Building courses with AI: Articulate Rise 360 plus Face Up

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Why combine Rise 360 and Face Up?

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You save significant production time while making the learning far more active. Rise 360 helps you set a clear structure and generate a first draft of the content. Face Up adds the practice element in a realistic context, with an actionable debrief and data you can use in your reporting: SCORM and xAPI traces on the LMS side, behavioural analytics on the simulation side.

The four things to take away from this approach:

1. Clarify the need before you open any tool
   Start from a simple business objective, such as improving the quality of the welcome, cutting unnecessary transfers, or securing a compliance step. Define the target population, the prerequisites, and two or three typical situations where your teams struggle. This step takes under half an hour, but everything that follows depends on it.
2. Build the module in Articulate Rise 360
   In the video we show two ways in. Pick whichever fits your context and the time you have.

Option A — Start from an existing template and adapt it
If you already have a template that matches your brand guidelines, reuse it. Replace the text and media block by block, reorganise the lessons and refine the assessments. The advantage is that you very quickly get a module that looks like it belongs, while keeping control of every detail.

Option B — Use the Rise 360 AI assistant
When you are starting from nothing, the AI assistant proposes a skeleton: a course outline, lesson titles, text blocks and even quiz questions. You then steer the AI with your own vocabulary, your examples and your sector constraints. Generation does not replace editing: rewrite, cut, and anchor the content in your real use cases.

Either way, keep the blocks short and readable (cards, accordions, lists) so the module works on mobile, and tell learners clearly that a practice scenario is coming later in the module.

3. Embed a Face Up practice scenario in your course
   The point is to let your learners practise the skills they have just been taught.

Open it via a link: add a "Start the simulation" button that opens your scenario in a new tab.

On the tracking side, the Rise module sends its traces to the LMS via SCORM or xAPI. Face Up separately provides granular data on the behaviours observed: active listening, rephrasing, framing, clarity of the proposal, and so on.

4. Close with a debrief that is genuinely useful on the job
   Finish with a debrief sequence that revisits the assessment criteria and offers concrete examples of what to improve. The aim is for the learner to transfer what they have just experienced straight into real situations.

A module structure that works well

• Introduction: why this subject matters to your customers and to your organisation.
• Lesson 1: the fundamentals, illustrated with situations that come up often.
• Short quiz: check comprehension without weighing the programme down.
• Lesson 2: cases by channel (face to face, phone, chat).
• Face Up practice scenario: the learner practises with an AI avatar.
• Debrief and action plan: personalised feedback and the points to work on.
• Resources: scripts, checklists and materials to print or share.

What to watch out for when you use AI

AI lets you move faster, provided you hold the editorial bar high. We always recommend a human edit, sources wherever the material is sensitive or regulated, and sign-off from the people who do the job. Finally, work in short iterations: publish a first version, watch the feedback, and improve.

What next?

If you want to modernise existing content or build a ready-to-deploy programme, we can handle the redesign, the LMS integration and the licensing for the simulations. We work in particular across transport, banking and retail.

Get in touch: mame@face-up.fr

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