How narendraprasadrn/neuro_edtech_learning_app works
Neuro EdTech is a cognitive-state-adaptive learning app combining a React experience, a Node API, JavaScript state inference, and a Python learning companion. The principal documented workflow is that a learner enters the Learning Zone, interacts with learning/chat features, and receives content and UI adapted to cognitive state. The backend proxies prediction requests to the ML server and chat or content-processing requests to the chatbot. The README documents real-time state updates and interactive learning; sampled code confirms API routes and selected UI behavior, but not all frontend-to-API wiring, so uncertain links are omitted.
Main entry points: App.tsx App shell · LearningZone.tsx Learning Zone · index.js API gateway · train_soft.js Soft-label trainer
Components 15
Learner experience
- App shell
myapp/Frontend/src/App.tsx - Learning Zone
myapp/Frontend/src/components/LearningZone.tsx - Dashboard
myapp/Frontend/src/components/Dashboard.tsx - Store
myapp/Frontend/src/components/Store.tsx - Avatar UI
myapp/Frontend/src/components/Avatar.tsx - Learning activities
myapp/Frontend/src/components/interventions/MiniGameModal.tsx
Application API
- API gateway
myapp/backend/index.js
Cognitive inference
- Inference server
myapp/ML/ml_server.js - Soft-label trainer
myapp/ML/train_soft.js - EEG data generator
myapp/ML/balanced_soft.js
AI companion
- Chatbot API
myapp/CHATBOT___/chat_api.py - Chat and content core
myapp/CHATBOT___/core.py
Other components
- Learner
- Generative AI
- Browser storage
Connections 14
- Learner → App shell: uses
- App shell → Learning Zone: renders
- App shell → Dashboard: renders
- App shell → Store: renders
- App shell → Avatar UI: renders
- App shell → Browser storage: persists profile
- Learning Zone → API gateway: uploads files
- Learning Zone → Learning activities: offers activities
- API gateway → Chatbot API: forwards requests
- Chatbot API → Chat and content core: calls
- Chat and content core → Generative AI: generates responses
- API gateway → Inference server: forwards predictions
- EEG data generator → Soft-label trainer: provides training data
- Soft-label trainer → Inference server: produces model