Educational feedback

How can you personalise learner feedback with AI without automating the grade?

1250 € per session, excl. VAT

In short

Trainers, L&D teams and tutors learn to personalise feedback with the chosen AI assistant: identify evidence of learning in a piece of work, write descriptive feedback, suggest a remediation question and a tailored exercise, then check fairness and consistency. Deliverables: a feedback grid, personalised comments and remediation exercises, with the trainer validating every comment.

Why this training?

The problem
Educational teams face difficulties personalizing feedback for a large number of learners without spending excessive time.
What it costs today
Learners receive generic or incomplete feedback, leaving them without clear guidance for progress after a submission.
Why this skill
This skill is necessary to provide high-quality pedagogical feedback that helps each learner improve in a targeted manner.
What you gain
The participant and the company develop greater reliability of the feedback provided, ensuring precise support and improved learning quality without compromising human responsibilities.

Objectives of this training

  • Identify evidence of learning within student productions using the chosen AI assistant
  • Formulate relevant descriptive feedback for each learner
  • Propose remediation questions and exercises adapted to individual needs
  • Verify the fairness and consistency of feedback generated by the assistant
  • Adjust and validate feedback before its transmission to learners

Who is it for and what are the prerequisites?

Roles and tasks concerned

  • Trainers and educators
  • L&D teams
  • Tutors and coaches

Prior skills

  • AI Fundamentals and AI Prompting completed, or equivalent experience (a learning prerequisite, not a registration condition).
  • Basic practice of an AI assistant
  • Experience in evaluating learner productions
  • A paid subscription to an AI solution offering the features used, the organisation’s authorisation for third-party tools, and the actual accounts and access rights.

To prepare before the session

  • Functional account for the chosen AI assistant.
  • Experience evaluating learner productions.
  • Access to fictional practice submissions and the evaluation grid.

What you will work on

  1. Starting from a Common Grid

    The participant clearly defines the expected criteria and levels for evaluating learner productions.

  2. Identifying Evidence with the Chosen AI Assistant

    The participant uses the chosen AI assistant to identify specific evidence of learning in productions and validates these identifications.

  3. Formulating Descriptive Feedback

    The participant writes personalized feedback including factual descriptions, remediation questions, and adapted exercises.

  4. Fairness and Validation

    The participant ensures the fairness and consistency of all feedback before final validation.

What you take away

  • Feedback grid
  • Personalized comments for practice submissions
  • Remediation exercises

Method and assessment

  • Fictional pieces of work with different errors
  • Human analysis first, assistant second
  • Cross-review for fairness

Feedback is assessed on reliance on quoted evidence, descriptive wording, relevance of the remediation question and exercise, consistency across learners and explicit validation by the trainer.

Frequently asked questions

What concrete result does this course deliver?

Trainers gain a method for personalising useful, fair feedback while keeping the teaching decision. Deliverables: feedback grid, personalised comments on the exercise pieces of work, remediation exercises.

Who is this course for and what are the prerequisites?

It is designed for: trainers, l&d teams, tutors and coaches. Basic experience with the chosen AI assistant and of assessing learners' work. The pieces of work and exercise grid are fictional.

What data and access need to be arranged?

Exercise pieces of work are fictional. Real learner work is only used anonymised and with the organisation's agreement. Required tools and licences are checked before the session; no subscription is included in the price.

What practical exercise is completed?

Participants receive three fictional pieces of work with different errors and a shared grid. They identify evidence of learning, write descriptive feedback, suggest a remediation question and tailored exercise, check fairness and consistency, then validate as trainers.

What are the limits and who validates the results?

The chosen AI assistant sets no grade and builds no learner profile. Every comment is reviewed, adjusted and validated by the trainer, who remains responsible for assessment.

Can the course be adapted to our line of work?

During scoping, the fictional pieces of work and grid are chosen to fit the context: vocational training, onboarding, sales training, writing skills or project work.

How is the session organised and what does it cost?

Half-day, private in-person session for up to 12 participants. The fee is €1,250 excluding VAT per session. Date and location are agreed during scoping; each session runs in a single language: French, Dutch or English.

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