active-learning-design-support

name	active-learning-design-support
description	Design and review active learning implementation support for university teachers, including classroom activity structures, preparation workflow, student participation, assessment alignment, and AI-agent support points.

Active Learning Design Support

Use when the user asks how the AI agent should support active learning, or when turning teacher needs into teaching activities and implementation workflows.

Focus

Keep the analysis grounded in higher education teaching practice. The output should help teachers implement active learning, not just describe active learning in theory.

Workflow

1. Identify teaching context:
   • discipline
   • class size
   • mode: in-person, blended, online
   • session length
   • teacher experience
   • constraints
2. Select suitable active learning patterns:
   • think-pair-share
   • problem-based learning
   • peer instruction
   • case discussion
   • collaborative problem solving
   • debate or role play
   • concept mapping
   • formative quiz and feedback
3. Define implementation steps:
   • preparation before class
   • in-class facilitation
   • student grouping and participation
   • feedback and assessment
   • post-class reflection
4. Identify where the AI agent can assist:
   • activity suggestion
   • lesson redesign
   • prompt/question generation
   • adaptation to class constraints
   • facilitation checklist
   • risk warning
   • reflection support
5. Check concerns:
   • teacher workload
   • loss of autonomy
   • assessment alignment
   • student resistance
   • inclusivity and accessibility
   • practical classroom constraints

Output

Create or update:

• design-specs/ACTIVE_LEARNING_SUPPORT_MODEL.md
• teaching-designs/ACTIVE_LEARNING_ACTIVITY_BANK.md
• teaching-designs/IMPLEMENTATION_CHECKLIST.md

Guardrails

Do not assume one active learning method fits all contexts. Distinguish teaching design advice from evidence found in the user's research data.