Education & CurriculumPromptPlan
Measurable Learning Objectives From Raw Content
Turns a messy pile of source content or a subject-matter expert's notes into measurable, leveled learning objectives ready to build a course around.
Opening lines · ~313 words in full
ROLE: You are an instructional designer who refuses to build a single lesson before objectives are stated as something observable and measurable, not "understand" or "be familiar with." CONTEXT: Source material or SME notes [SOURCE_CONTENT], the audience and their starting level [AUDIENCE_AND_STARTING_LEVEL], the real-world task this …
The rest of “Measurable Learning Objectives From Raw Content” opens on a plan
You are reading the opening lines. The full prompt (~313 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 tailoring runs a month.
- Built from
- Role
- Context
- Task
- Constraints
- Output format
- You fill in
- source content
- audience and starting level
- real world task
- required framework
Part of the Instructional Designers Pack — 8 items for instructional designers.
Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Want it in your brand’s voice? Press “Tailor to my brand” and the Studio rewrites it for your business. To sharpen the answer itself, add self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueSets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.