disciplinary-ai-literacy-sequence-designer
CommunityTeach AI reliability by knowledge type.
Education & Research#ai literacy#lesson design#knowledge types#disciplinary thinking#vertical vs horizontal#student activities
AuthorGarethManning
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps teachers design a comparison sequence so students learn when AI is likely reliable versus distorted, based on what kind of knowledge different disciplines produce.
Core Features & Use Cases
- Disciplinary side-by-side comparison: Students compare AI outputs for the same anchor question across two or three subjects to surface differences in reliability.
- Knowledge-type grounded predictions: The sequence culminates in a predictive framework (e.g., vertical vs horizontal discourse or other knowledge-structure distinctions) rather than a static list of mistakes.
- Teacher-ready lesson structure: Provides a two-lesson workflow, including what students should record, how to analyze patterns, and a guided discussion with a transfer test.
Quick Start
Use the disciplinary-ai-literacy-sequence-designer skill to produce a two-lesson sequence for students comparing AI answers across the disciplines Biology, History, and Ethics at Year 11 level.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: disciplinary-ai-literacy-sequence-designer Download link: https://github.com/GarethManning/education-agent-skills/archive/main.zip#disciplinary-ai-literacy-sequence-designer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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