Practice vocabulary for mixed reality: occlusion, passthrough cameras, spatial mapping, world anchors, and physical-digital interaction.
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When a virtual object realistically hides behind a real-world object (e.g., a digital cube disappears behind a real table), this is called:
The digital object occludes the real world correctly — proper occlusion is one of the hardest and most important aspects of convincing MR; it requires depth sensing of the real world.
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When an MR headset uses cameras to show the real world to the wearer (instead of optical see-through), this is called:
Passthrough shows the real world through the headset cameras — Quest Pro, Quest 3, and Vision Pro all use color passthrough cameras to display the real world.
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The process by which an MR headset builds a 3D model of the user's room to understand walls, floors, and objects is called:
The MR experience requires accurate spatial mapping — spatial mapping creates a mesh of the real world, enabling virtual objects to interact with real surfaces.
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When a virtual object is attached to a specific real-world location so it stays in place even as the user moves around, this is described as:
The anchor persists the virtual object in the real world — world anchors (ARAnchor in ARKit, WorldAnchor in OpenXR) save the pose relative to the real environment.
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The design space that covers how people interact with both physical and digital objects simultaneously in MR is called:
The physical-digital interaction vocabulary includes concepts like 'near interaction' (touching virtual objects), 'far interaction' (pointing), and 'hybrid manipulation' (using real objects to control virtual ones).
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David from the AR team Slack channel writes: 'Just deployed the new hand tracking feature. Users can now manipulate virtual objects with their hands directly in the MR environment! We're seeing a 30% increase in user engagement for this interaction compared to previous gesture recognition attempts.' What does '30% increase in user engagement' primarily refer to?
This phrase describes user behavior. 'User engagement' in this context is a key metric measuring how actively users are using the feature – specifically, how often they're manipulating virtual objects with their hands. Option A and C are irrelevant to the core meaning of the statement; option D relates to technical performance, not user interaction.
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Sarah is writing a PR description for her work adding support for Occlusion Planes in their MR application. She states: 'Implemented occlusion planes to improve the visual fidelity of the virtual objects when they are overlaid on real-world surfaces. This ensures that the user always sees the correct representation of the scene.' What is the primary benefit of using 'occlusion planes' in this scenario?
Occlusion planes are a core technique in mixed reality. They work by defining virtual surfaces that block the view of real-world objects behind them, creating a more convincing illusion of depth and realism. Options A, B, and D describe different functionalities, not the fundamental purpose of occlusion planes.
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You're reviewing a colleague's code that uses the Spatial Anchors API. The comments indicate the anchor is tied to a specific point in the user's physical room. What does this mean in terms of the virtual object's behavior?
Spatial Anchors are critical for persistent placement. When an anchor is tied to a specific physical location, the associated virtual object will maintain its position relative to that point, even as the user moves around the room. This creates a stable and predictable experience.
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During a standup meeting, Ben says: 'I'm working on integrating haptic feedback into the MR application. We're using controller vibration patterns to simulate the feeling of touching virtual objects.' What does he mean by 'controller vibration patterns'?
Haptic feedback is about creating a sense of touch. 'Controller vibration patterns' refers to the controlled pulsing or shaking of the MR controller, designed to mimic the feeling of physically interacting with virtual objects. This is distinct from sensor tracking or screen animations.
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The documentation for a new MR SDK describes 'Persistent Scene Graph'. What does this term primarily refer to in the context of mixed reality development?
The 'Scene Graph' is a foundational concept. It represents how all objects (both real and virtual) are organized and related within the mixed reality environment. The term emphasizes that this graph must be persistent across sessions to maintain consistency.
What does this Wearables & Spatial Computing Language exercise cover?
This exercise, "Mixed Reality Vocabulary", tests your understanding of wearables & spatial computing language vocabulary and phrasing through 10 multiple-choice questions drawn from real workplace scenarios.
Is this exercise free to use?
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How many questions does this exercise have?
This exercise has 10 questions. Each one presents a realistic sentence or scenario with multiple-choice options and an explanation once you answer.
What happens after I answer a question?
You'll see immediate feedback showing whether your answer was correct, along with a short explanation of why — then a button to move to the next question.
Can I retry the exercise if I get questions wrong?
Yes. Once you reach the results screen, click "Try again" to reset your answers and go through the exercise from the start as many times as you like.
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No account is needed. Your answers are scored in your browser during the session — nothing is saved to a server, so you can jump straight in.
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No — progress within an exercise resets if you navigate away or reload. Each exercise is short enough to complete in a few minutes in one sitting.
Who is this Wearables & Spatial Computing Language exercise for?
It's designed for IT professionals and learners who want to sound natural discussing wearables & spatial computing language topics in English — useful for meetings, documentation, interviews, and day-to-day communication with English-speaking teams.
How is this different from reading a glossary or blog article?
Exercises like this one are active recall drills — you have to choose the correct term or phrasing yourself, which builds retention faster than passively reading a definition.
Where can I find more Wearables & Spatial Computing Language exercises?
Browse the full Wearables & Spatial Computing Language exercises hub for more practice, or explore other exercise categories covering vocabulary, grammar, interviews, and workplace communication.