learning-method

Deliver adaptive module-based tutoring with quizzes and exercises for ADHD learners.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/oskar-dragon/claude-code --skill learning-method
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: learning-method
Source: https://github.com/oskar-dragon/claude-code/tree/main/plugins/tutor/skills/learning-method
Command: npx skills add https://github.com/oskar-dragon/claude-code --skill learning-method

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Delivers concise, module-based tutoring tailored for inattentive ADHD learners in tutor-initialized projects, preventing long, unfocused explanations and reducing frustration by using short lessons, scaffolded exercises, and immediate factual feedback.

Core Features & Use Cases

  • Linear progressive module flow with strict Concept → See It → Do It → conditional Check It → Connect steps to build a real project incrementally.
  • Adaptive quiz system with rotated formats, metacognitive confidence ratings, and spacing decisions driven by prior performance recorded in auto memory.
  • Integration points for course-outline.md, .claude/tutor.local.md for bridging prior knowledge, and an exercise-verifier agent to validate learner work.
  • Use case: run hour-long, 4-5 module sessions where each exercise adds real functionality to the learner's project and low-confidence topics are woven into subsequent modules.

Quick Start

Start a session by asking the tutor to teach the next module from course-outline.md for an inattentive ADHD learner and verify exercises with the exercise-verifier.

Frequently Asked Questions about learning-method

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up adaptive tutoring for inattentive ADHD learners?▼

Adaptive tutoring for inattentive ADHD learners uses module-based sessions with concise explanations, runnable examples, and scaffolded exercises. You initialize a repository with a course outline and local tutor configuration to start delivering short, focused lessons.

What is the best way to track learning progress and apply spaced repetition?▼

Progress tracking and spaced repetition are handled by recording quiz performance and metacognitive confidence ratings in auto memory. The tutor uses this data to weave low-confidence topics into subsequent modules, driving spacing decisions.

How do I structure a tutoring session to build a real project incrementally?▼

To build a project incrementally, structure sessions using a linear progressive flow: Concept, See It, Do It, conditional Check It, and Connect. Each exercise adds real functionality to the learner's project across 4-5 modules per session.

Can I use an exercise-verifier to validate learner work during tutoring?▼

Yes, an exercise-verifier validates learner work during tutoring. It integrates with the adaptive quiz system to provide immediate factual feedback on real-project exercises, reducing frustration and ensuring correctness.

Does adaptive tutoring work without prior course materials?▼

Adaptive tutoring relies on prior course materials like a course-outline.md file and a local tutor configuration to bridge prior knowledge. Without these hooks, the tutor cannot deliver the structured, linear progressive module flow.

Why does the tutor rotate quiz formats during a learning session?▼

The tutor rotates quiz formats during a learning session to maintain engagement for inattentive ADHD learners. Format rotation, combined with confidence recording, prevents habituation and informs spacing decisions for future modules.