exercise-designer

What problem does it solve?

This Skill helps educators design deliberate practice exercises applying cognitive science principles to programming education, enabling scalable creation of varied, high-quality practice sets.

Core Features & Use Cases

• Evidence-based design: Builds exercises that apply retrieval practice, spaced repetition, interleaving, and elaboration.
• Diverse exercise types: Supports fill-in-the-blank, debug-this, build-from-scratch, extend-code, explain-code, trace-execution, Parsons problems, and AI-collaborative formats.
• Templates & evaluation: Generates objectives-to-eval mappings, rubrics, test-case templates, starter code, and hints to accelerate instructor workflows.
• Use cases: Ideal for Python practice, homework sets, quizzes, and formative assessment across single topics or spiral curricula.

Quick Start

• Define learning objectives and select 3-5 exercise types that align with those objectives.
• Apply evidence-based strategies (retrieval practice, spaced repetition, interleaving) to structure the set.
• Generate starter templates and rubrics, then adapt for your course cadence and difficulty progression.