Using Generative AI Effectively in Research

Generative AI can support many research tasks, but the quality of the output depends on how clearly the task is defined and what information is provided. This level teaches a practical approach to giving instructions to AI tools. Learners will provide context, define the task, set constraints, request a useful output format and revise the result when necessary. Verification is treated as part of the process, with attention to unsupported claims, fabricated references and inappropriate statistical advice.

Who this level is for

Anyone who uses or plans to use generative AI for research, academic work, data analysis, teaching, scientific writing or project management. No coding experience is required. Recommended after Level 1.

What you'll learn

• Why clear instructions improve the usefulness of AI outputs
• How to structure instructions using context, task, constraints and expected output
• How examples and reference materials can improve AI responses
• How to divide complex research tasks into smaller steps that can be reviewed
• How to review and refine an AI response instead of accepting the first result
• How to ask AI to distinguish evidence, assumptions and uncertainty
• How to recognise fabricated references, factual errors and unsupported conclusions
• How to verify AI outputs against original sources, study data and established methods

You finish with: A reusable research prompt library + your own AI verification checklist.