Step 1
Clarify your AI planning boundaries
Clarify your AI planning boundaries
Use this step to define what AI will and will not do in your planning workflow.
AI can help me with
AI will not decide
Reflection
Step 2
Capture your observation data
Capture your observation data
Summarize what you are actually seeing in the classroom. These observations will feed your AI prompts.
Age group(s) & environment
Key patterns this week
Materials most chosen
Materials rarely chosen
Children needing targeted support or challenge
Reflection
Step 3
Generate baseline AI-assisted lesson ideas
Generate baseline AI-assisted lesson ideas
Use this reusable core prompt to generate a list of lesson ideas based on your observations.
You are a Montessori-trained guide supporting lesson planning for a [age group] classroom.
I will paste my weekly observations.
Your task: suggest 5–10 lesson presentations or follow-up activities using authentic Montessori materials or close equivalents, aligned with child-led, hands-on learning.
Constraints:
- Avoid replacing materials with screens.
- Propose lessons at different levels (introduction, repetition, extension).
- Name the material, plane of development, and key skill.
- Output in a simple table: material, lesson description, child readiness (emerging/secure/extension).
Baseline lesson plan (paste AI output)
Reflection
Step 4
Differentiate lessons for specific children
Differentiate lessons for specific children
Use this prompt to generate scaffolds and extensions for individual children while you keep final judgment.
You are a Montessori guide.
I will describe a child’s profile and a baseline lesson.
Your task: suggest 3 differentiated variations: one simplified scaffold, one standard presentation, and one extension.
Constraints:
- Preserve hands-on materials.
- Avoid screen-based replacements.
- Respect the child’s independence and choice.
- Include a short note on what I should observe to decide when to offer each variation.
Child label
Focus area
Strengths
Challenges
Baseline lesson description
Differentiated variations (paste AI output)
Reflection
Step 5
Map lessons into a weekly work cycle
Map lessons into a weekly work cycle
Translate AI-generated ideas into a realistic weekly plan that respects the Montessori work cycle and child choice.
Weekly planning grid
Checklist
Step 6
Check hands-on learning & tech limits
Check hands-on learning & tech limits
Use this ethics and pedagogy checklist to keep materials and child-led work at the center.
AI is primarily used for
AI is not used for
Digital child-facing activities
Step 7
Save & connect to your Montilyceum hub
Save & connect to your Montilyceum hub
Turn this workflow into a reusable system inside your Montilyceum Method memory.
Assets to save
Hub link / reference