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AI agent for computer science students

Exam Revision Plan Agent

A revision plan that spends the most time where it raises the grade most

LearningPlanningIT and development
See how it worksGet access
Exam Revision Plan Agent: what goes in, what the agent does and what you get

What it does

Students often revise the topics they already know and leave weak areas to the last night. This agent builds a revision plan from the syllabus, past papers and the student's own confidence ratings. It schedules sessions that give more time to weak, high-weight topics before the exam date. In each session it gives a few practice questions, checks the answers and updates the confidence score. If scores on a topic stay low after two sessions, it moves more time to that topic and changes the approach, for example worked examples before questions. As the exam nears, it shifts toward full past papers. The student decides daily hours and can move sessions. Edge case: a topic rated confident but failing practice is reopened, because the self-rating was wrong.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Student sets an exam date 2 DOES Build a plan from syllabus weight and confidence 3 USES A TOOL Give practice questions for the day's topic 4 USES A TOOL Mark the answers and update confidence 5 CHECKS THE RESULT Is the topic now at the target confidence? If not: add time, switch to worked examples, andpractice again. Back to step 3. 6 DOES Rebalance the remaining days 7 YOU APPROVE Student approves the updated plan 8 RESULT Updated plan through to the exam
Read the steps as a list
  1. Student sets an exam date
  2. Build a plan from syllabus weight and confidence
  3. Give practice questions for the day's topic
  4. Mark the answers and update confidence
  5. Is the topic now at the target confidence?If not: add time, switch to worked examples, and practice again. Back to step 3.
  6. Rebalance the remaining days
  7. Student approves the updated planThe agent waits here for your OK.
  8. Updated plan through to the exam

How it decides

It prioritizes topics by exam weight times weakness, and reallocates time whenever practice results change the weakness estimate.

  • Weight time by exam weight times weakness
  • Reopen confident topics that fail practice
  • Protect a review day before the exam

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Target confidence level
  • Daily study hours
  • Question sources
  • How aggressively to rebalance

What keeps you in control

It always asks you first

  • Student approves each plan update

Hard limits

  • Does not take the exam or do graded work
  • Keeps a rest day in the plan

It stops when

  • Done: all high-weight topics at target or exam reached
  • Stop: no syllabus or past papers available

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensFour weeks before a May 28 exam, a student rated graph algorithms as confident but scored 4 of 10 on practice, so the check failed. The agent reopened the topic, switched to worked traversals first and added two sessions. At the next check the student scored 8 of 10. The agent moved the freed time to databases, and the student approved the updated plan.

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