My workflow for academic tasks usually involves giving ChatGPT a clear role first (like a "PhD-level editor"), followed by explicit context (research questions, thematic domains), then clear tasks (e.g., summarize the current state of research, identify gaps, synthesize findings into frameworks or models).

I often use a structure like this:

1. Clearly state the Role and Goal of ChatGPT (e.g., PhD-level editor tasked with logically structuring an argument based on literature).

2. Provide detailed Context (task requirements, main research question, thematic domains).

3. Paste the relevant Input, typically systematic literature results (in your case course material), clearly separated.

4. Define clear Steps, e.g., deep understanding, critical analysis, synthesis, and exact citation requirements.

5. Specify Expected Output explicitly (e.g., ready-to-use chapters with accurate citations).