Review AI-generated exercises with four quick checks before using them: right difficulty level, real student context, achievable time frame, and your natural voice as an educator.
Ask AI to write each exercise in two formats — action-first for hands-on learners and explanation-first for readers — both teaching the same skill from different entry points.
Write your core exercise once, then ask AI to rewrite it for three to five specific niches — same skill, different context — making your course feel personalised without manual rewriting.
Tell AI what the final portfolio piece is, then ask it to design exercises that build one component per session — students arrive at the end with a complete, real output rather than scattered tasks.
Tell AI to anchor exercises to the student's real business — not hypothetical scenarios — by adding "using their own real [content/course/clients]" to your prompt. That phrase makes all the difference.
Ask AI to design a first-lesson exercise under ten minutes that any student can complete and produces one concrete output — early wins are the strongest predictor of course completion.
An exercise is practice, an assessment measures understanding, and a reflection prompt builds personal meaning — each serves a different purpose and needs different AI prompting to create.
Give AI your course outline and the outcome you promised students, then ask it to design a capstone project that demonstrates both — including the rubric if you need one.
AI can write peer feedback frameworks with observation prompts and sentence starters that help students give useful, specific feedback rather than vague responses.
Give AI a sample of your existing content and a description of your audience, and it will match your course tone — cutting editing time significantly on the first draft.