1137043480

1137043480 / word-learning-system

Public

An intelligent adaptive vocabulary learning system for Chinese as a Foreign Language (CFL) — built from master's thesis research at Peking University. Features AI-driven personalized learning, SM-2 spaced repetition, and real-time analytics.

adaptive-learning chinese-language education flask language-learning
10
0
100% credibility
Found Mar 19, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

A web-based adaptive system for intermediate Chinese vocabulary learning with personalized paths, spaced repetition reviews, and progress analytics.

How It Works

1
📱 Discover the app

You find this friendly Chinese word learning app and open it on your phone.

2
❓ Quick level check

Answer simple questions about a sample word to see your starting point.

3
🧠 Get your custom plan

The app smartly picks the perfect lessons just for your level and style.

4
📖 Learn words step by step

Study characters, meanings, phrases, and sentences with audio and examples.

5
✏️ Practice with quizzes

Test yourself with fun interactive exercises and helpful feedback.

6
🔄 Smart daily reviews

Get reminders to revisit words right when you need them most.

📈 Celebrate your progress

Watch colorful charts show how much stronger your vocabulary is getting.

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AI-Generated Review

What is word-learning-system?

Word-learning-system delivers a complete web platform for intermediate Chinese vocabulary learning, guiding users from VKS assessments through adaptive modules on characters, words, collocations, and sentences. It handles personalized recommendations, SM-2 spaced repetition reviews, interactive exercises, and real-time analytics dashboards—all powered by a TypeScript Next.js frontend and Python Flask backend. Developers deploy it locally with one-click scripts that auto-generate test data for instant demos.

Why is it gaining traction?

Its research pedigree from Peking University ensures battle-tested adaptive logic that feels smart without complexity, prioritizing urgent reviews before new content based on your patterns. The dashboard shines with mastery heatmaps and efficiency trends you see immediately, plus API endpoints like `/api/adaptive/recommendation/{user_id}` for easy integration. Quick setup via `start_system.sh` skips boilerplate, making it a fast prototype for intelligent adaptive systems.

Who should use this?

Edtech developers prototyping personalized language apps, Chinese CFL instructors customizing vocab trainers with user progress isolation, or UI builders testing Next.js with shadcn components for interactive learning flows. Researchers in spaced repetition or intelligent adaptive systems evaluating real-user data pipelines. Frontend teams exploring TypeScript education tools with backend analytics.

Verdict

Worth forking for edtech experiments—polished prototype with strong docs and test data generators, though 10 stars and 1.0% credibility reflect early maturity. Extend vocab scale for production, but it's production-ready for demos.

(198 words)

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