Teaching AI Fluency
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{lesson} 01Teaching AI Fluency

Study Notes

wab

wab — yIlaD.

{study notes}
  • {AI Fluency Framework} - cha'DIch: SovwI'pu'vaD nuq 'oS AI collaboration; cha'DIch: nuqDaq mejDI' SovwI'pu' QaPla'
  • loS Qapla' teaching approaches - linear (Delegation → Description → Discernment → Diligence), non-linear (flexible movement), focused (wa' competency deep dive), loop-based (strategic/tactical nested processes)
  • Linear approach - qapla'pu' chu'wI'pu'vaD; sequential skill building; structure 'oS QaPla'
  • Non-linear approach - SovwI'pu' experienced-pu'vaD; real-world complexity; flexible entry points
  • Focused approach - wa' D-vaD deep exploration; three sub-components thorough analysis
  • Teaching context mapping - student backgrounds, AI experience, constraints, success metrics; Claude-vaD context document
  • Approach selection - student readiness, available time, learning goals, institutional policies 'oS basis
{flashcards} 10 {cards}
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Anki (.tsv) ↓
{knowledge check} 6 {questions}