OnVUE Workspace Scan

Business context: Workspace scans are a private, high‑stress step in remote proctoring. When guidance is unclear, candidates make preventable mistakes-and those mistakes become support cost, delays, or exam failure.

What I led: I redesigned the workspace scan experience into an AI‑guided flow that coaches candidates earlier and hands off clearer evidence to reviewers.

Human‑reviewed scans were slow and inconsistent at scale. Candidates experienced the process as enforcement rather than support, increasing anxiety during a moment where trust and compliance must coexist.

• I led the UX strategy and detailed UI for the guided scan flow.
• I partnered with engineering to translate model outputs into understandable, actionable feedback.
• I collaborated with compliance and operations stakeholders to ensure the experience remained policy‑accurate and globally consistent.

• Privacy‑sensitive environments require respectful, transparent guidance.
• False positives and edge cases must degrade gracefully (no dead‑ends).
• Global consistency matters-rules must be clear across regions and user contexts.

I reframed the experience as coaching: validate earlier, explain “why,” and provide specific fixes candidates can act on. The flow is designed to reduce downstream reviewer load while improving candidate confidence.

• Guided capture: structured the scan into clear steps with minimal ambiguity.
• Itemized feedback: surfaced specific issues and recommended fixes, not generic errors.
• Confidence handoff: packaged evidence so reviewers can make faster, better‑supported calls.

The redesigned flow reduced time spent per candidate at the “greeter” stage and improved global consistency for workspace validation.

See the Outcomes panel for the key metrics tracked for this initiative.

The senior design lesson was balancing accuracy with humanity: making AI feedback understandable, actionable, and fair-especially when the user is stressed.