Course Design Helper

The Problem

Lesson plans often remain at the template level: objectives are written as “understand” or “grasp,” interaction is reduced to open questions, and course-type differences are ignored. This skill turns instructional theory into executable steps, helping teachers create a teaching plan with concrete actions, time allocation, and knowledge checks based on the topic, student level, and class duration.

How It Works

The skill uses a decision-orchestration layer plus domain knowledge modules. It first confirms subject, topic, grade, prior knowledge, duration, online/offline conditions, and course type. It then maps objectives to Bloom verbs, conditions, and standards using bloom_taxonomy.md. Depending on the need, it selects BOPPPS, Gagné’s nine events, or constructivist paths from teaching_models.md and builds the teaching flow. For a standard 45-minute lesson, it references time blocks for introduction, instruction, practice, summary, and extension, while keeping direct instruction below 50% and reserving at least 50% for interaction. Interaction design reads interaction_design.md and matches prompts, Think-Pair-Share, case analysis, One-Minute Paper, Jigsaw, and similar methods to each stage. Finally, a checklist verifies measurable objectives, interaction share, concrete hooks, layered practice, and knowledge checks.

Boundaries

The skill produces instructional design content rather than PPT files, and it is not aimed at research papers on educational theory. course_planner.py can generate a base framework quickly, but hooks, case selection, and interaction details still need teacher judgment.