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AI USE CASE

Tutoring Lesson Plan Personaliser

Generates personalised lesson plans for tutors from prior session notes and student weaknesses.

Typical budget
€500–€5K
Time to value
1 weeks
Effort
1–4 weeks
Monthly ongoing
€50–€300
Minimum data maturity
basic
Technical prerequisite
spreadsheet savvy
Industries
Education
AI type
llm

What it is

An LLM-powered tool that reads the previous session's notes, the student's exam board, and their weakest topics to auto-draft a ready-to-use lesson plan in minutes. Tutors report saving 20–30 minutes of prep per session, freeing up time for more students or higher-quality delivery. For a tutor running 20 sessions per week, that equates to 6–10 hours of recovered time weekly. Early adopters see improvements in lesson coherence and student progression rates within the first month.

Data you need

Past session notes (text), student exam board or curriculum reference, and a list of the student's weakest topics — stored in any format (notes app, spreadsheet, or document).

Required systems

  • none

Why it works

  • Tutors maintain a consistent, brief note-taking habit immediately after each session.
  • A simple template or prompt is standardised across the tutoring firm so outputs are consistent.
  • Plans are treated as first drafts — tutors review and adjust before each session.
  • The tool is introduced gradually with one willing tutor acting as an internal champion.

How this goes wrong

  • Tutors stop providing structured session notes, causing output quality to degrade rapidly.
  • The generated plan is used without review, leading to misaligned content for the student's actual level.
  • Exam board or syllabus data is outdated, producing plans that reference superseded content.
  • Buy-in is low because tutors see plan generation as a core skill they don't want to delegate.

When NOT to do this

Don't invest in a custom-built solution if your firm has fewer than five tutors — an off-the-shelf LLM tool or a simple GPT prompt template will deliver the same time saving at a fraction of the cost and complexity.

Vendors to consider

Sources

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