Exercise Set: [Topic]

Purpose

The exercise-designer skill helps educators create varied, evidence-based practice exercises that target specific learning objectives and apply proven strategies from cognitive science. This skill designs exercises with appropriate difficulty progression, spaced repetition opportunities, and clear assessment criteria.

Constitution v4.0.1 Alignment: This skill implements evals-first exercise design—defining success criteria BEFORE creating exercises, integrating Section IIb (AI Three Roles Framework) co-learning exercise types, and aligning with Section IIa (4-Layer Method) for layer-appropriate exercises.

When to Activate

Use this skill when:

• Educators need practice exercises for Python concepts
• Designing homework assignments or problem sets
• Creating varied exercise types beyond simple coding problems
• Applying evidence-based learning strategies (retrieval practice, spaced repetition)
• Establishing difficulty progression across exercise sequences
• Generating test cases and rubrics for exercises
• Evaluating existing exercises for pedagogical effectiveness

Inputs

Required:

• Learning objectives: What learners should be able to do
• Concept/topic: Python concept to practice (e.g., "loops", "dictionaries")

Optional:

• Target audience: beginner | intermediate | advanced
• Number of exercises: How many to generate
• Exercise types: Preferred types (fill-in, debug, build-from-scratch, etc.)
• Time constraints: Total time available for exercises
• Prior concepts: Previously learned concepts for spaced repetition

Evals-First Exercise Design (Constitution v3.1.2)

CRITICAL WORKFLOW:

1. Evals First: Review success criteria from chapter spec BEFORE designing exercises
2. Objectives Second: Ensure exercises target learning objectives that lead to evals
3. Exercises Third: Design practice activities that prepare students for eval success
4. Validation Fourth: Verify exercises measure progress toward defined success criteria

Template: