How unclear navigation was costing Dubai’s education authority 40% user success”
KHDA’s online services were scattered across 300+ categories. Using evidence-based card sorting and data clustering, we improved clarity by 68% and created KHDA’s official IA blueprint for 2025.
Challenge & Context
Knowledge and Human Development Authority (KHDA) serves over 800,000 users across 300+ digital services. Navigation was confusing, redundant, and department-driven.
40% task abandonment
Confusing category labels
Navigation by departments, not user tasks
Arabic-English language mismatch
Reducing confusion is expected to lower support tickets by ~25%
Research Approach
A 5-phase framework to discover, validate, and propose a user-driven IA.
Data derived from card-sorting sessions (N = 31 valid after cleaning; 4 invalid responses excluded).
EVIDENCE & INSIGHTS
High-Consensus Clusters: Enrollment → Grades → Journey → Records
Medium: My Account, School & Staff
Low: User Management, Golden Visa, Wellbeing
Key Insight: Users group by tasks, not departments
HYBRID IA PROPOSAL
Impact & Outcome
REFLECTION & LEARNINGS
Balancing user data, organizational politics, and design practicality was key.
Quantitative data helped depoliticize decisions.
Next time, I’d prototype IA early using Tree Testing.
🧰 Tools
Optimal Workshop, Excel, Miro
👥 Stakeholders
KHDA Digital Transf, IT,Education
⏱ Duration
4 Weeks
🌍 Limitation
UAE-based participants only
“Next → TDRA UX Lab”
“Eye-tracking + FaceReader uncovered hidden friction in UAE PASS.”