Results for “learning”8 prompts
A full course outline for STEM enrichment: modules, arcs, assessments and pacing. Built for instructional designers working in STEM enrichment, tuned for NotebookLM. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Specific, growth-oriented feedback at scale for K-12 classrooms work. Built for course creators working in K-12 classrooms, tuned for Claude. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A full course outline for professional certifications: modules, arcs, assessments and pacing. Built for instructional designers working in professional certifications, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Complete, engaging lesson plans for music education aligned to stated outcomes. Built for instructional designers working in music education, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
Valid assessments for language learning that measure understanding, not recall tricks. Built for tutors working in language learning, tuned for Claude. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A ready-to-run workshop for STEM enrichment audiences: agenda, activities, materials and facilitation notes. Built for tutors working in STEM enrichment, tuned for NotebookLM. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A full course outline for homeschooling: modules, arcs, assessments and pacing. Built for teachers working in homeschooling, tuned for ChatGPT. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.
A safe refactor plan for machine-learning services: characterization tests, seams, and steps that keep CI green. Built for platform teams working in machine-learning services, tuned for Cursor. Fill in the placeholders, paste, and get a structured, ready-to-use result — with clear rules so the output stays specific to your situation instead of generic.