De-Risking Navigation for a National Education Platform

De-Risking Navigation for a National Education Platform

Validating information architecture decisions with real user evidence

Validating information architecture decisions with real user evidence

Company

Government (NZ)

ROLE

UX/UI Designer

duration

3 Months

KEY IMPACT

✓ Validated navigation structure across fiver user groups, enabling the team to ship with confidence rather than assumption

✓ Validated navigation structure across fiver user groups, enabling the team to ship with confidence rather than assumption

✓ Reduced navigation friction by clarifying mega-menu pathways, supporting faster and smoother content discovery

✓ Reduced navigation friction by clarifying mega-menu pathways, supporting faster and smoother content discovery

✓ Enabled the content team to make navigation decisions backed by data, rather than assumptions

✓ Enabled the content team to make navigation decisions backed by data, rather than assumptions

✓ Reduced long-term navigation risk by restructuring the top navigation to accommodate future Level-1 content growth

✓ Reduced long-term navigation risk by restructuring the top navigation to accommodate future Level-1 content growth

TL;DR

The Education Workforce website is a new site to replace the legacy TeachNZ platform. It connects aspiring teachers, overseas applicants, and school principals to government-funded scholarship, relocation grants, and workforce programs to address NZ's teacher shortage.

The Education Workforce website was created to replace the legacy TeachNZ platform, with the goal of making education-related information easier to find, understand, and keep up to date for a wide range of users.

Problem

By the time I joined the project, an initial round of IA testing had been conducted, but with non-representative participants - leaving the team uncertain whether the structure would hold up for real users.

By the time I joined the project, the initial site design had already been completed and implementation was about to begin. However, questions remained about whether the information architecture truly reflected how real users looked for information.

Early IA tests were conducted but used non-representative participants, which limited confidence in the results. As a result, the team faced uncertainty about whether the existing structure would support clear navigation once the site went live.

To reduce the risk of shipping an unvalidated structure, the team decided to conduct a second round of IA testing with representative user groups, ensuring the right people could actually find what they came for.

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MY ROLE

  1. Lead structured information architecture testing

    I conducted tree test with five distinct user segments, each with tailored scenarios representing their specific information needs.

  1. Lead structured information architecture testing

    I conducted tree test with five distinct user segments, each with tailored scenarios representing their specific information needs.

  1. Analysis and translate IA testing insights into design guidance

    Over 300 participants participated and submitted their results.

  1. Analysis and translate IA testing insights into design guidance

    Over 300 participants participated and submitted their results.

  1. Make UX/UI iteration alongside website implementation support

    I worked closely with cross-functional Agile delivery team to ensure design-product-alignment and made UI changes when needed

  1. Make UX/UI iteration alongside website implementation support

    I worked closely with cross-functional Agile delivery team to ensure design-product-alignment and made UI changes when needed

  1. Execute UX quality assurance and accessibility validation

    Conducted user acceptance testing (UAT) and accessibility reviews to ensure the final experience met usability and inclusive design expectations for diverse user needs.

  1. Execute UX quality assurance and accessibility validation

    Conducted user acceptance testing (UAT) and accessibility reviews to ensure the final experience met usability and inclusive design expectations for diverse user needs.

Outcome

The tree testing findings were delivered as a structured report to guide the content and product team's decisions on information labelling and organization.

IA Testing

Over 300 validated data points provided actionable confidence for structural and language changes.

Over 300 validated data points provided actionable confidence for structural and language changes.

Tree testing results by audience

Structure navigation failure points

Separately, I made targeted UI iterations to the navigation and mega-menu driven by UX principles for findability and future content scalability.

Navigation Iteration

Redesigned the top navigation to accommodate the new site name and allow for future Level-1 content growth without breaking the hierarchy

Redesigned the top navigation to accommodate the new site name and allow for future Level-1 content growth without breaking the hierarchy

Redesigned the top navigation to accommodate the new site name and allow for future Level-1 content growth without breaking the hierarchy

Before

AFTER

Mega-menu Iteration

Refined to reduce cognitive load with fewer simultaneous choices and clear grouping, supporting faster pathway-finding.

Refined to reduce cognitive load with fewer simultaneous choices and clear grouping, supporting faster pathway-finding.

Before

After

Constraints

Two rounds of tree testing with 5 user groups produced large datasets. While the first analysis established a solid reporting result, the second round needed to be completed with half the time available, this created pressure on me to deliver the IA report and design recommendations on time, without compromising the quality of analysis.

Two rounds of tree testing with 5 user groups produced large datasets. While the first analysis established a solid reporting result, the second round needed to be completed with half the time available, this created pressure on me to deliver the IA report and design recommendations on time, without compromising the quality of analysis.

Two rounds of tree testing with 5 user groups produced large datasets. While the first analysis established a solid reporting result, the second round needed to be completed with half the time available, this created pressure on me to deliver the IA report and design recommendations on time, without compromising the quality of analysis.

Response:

To manage this, I prioritised tasks for the week, broke the analysis into clearly defined tasks, and onboarded additional support using the previously established workflow. This allowed us to work in parallel and delivered clear, actionable insights on time.

Next Step

For a site where users are making high-stakes career decisions, combining analytics with card sorting and periodic tree testing would catch navigation drift as new content are added to the site over time.

Emma W

thanks for stopping by

©2026 by Emma Wang

Emma W

thanks for stopping by

©2026 by Emma Wang

Emma W

thanks for stopping by

©2026 by Emma Wang