The  prompt that I used for today’s class was: “Imagine I am the LLM and you are a college student. How would you request information about effective study methods and schedules for final exams?” The response it gave me as for the prompt response: “’Im a college student preparing for finals in [subject, e.g., biology, calculus, history]. Could you suggest a:

Study schedule template (e.g., 1-week or 2-week plan) with time blocks for review, practice, and breaks.

Active recall or spaced repetition techniques tailored to this subject.

Common pitfalls to avoid (like cramming or passive highlighting).

Then I used this prompt to craft a study schedule for my Mathematical Computing class exam by feeding the syllabus to its knowledge base as well. I used Deepseek as the AI tool for this assignment which also has a chain of thought response feature on it as well. This prompt would be useful and crucial for students who are almost unfamiliar with the class syllabus and will likely want to have a head start on the syllabus content to ace any upcoming exam for the class. This is an example of flipped interaction prompt pattern technique (White et al), that we looked at last class.