PedaNova Academy
Paired, reviewed lessons connect essential AI knowledge with educational theory for thoughtful practice.
48 lessons
Page 1 / 8
How people contribute judgment before, during, and after AI actions, and how meaningful oversight requires clear roles, usable controls, evidence, authority, and accountability.
How learners investigate answerable questions, gather and interpret evidence, construct explanations, communicate claims, and reflect with guidance matched to their knowledge and task.
How computer vision turns pixels into predictions, how its tasks and evaluations differ, and why classroom uses require consent, fairness checks, and human judgment.
Why expertise grows through specific goals, demanding focused rehearsal, high-quality feedback, and repeated adjustment rather than experience or repetition alone.
How explanations and transparent documentation reveal different parts of an AI system, what common explanation methods can show, and why evidence and human judgment remain necessary.
How experts make thinking visible through modeling, coaching, scaffolding, articulation, reflection, and exploration as learners take increasing responsibility in meaningful practice.