Role Play: what it is and why it matters
Role Play lets your people practise a real conversation with an AI persona inside Learn Content. An AI designer builds the scenario from your description, learners practise it, and every session is scored against a rubric, turning soft-skill practice into measurable evidence.
Note: Role Play is a content block of Learn Content. If you do not see the Role Play block in the Content Management tab, contact GFoundry support.
What is a Role Play?
A Role Play is a guided conversational simulation inside a Learn Content item, alongside other content blocks such as videos, PDFs and quizzes. The learner chats with an AI persona (for example a frustrated customer, a hesitant candidate or a direct report) and works through the scenario in stages. At the end, the conversation is automatically evaluated against a set of criteria.
It complements the other Learn tools: a video or PDF delivers knowledge, a quiz checks recall, and a Role Play lets people practise the behaviour. See Building Content: Adding Content Blocks for the full set of blocks.
What is it for?
Practising high-stakes conversations in a safe space: sales objections, difficult feedback, support calls, interviews, negotiations.
Turning theory into behaviour: pair a Role Play with the surrounding Learn Content so people apply what they just read or watched.
Generating per-skill evidence, instead of relying only on a quiz score or a self-assessment.
Benefits
Fast to build: describe the scenario in plain language and the AI designer drafts the persona, stages, criteria and skills for you.
Safe practice: learners who do not pass can try again.
Consistent evaluation: every session is scored against the same rubric, with feedback per criterion.
Measurable skills: each evaluated session records evidence for the skills its criteria exercise.
Full visibility: admins can review every learner session, its score and its feedback.
How Role Play fits with the other skill sources
Videos, PDFs and quiz questions can also be linked to skills with Skill Tags. Role Play adds a behavioural signal, because every session is scored against a rubric whose criteria are mapped to skills.
For how each source contributes, see How Learn content feeds the skills engine and How role-play sessions feed the skills engine.
How it works, end to end
Design: an admin describes the scenario to the AI designer, which builds the role play. See Designing a Role Play with the AI Designer.
Test and publish: the admin tries the scenario as a learner would, reviews the evaluation and publishes. See Testing and publishing a Role Play.
Practice: learners run sessions, get scored and receive feedback. See The learner experience: practicing a Role Play.
Review: admins review sessions and outcomes. See Reviewing Role Play sessions, evaluations and feedback.
For the agent behind Role Play, including which AI providers it uses and what data they receive, see Role-Play Coach Agent: AI Skills Practice and Evaluation.