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Always check and follow your local guidelines about whether this use of generative AI is permitted. If it is permitted, you may need to acknowledge the use of AI.
Generative AI tools generally have a word limit for each response, so you may need to break down a large task into smaller sub-tasks.
The requirements for case studies vary across disciplines - remember to adapt your usage of generative AI according to your specific needs.
Think of what are the common problems of your cases - apply your concepts to these problems.
Ensure you develop your own creative problem solving abilities - if you start with AI, it might stifle or bias your own thoughts.
Start by reading and analysing the case yourself, before you reach out for generative AI. This helps you develop your own thoughts and questions before you consult AI.
It’s essential to understand the specific requirements for your case studies. Keep in mind that generative AI doesn’t provide automatic guidance.
To gain a precise understanding, follow up on references suggested by generative AI. These references may provide further insights and guide your next steps.
Instead of asking AI for a complete analysis, consider using it to address specific aspects of the case that you find challenging.
Always fact-check information provided by AI.
When approaching an unfamiliar topic, you could use generative AI to provide a quick overview of a new concept.
Generative AI might help generate search terms and synonyms for finding relevant cases.
It is also quite effective at summarising sources, suggesting counterarguments for a topic, and exploring different perspectives.
Because of its associative abilities, generative AI might be helpful in finding relevant analytical frameworks and connecting concepts. For example, you might ask AI:
"Can you suggest some analytical frameworks that might be applicable to this case?"
"How might [specific concept from class] apply to this case study?"
You might find it helpful to have AI help suggest a structure for an analysis.