Organising learning progression
How do you move from a list of content to a verifiable progression towards professional autonomy?
1960 € per session, excl. VAT
In short
This 7-hour day, excluding breaks, enables you to turn a workplace need into coherent learning stages. Using generative AI, you clarify prerequisites, sequence levels of difficulty, adjust the amount of support and define evidence of mastery. You produce a documented learning pathway, revised against a quality checklist.
Why this training?
A catalogue of concepts does not constitute a progression: learners may understand each module without being able to perform the final task. Implicit dependencies and jumps in difficulty then make exercises artificially difficult. AI helps suggest ways to break down the learning, compare sequences and vary situations. The designer remains responsible for occupational validity, cognitive load and alignment between objectives, activities and assessments. Running case study: The fictitious organisation « Valsune Réparation » wishes to train its new coordinators to handle service requests. Its current materials mix assessment, prioritisation and exception handling. Using fictitious procedures, participants organise a pathway that progresses from a simple request to independently handling an ambiguous case. Transfer to the workplace: Take an existing pathway, identify a break in progression and revise the stage concerned. After use, compare the errors observed with the planned mastery criteria, then adjust the scaffolding or prerequisites rather than automatically adding content.
Objectives of this training
- Breaking down a work activity into observable capabilities
- Mapping dependencies and prerequisites between learning components
- Sequencing situations by complexity and expected independence
- Writing activities with decreasing scaffolding
- Evaluating pathway alignment and correcting identified breaks
Who is it for and what are the prerequisites?
Roles and tasks concerned
- Instructional designers and training managers who revise occupation-specific learning pathways
- Trainers and subject-matter experts responsible for helping mixed-ability groups progress
Prior skills
- Be able to formulate and refine a request to a generative AI assistant
- Have previously delivered or designed a vocational training sequence
- Identify the tasks and common errors in the target occupation
What you will work on
Defining the final performance
Objective: Distinguish the professional task from the content to be taught. Target audience, working conditions, critical errors and expected independence.
Making prerequisites visible
Objective: Avoid introducing learning components too early. Dependencies, entry assessment and the distinction between essential and supplementary requirements.
Sequencing the levels
Objective: Organise a controlled increase in difficulty. Case complexity, variability, cognitive load and reactivation of prior learning.
Gradually withdrawing support
Objective: Move from a guided example to independent performance. Annotated example, partially guided exercise, independent task and targeted feedback.
Defining transitions and remedial support
Objective: Make progress conditional on observable learning outcomes. Formative assessment, justified thresholds and targeted revisiting after errors.
Auditing coherence
Objective: Identify and correct breaks in the pathway. Alignment of objectives, activities and assessments, coverage of capabilities and feasibility within the available time.
What you take away
- Matrix of capabilities, prerequisites and evidence of mastery
- Progression map with durations and transition points
- Activity sheets with decreasing support
- Completed audit checklist and correction log
Method and assessment
- Brief instructional input followed by immediate practice using the running case study.
- Individual work followed by work in pairs, with peer review of outputs.
- Guided group discussion: what works, what needs correcting and what remains a human decision.
- Preparation: Prepare a fictitious or anonymised example of a programme with its objectives and time constraints. Check access to an AI tool authorised by the organisation; no learner records containing names will be used.
Observable criteria: Each objective describes an observable action and has evidence of mastery. ; Each prerequisite is acquired beforehand or checked during placement assessment. ; Each stage specifies its difficulty, support and progression criterion. ; The combined durations stay within the time allocated to the pathway. ; AI proposals are checked against the supplied procedures and corrections are recorded..
Frequently asked questions
Do all the materials need to be produced?
No. The day focuses on the structure and three activities representative of the progression.
How do you address different entry levels?
The placement assessment directs learners towards refresher learning or direct access to stages they can master.
Does AI decide the teaching sequence?
AI proposes alternatives; the designer decides based on dependencies and occupational constraints.
Can you use an internal programme?
Yes, after anonymisation and checking confidentiality rules, using authorised tools only.
Last updated: