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CHAPTER THREE
To organize and analyze the indoor signage photos collected across all During the observation, I noted several issues:
buildings, I created a coding system. Each sign was labeled using the
1. There were no clear signs indicating which parking areas were
format: “Building letter + Floor number + Sign number”. For example,
available, causing drivers to circle around looking for spaces.
A1-01 refers to the first sign photographed on the first floor of Building
A. This system allowed for consistent tracking and easier quantitative
2. The overflow parking lot had no signage and was largely unused
analysis of signage distribution and types.
due to lack of awareness.
3. The school’s paper maps lacked clarity and detail, leading some
visitors to stand in front of signs for a long time before asking staff
for help.
4. The campus brochure didn’t connect building functions with
the map layout, making it hard to understand what facilities were
located where.
Figure 8 Coding rules for existing navigation
signs in the building
These findings helped me better understand how the campus
navigation system functions in real situations and where key problems
lie. It also became clear that users navigate in different ways: some
Observations on user navigation behavior during ask others, some use paper maps, and some rely on digital tools like
School Open day Google Maps. Relying on only one form of navigation may not meet
the needs of all users. Additionally, inconsistencies between different
On October 24, 2024, during the School Open Day, I conducted the systems — such as signage icons and digital map visuals — may cause
second field observation at SETU Carlow. My focus was on two main confusion and reduce navigation accuracy.
aspects: how drivers found parking, and how visitors navigated after
entering the campus.
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