# Self Explanation Prompt Designer

Create self-explanation prompts that deepen understanding of worked examples, texts, or...

- Repository: https://github.com/GarethManning/education-agent-skills (939 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-10-22
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add GarethManning/education-agent-skills --skill self-explanation-prompt-designer -g -a claude-code -y`
Codex: `npx skills add GarethManning/education-agent-skills --skill self-explanation-prompt-designer -g -a codex -y`
Cursor: `npx skills add GarethManning/education-agent-skills --skill self-explanation-prompt-designer -g -a cursor -y`
Gemini CLI: `npx skills add GarethManning/education-agent-skills --skill self-explanation-prompt-designer -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add GarethManning/education-agent-skills`

## Description

Create self-explanation prompts that deepen understanding of worked examples, texts, or diagrams. Use when students read material passively without engaging with underlying principles.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Self-Explanation Prompt Designer

## What This Skill Does

Designs self-explanation prompts, the specific questions placed at key points in learning material that prompt students to explain TO THEMSELVES why something is true, how it works, or what it means. Chi et al. (1989) discovered that students who spontaneously self-explain while studying worked examples learn dramatically more than those who don't, and crucially, Chi et al. (1994) showed that students who are PROMPTED to self-explain also show significant learning gains, even if they wouldn't have self-explained spontaneously. The self-explanation effect is one of the most robust findings in learning science: it works across ages, domains, and material types. The mechanism is that self-explaining forces the learner to generate inferences, fill in gaps, connect new information to existing knowledge, and notice their own confusion, all of which strengthen understanding. The challenge is designing prompts that actually elicit deep self-explanation rather than shallow restating. "Why does this step follow from the previous one?" is a good self-explanation prompt. "What happens in this step?" is not, it elicits description, not explanation. AI is specifically valuable here because it can deliver prompts at exactly the right moment (during study, not after) and can evaluate the quality of student responses in real time.

## Evidence Foundation

The rest: https://github.com/GarethManning/education-agent-skills/blob/HEAD/skills/ai-learning-science/self-explanation-prompt-designer/SKILL.md