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Adaptive Learning

读取课程网页或本地 PDF 资料，生成 questions.json 题库，再用打包脚本与前端框架产出可离线使用的 HTML/CSS/JS 学习应用；应用内置 FSRS 间隔复习、BKT 掌握度估算、广度/深度两种模式和 KaTeX 公式渲染。

weishuz
weishuz
热度 57.83
最近更新 2026-05-11 17:38:37
分类：知识依赖：代码执行 / 读写文件 / 联网浏览搜索 / 第三方 API / 内部调用大模型应用场景：教学辅导 / 测验 / 模板 / 研究

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add adaptive-learning
Metadata
name
adaptive-learning
description
Create adaptive learning flashcard apps from course materials (URLs, PDFs, or folders). Uses FSRS (Free Spaced Repetition Scheduler) and Bayesian Knowledge Tracing for intelligent review scheduling. Use when asked to create study materials, flashcards, review apps, spaced repetition systems, or adaptive quizzes from course content. Triggers on "make me a study app", "create flashcards for this course", "adaptive learning", "spaced repetition", "review system for [course]".

Adaptive Learning Skill

Create self-contained, browser-based adaptive learning apps from any course material.

Architecture

  • FSRS (ts-fsrs): Per-card spaced repetition scheduling (Stability, Difficulty, Retrievability)
  • BKT: Per-topic Bayesian Knowledge Tracing for mastery estimation
  • Two modes: Breadth-first (cover all topics, weakest first) / Depth-first (drill one topic deep)
  • Pure frontend: HTML + CSS + JS, works offline via file://, no server needed

Workflow

1. Gather Course Material

From a URL:

1. Fetch the course page, extract topic list and resource links
2. Download HW/Discussion/Lecture PDFs to ~/COURSE_NAME/

From a local folder:

1. List files, identify PDFs and documents
2. Read/parse to understand topics and content

2. Generate Question Bank

Create questions.json with this schema:

[{
  "id": "unique-id",
  "topic": "Topic Name",
  "topicIndex": 0,
  "difficulty": 1,
  "question": "Supports $LaTeX$ via KaTeX",
  "answer": "Supports $LaTeX$ and \\n for line breaks",
  "tags": ["tag1", "tag2"]
}]

Guidelines:

  • 5-8 questions per topic minimum, across 3 difficulty levels
  • Difficulty 1 (基础): Definitions, "what is", simple complexity questions
  • Difficulty 2 (中等): Apply algorithms, analyze examples, describe procedures
  • Difficulty 3 (高级): Proofs, novel problem design, optimization, "why" questions
  • Use LaTeX ($...$ inline, $$...$$ block) for math
  • Use \\n for line breaks in question/answer text
  • topicIndex controls topic ordering (0-based)

3. Build the App

Run the bundler script:

bash SKILL_DIR/scripts/generate-course.sh <course-id> <questions.json> <output-dir>

Then register the course in engine.js COURSE_REGISTRY:

{ id: 'course-id', name: 'Course Name', desc: 'Description', school: 'School', term: 'Term' }

4. Verify

Open <output-dir>/index.html in a browser. Verify:

  • Course appears in selector
  • Cards render with KaTeX math
  • Flip/rating/FSRS scheduling works
  • Mode toggle (breadth/depth) works

Framework Files (assets/framework/)

File Purpose
index.html Main page with course selector + learning UI
style.css Dark theme, responsive styles
engine.js FSRS + BKT engine, question selection, state management
ts-fsrs.umd.js FSRS algorithm library (UMD build of ts-fsrs)

Key Features

  • FSRS scheduling: Cards show Stability/Difficulty values; review intervals adapt to performance
  • BKT mastery: Per-topic mastery percentage in progress drawer
  • Configurable: Target retention (70-97%), daily new card limit
  • localStorage: All progress persists across sessions
  • Keyboard shortcuts: Space=flip, 1=Good, 2=Hard, 3=Again, f=follow-up, n=next-topic
  • KaTeX: Full LaTeX math rendering
  • Drag & drop: Import any questions.json directly in the UI
  • Multi-course: One framework, multiple course data packs

Adding to Existing Installation

To add a new course to an existing adaptive-learning setup at ~/adaptive-learning/:

  1. Save questions.json to ~/adaptive-learning/courses/<id>/
  2. Generate preload: bash scripts/generate-course.sh <id> questions.json ~/adaptive-learning/framework/
  3. Add to COURSE_REGISTRY in engine.js