The best approach is to lead with the learning objective — tell the AI what your students should know or be able to do after completing this module — and then ask it to build a research brief around that specific outcome.
Start With the Outcome, Not the Topic
Most educators make their research harder by starting too broad. “Tell me about email marketing” produces a wall of general information. “My students are solo online coaches who have never sent an email campaign — what are the five most important things they need to understand before sending their first one?” produces something you can actually build a module from.
The difference is framing the prompt around a learning outcome. AI is much better at being useful when you’re specific about who the learner is and what they’ll be able to do at the end. Think of it the way you’d brief a really smart colleague: “I need you to help me teach a beginner this specific skill. Here’s who they are and here’s what success looks like. What do they need to know?”
A Four-Step Research Sequence That Works
Step one: state the module objective. “My students should be able to set up their first automated email sequence by the end of this module.”
Step two: ask for a structured concept summary. “What are the core concepts, in logical order, that a beginner needs to understand to achieve this?” You now have an outline.
Step three: ask for misconceptions. “What do beginners typically get wrong about this topic that I should proactively address in my teaching?” This is gold — it tells you where to slow down and explain more carefully.
Step four: ask for real examples. “Give me two specific, concrete examples of each concept that would make sense to a solo online educator who is not technical.” Now you have content.
This four-step sequence takes 15–20 minutes and produces the research foundation for a full module. Claude tends to be stronger at nuanced explanations and structured reasoning. ChatGPT tends to produce more conversational, varied examples. It’s worth running the sequence in both and comparing — you’ll often find that combining the outputs gives you the strongest result.
What This Means for Educators
This workflow is not about outsourcing your expertise — it’s about organizing what you already know and filling the gaps quickly. You bring the experience, the judgment, and the relationship with your students. AI brings the synthesis and the structure. Together, that’s a module that would have taken a full day to research and now takes a morning.
The Simple Rule
Open every module research session with one sentence: “My students should be able to [outcome] after this module.” Everything you ask AI after that flows from that sentence — and every answer it gives you will be pointed at the right target.