University of Richmond Library IA Evaluation
Boatwright Library partnered with Pratt’s Digital Experience Center to evaluate and improve its website navigation.
Duration
1 Month
Client
Jane, Shaelyn, Cherry, Shane
Tools
Role
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UX Research
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Information Architecture

Testing the IA Through Real Student Journeys
We used two complementary methods: moderated usability testing on the current website and tree testing on the proposed IA. The moderated test helped us understand why users struggled in the existing structure, while the tree test helped us validate whether the new IA improved findability without relying on visual design, page content, or search.
To evaluate the experience, we tested five core library journeys:
Research Discovery — finding research materials and subject-based resources
Borrowing & Delivery — requesting books and understanding delivery options
Study Spaces — finding and reserving a room
Events & Programs — locating Peple Lecture information
Wayfinding — finding the Parsons Music Library map
Where Students Got Stuck in the Existing Navigation
The current IA often made users work harder than expected. The information was usually there, but the path to it was not always clear.
For research tasks, users were more confident when they could rely on search, but browsing through navigation felt less predictable. Book request and delivery tasks also lacked a clear action path: users expected direct options like request, delivery, or item retrieval, but often encountered policy-style information instead. Room booking had a similar pattern. The feature existed, but users had to interpret labels like “study zones,” “study rooms,” and “facilities” before knowing where to go.
The broader issue was not simply that users were lost. It was that the IA often required users to understand library terminology before they could complete student-centered tasks.
What We Saw In The Proposed IA
What Improved:
The clearest improvement was physical-space navigation. In the old IA, space-related tasks were buried under broad labels like “Library Services.” In the new IA, they were grouped under “Libraries & Spaces,” which users recognized more easily.
This worked best for room reservation: 100% of participants first clicked “Libraries & Spaces,” and the task had the highest success rate at 71%.
What Still Needed Refinement:
The new IA improved where users started, but not every workflow was easy to complete. Overall tree test success was only 34%, showing that several journeys still needed work.
Research materials had 14% success, borrowing workflows had 43% success, and Peple Lecture had 29% success. Even room reservation, the strongest task, still needed clearer action cues since only 57% completed it directly.
What I Learned.
This project showed that IA is not just about where content lives. It is about whether users can predict where content should live.
The proposed IA made one important step forward by improving physical-space navigation. But the study also showed that research support, borrowing workflows, event discovery, and wayfinding still need clearer, more student-centered pathways. A stronger IA should help users move from goal to action without needing to understand the library’s internal structure first.
