QAVRAHelp

Tutor Chat And Learners

QAVRA includes learner-facing course delivery, tutor support, approved Expert Chat, AI Practice, and learner progress views.

Learner Workspace

Learners use their workspace to:

  • Continue courses.
  • Resize the Course Contents and Tutor side panels on desktop when they are open.
  • Start or resume AI Practice.
  • Ask approved Experts questions.
  • Browse available learning products.
  • Review billing and AI credits where enabled.
  • Update profile details.
  • Accept organisation invitations.

Tutor And Expert Chat

Tutor chat supports learners inside course experiences. Expert Chat lets learners ask approved learner-facing Experts questions from connected Knowledge Profiles.

Expert answers depend on the Knowledge Profiles and Public Mentor Profiles made available to the learner audience.

Anonymous Expert Chat does not retain resumable chat history, so its saved-chat rail is hidden. Sign in to save and resume Expert Chat threads.

For a public Expert or AI practice marked public paid, anonymous visitors cannot send a free message or start a session. QAVRA explains that the organisation requires payment and offers a sign-up CTA. After signing up, an external learner adds paid AI credit in their learner wallet; each eligible Expert or AI practice response debits that personal paid-credit balance. Organisation members and public-free access follow their configured access and billing rules.

Agents can add booking or workshop CTAs after eligible Tutor Chat, Expert Chat, or AI practice responses when an admin has configured them for the Knowledge Expert.

Admin Setup Checks

Before learners rely on chat support, confirm:

  • The correct Knowledge Profile is approved and healthy.
  • The learner-facing Expert or mentor profile is available to the audience.
  • Course content and tutor support are using the intended published version.
  • Any booking or workshop agents have tested HTTPS links and clear CTA labels.
  • Learners have access through the right organisation, offering, purchase, or invitation.

AI Practice

AI practice is the learner-facing umbrella for guided, scenario-based skill-building. Learners choose AI coaching for guided skill-building or AI role play to practise with an approved scenario counterpart. Both approaches support Chat and Live Voice.

Public AI Practice is different from learner AI Practice. A public trial is held only in its current browser tab so visitors can try a scenario; it is not saved learning history, has no cross-device resume, and is not imported after sign-in. Account-owned AI Practice in the learner workspace keeps its existing durable progress and history.

The approach is selected before an attempt starts. Chat and Live Voice can be changed within that same approach without crossing into the other approach’s history. Role Play locks the selected counterpart identity and voice for the attempt.

Role Play counterpart feedback is deliberately separate: learners can use Review with Coach after completion, or while paused where available. It is not a message from the simulated counterpart.

The objective list remains available when a scenario has only one objective. Open an objective’s actions menu to restart it. Restart permanently removes only the selected approach’s scenario chat and progress, including the shared progress shown in the course player. Use Hide from AI Practice in Scenario History when you only want to remove a launch from the AI Practice list without deleting course progress.

Scenario introductions present the participants, goal, immediate situation, and first move as a compact visual brief. One focus cue and one watch-out may appear, while additional detail stays under View Full Scenario Brief.

Admins can review learner scenario progress, missed signals, and risk flags from scenario and analytics views.

If Something Looks Wrong

If a learner cannot see a course, check enrolment, organisation access, offering setup, purchase state, or invitation status.

If chat is not grounded in the right material, review the Knowledge Profile and learner-facing Expert setup before changing course content.