Jiangsu Vocational AI General Education Project-Based Course Prep Assistant

The Problem to Solve

Teachers of vocational AI general education courses often face the challenge of "having standards and textbooks but struggling to implement them." Project-Based Learning (PBL) designs remain abstract, the 90-minute lesson structure is hard to align with assessment rubrics, and first-year vocational students lack professional foundations. Directly applying higher-education cases makes tasks too difficult. This skill integrates the 2026 curriculum standards, a 198-page textbook, the GRASPS task framework, and the BOtPPPS classroom model into a structured generation workflow, reducing the time cost of manually searching literature and assembling templates.

How the Skill Works

The skill provides two core generation modes:
- Full Project Design: Based on PBL + UbD (Backward Design), it generates a complete project plan through seven steps: set objectives → define tasks → configure assessments → schedule progress → prepare resources → optimize structure → output documents. Single-lesson design can be appended optionally.
- Single Lesson Design: Based on the BOtPPPS model, it outputs a 9-section lesson plan for a 90-minute double period, covering pre-class preview, six in-class phases (bridge-in, objectives, pre-test, participatory learning ×2, post-test, summary), and post-class extension.

Key constraints are built into the logic: driving questions and performance tasks are strictly limited to the "professional/vocational awareness" level, and AI tool tasks focus on "following steps to complete." Learning objectives must use measurable, observable action verbs (banning "understand/master"). Assessment plans must include formative, summative, and outcome-based types plus motivation mechanisms. The skill reads references/ for raw curriculum, textbook OCR text, and knowledge-type tables on demand, ensuring teaching activities align with actual textbook arrangements.

Boundaries and Considerations

• Student Profile: Exclusively for first-year vocational students (no professional background) in AI general education; not suitable for higher-ed or deep development courses.
• Textbook Dependency: Teaching design relies heavily on the built-in 198-page textbook OCR text. Non-standard textbooks require manual consistency checks by the teacher.
• Terminology: Output documents filter out internal theoretical terms (e.g., Show-Q/DOex), but teachers must still verify local naming conventions with their teaching-research groups.