install production dependencies
npm install
# Spin up the local development server
npm run devWe are actively seeking developers, instructional designers, and special education teachers to expand Noggin's impact.
- 💡 Teachers & Educators: Request specific lesson templates, suggest interface enhancements, or flag gaps via our GitHub Issues tracker.
- 💻 Open Source Developers: Look through our codebase repository tags for bugs, Tailwind configuration refinements, or Supabase schema optimizations.
Distributed entirely under the MIT License. See LICENSE for the complete legal text.