Authors - Janset Shawash, Henri Liu, Alicia Sudlerd, Leevi Rantala Abstract - Simulation-based learning gives healthcare students safe, repeatable practice before clinical placement; virtual reality (VR) makes it more accessible and affordable. This paper presents Aino, an artificial-intelligence-driven virtual patient for an occupational therapy (OT) home-visit showering assessment, built in Unity for the standalone Meta Quest 3. Where most of existing OT VR tools rely on fixed-viewpoint, pre-recorded 360-degree branching video, Aino is a conversational 3D patient whom students address in unconstrained natural speech (Finnish or English) while moving freely within a single continuous scene that follows a dynamic clinical narrative. The technical core is a hybrid control architecture that decouples a scripted, data-driven clinical narrative from free-form conversational responses: a section-based state machine runs twenty-nine designer-authored sections, each with an explicit completion contract that reconciles deterministic clinical progression with variable-length AI dialogue, behind an AI-provider-agnostic interface. OT educators use observation-based scenarios, and thus, the patient narrates her actions and reactions to keep her performance legible; this narration pattern and its calibration are examined as a transferable design lesson. The showering task additionally involves intimate personal care that cannot be ethically rehearsed in live role-play yet is staged safely in VR. Formative findings from educator co-design, educator try-out sessions, and play-testing are reported, and planned student evaluations are outlined.
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