AR user research employs methodologies tailored to understand how users interact with digital overlays in physical environments. Three core approaches are controlled user testing, field studies, and iterative prototyping with feedback loops. Each method addresses specific aspects of AR design, such as spatial interaction, contextual relevance, and usability.
Controlled user testing involves observing participants in lab environments designed to simulate real-world scenarios. For example, researchers might use motion capture systems to track hand movements during AR gesture interactions or eye-tracking glasses to analyze where users focus their attention when digital elements are overlaid. These labs often include physical props (like mock furniture for interior design apps) to ground the AR experience in a tangible context. Developers can measure metrics such as task completion time, error rates, or physiological responses (e.g., pupil dilation for cognitive load). A concrete example is testing AR maintenance guides for industrial equipment: users might troubleshoot a virtual engine model projected onto a physical workspace while researchers assess clarity of instructions.
Field studies prioritize observing AR use in real-world settings where environmental variables (lighting, noise, movement) influence behavior. For instance, a navigation app might be tested outdoors using GPS and camera-based AR to guide pedestrians, with researchers logging issues like occlusion (digital arrows obscured by sunlight) or safety concerns. Wearable devices like smart glasses or head-mounted displays can record first-person video and sensor data, while mobile ethnography tools (e.g., experience sampling apps) prompt users to self-report frustrations in the moment. A retail AR app trial could involve users scanning store shelves with their phones to view product details, with researchers noting how often they switch between AR and non-AR modes due to usability barriers.
Iterative prototyping combines rapid development cycles with frequent user feedback. Tools like Unity or Unreal Engine enable developers to build low-fidelity AR prototypes (e.g., basic 3D models anchored to surfaces) for early usability tests. For example, a furniture placement app might start with wireframe couches that users drag via touch gestures, with feedback informing refinements like collision detection or scaling controls. Co-design workshops—where users sketch AR interfaces or role-play interactions—help uncover unmet needs, such as the desire for voice commands in hands-free scenarios. Post-test surveys and semi-structured interviews often complement these sessions, revealing subjective preferences (e.g., aversion to cluttered AR menus). This approach balances technical feasibility with user-centric design, ensuring AR solutions align with practical workflows.