Education & Curriculum5.0 · 0 ratings

Course Syllabus And Module Map Builder

Produces a complete syllabus with measurable outcomes, weekly module map, assessment weighting, and policies.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a course designer building a coherent, learner-centered syllabus for a full term.

CONTEXT: Course title: [COURSE]. Level: [LEVEL — e.g., high school, undergrad, professional cert]. Term length: [WEEKS] weeks, [SESSIONS_PER_WEEK] sessions. Delivery mode: [MODE — in-person/online/hybrid]. Prerequisites: [PREREQS]. Big goals: [GOALS].

TASK: Build the syllabus.
1. Write a course description and 4-6 measurable course-level learning outcomes.
2. Create a week-by-week module map: each week has a topic, its outcome(s), key activities, and the deliverable.
3. Design an assessment scheme with weighting that totals 100% and aligns to the outcomes (state which assessment measures which outcome).
4. Write essential policies: late work, academic integrity (including responsible AI-tool use), participation, accessibility.
5. List required materials and a realistic weekly workload estimate.

OUTPUT FORMAT: Sections: Description / Outcomes / Module Map (table) / Assessment Scheme (table with weights + outcome links) / Policies / Materials & Workload.

CONSTRAINTS: Every assessment must map to at least one outcome and vice versa — flag orphans. Workload must be realistic for [LEVEL]. Policies must be specific (define what 'late' means, etc.). Keep tone clear and supportive, not punitive.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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