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Educator and Classroom Prompts

Six prompts designed for instructors introducing FCC to undergraduates, graduate students, or professional-education cohorts. They emphasize scaffolded learning, assessment transparency, and accessibility. All examples assume a 90-minute class session or a 2-hour workshop block.

Personas Used

Persona ID Full Name Category Role in Prompts
CS Content Strategist docs_as_code Module design, narrative structure
DQR Docs Quality Reviewer docs_as_code Clarity and consistency checks
UAA UX Accessibility Auditor ux_visualization Accessibility and inclusion

Prompt 1: Designing a 90-Minute Workshop

Audience: Educator Difficulty: intermediate Personas: CS, UAA

Context

An instructor has one class session to introduce FCC to a mixed-skill audience.

Prompt

CS leads; UAA reviews for accessibility.

Find: audit the three most common learner starting points (never
coded; coded but no AI; coded with AI). Identify the single concept
that unblocks all three.

Create: produce a 90-minute session plan broken into six blocks with
minute markers. Include the pre-reading (<=15 minutes), a 20-minute
live demo, a 30-minute paired lab, and a 15-minute reflection.
Provide speaker notes for the demo.

Critique: UAA to flag anything that would exclude a learner using a
screen reader, a learner with slow internet, or a learner without a
GPU.

Expected Output

  • Six-block session plan
  • Speaker notes
  • Accessibility critique

Prompt 2: Authoring Assessment Rubrics from Quality Gates

Audience: Educator Difficulty: intermediate Personas: DQR, CS

Prompt

Convert three FCC quality gates (from `src/fcc/data/governance/
quality_gates.yaml`) into a 20-point student rubric for a capstone
assignment. Preserve the gate thresholds but translate them into
student-facing language. Include examples of passing, borderline,
and failing work for each rubric row.

Expected Output

  • 20-point rubric
  • Exemplar gallery

Tips

  • Use parallel grammar across rows so students can compare easily.

Prompt 3: Authoring a Student Scenario

Audience: Educator Difficulty: intermediate Personas: CS

Prompt

Write an FCC scenario JSON that students can tweak. Scenario goal:
a small nonprofit wants to build a volunteer scheduling assistant.
Requirements:
- Exactly three personas (one core, one docs_as_code, one governance)
- A setup.ai_config set to the mock provider
- A well-commented constraint list that students can edit
- A "stretch" variant that adds a fourth persona

Validate the scenario with `fcc validate` and note any warnings.

Expected Output

  • Scenario JSON
  • Validator output
  • Stretch variant

Prompt 4: Explaining R.I.S.C.E.A.R. to Undergraduates

Audience: Educator Difficulty: beginner Personas: CS, DQR

Prompt

Produce a 10-minute mini-lecture script that explains the ten
R.I.S.C.E.A.R. slots to undergraduates without prior AI coursework.
Use a running analogy (hiring a teammate). For each slot give one
concrete example and one common misconception. End with three
check-for-understanding questions and model answers.

Expected Output

  • Lecture script
  • CFU questions with answers

Prompt 5: Guiding a Group Through the Collaboration Engine

Audience: Educator Difficulty: advanced Personas: CS, UAA

Prompt

Design a 45-minute group activity that puts four students into a
single collaboration session using FCC's CollaborationEngine. One
student role-plays the human reviewer, three personas drive Find,
Create, and Critique respectively. Provide:
- Setup instructions (one shared notebook or one shared VS Code Live
  Share)
- An approval-gate scenario that forces genuine judgment
- A debrief protocol that surfaces what each role learned
- Accessibility accommodations (UAA)

Expected Output

  • Activity plan
  • Debrief protocol

Prompt 6: Feedback Loop for Instructors

Audience: Educator Difficulty: intermediate Personas: DQR, UAA

Prompt

Design a lightweight feedback mechanism that lets students flag
confusing sections of the guidebook chapters in real time. Output
a markdown file with five questions students answer after each
module, a pivot-table format that aggregates responses across
cohorts, and a rule for when a section warrants a revision (for
example, > 20% of students mark it confusing).

Expected Output

  • Feedback template
  • Aggregation format
  • Revision rule

See Also

  • Guidebook Appendix (Teaching Guide)
  • docs/books/ series
  • docs/tutorials/sample-prompts/beginner-first-project-prompts.md