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Robots & Runes

Information Architecture Redesign

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1.

Overview

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Introduction, Goals, and Personas

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Introduction

The Problem

Robots & Runes is a web guide to Hugo and Nebula award-winning science fiction and fantasy literature. While the site offers rich content, its current information architecture creates friction for users trying to:

  • Discover new books
  • Filter by preferences
  • Understand award systems
  • Navigate efficiently across devices

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Users Experience:

  • Scattered award information
  • Overwhelming filtering interfaces
  • Unclear navigation pathways

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Our Goal

Redesign the site’s information architecture to:

  • Improve discoverability of books

  • Streamline filtering and browsing

  • Clarify award-related content

  • Support casual and research driven users

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Core Content Areas:

  • Book discoverability and filtering system

  • Hugo and Nebula award information

  • Blog content area

  • About and support content

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Personas

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Personas

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Personas

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2.

Testing Process

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Content Inventory, Card Sort, and Tree Test

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Test Overview

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Content Inventory

Card Sort

IA Testing (Tree Tests)

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We documented all of the existing content on the site and then performed a content audit.

We conducted a pilot test and two formal rounds of testing to better understand how to organize the content on the site.

We conducted a pilot test and two formal rounds of testing to examine if users would be able to complete specific tasks.

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Content Inventory

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Process

We conducted a full audit of the existing site:

  • Identified all pages and navigation elements

  • Grouped content by type (books, awards, etc)

  • Documented any redundancy and inconsistencies

Key Findings

  • Duplicate pathways to similar content

  • “Buying Guide” overlapped with book filtering

  • Award information fragmented across pages

  • Navigation labels unclear or inconsistent

Actions Taken

  • We consolidated overlapping sections (Books + Buying Guide)

  • Removed redundant navigation paths

  • Clarified labeling (“Not sure where to start?” to “Find Your Next Epic Read”)

  • Identified dynamic vs. static content

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Card Sort: Overview

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Methodology

  • Closed card sort
    • Refined categories across rounds

  • Conducted using UXtweak

  • 3 total rounds:
    • Pilot
    • Round 1
    • Round 2

Participants

  • Pilot: 2 respondents

  • Round 1: 5 respondents

  • Round 2: 5 respondents

  • Total: 12 respondents

Cards & Categories

  • 15-20 content items (navigation labels, features, and pages)

  • Categories evolved each round based on respondents’ mental models

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Card Sort: What We Tested

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Card Sort Goal:

The goal of our card sort was to understand how user’s naturally group book discovery tools, awards content, blog content, and informational content.

Key Questions:

  1. Where do users expect to:
    1. Find books
    2. Learn about awards?
    3. Read articles?

  1. Do labels match user expectations?

  1. Are any items confusing or ambiguous?

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Card Sort: Results

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Pilot Findings

  • High inconsistency
    • 7 categories

  • Major confusion
    • “Not Sure Where to Start?” → Unclear to all respondents

  • Mixed mental models
    • Navigation, content, and external links grouped together

This told us that labels were unclear and site structure did not reflect user expectations

Round 1

What improved?

  • More consistent grouping:
    • Books
    • Awards
    • Blogs
    • About This Site

New issues identified:

  • Blogs became a catch-all category (12 items)
  • “Not Sure Where to Start?” grouped under About This Site
  • External links category wasn’t working

Users tended to group unclear items into vague categories

Round 2

What Changed?

  • Refined cards:
    • Not Sure Where to Start → Find Your Next Epic Read
    • Reviews → Critic Reviews
    • Get Book Recommendations → Find Books By

Results

  • Strong agreement:
    • Awards content 100% grouped together
    • Books and Blog more clearly defined

Users shared a consistent mental model.

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Card Sort: Changes Across Rounds

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Iterations

  1. Label Refinement
    1. Removed vague phrasing
    2. Used action based labels (Find Books By)

  1. Category Consolidation
    1. Reduced redundant categories
      1. Groups Hugo & Nebula Awards
      2. We went from having 7 categories to having 4.
    2. Defined clear top level navigation structure

  1. Removed External Links category and cards
    1. Moved to footer
      1. Based on user behavior

  1. Separated content vs. tools
    1. Blog does not equate to book discovery
    2. Find Your Next Read (recommendation quiz) does not equate to filtering

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IA Testing (Tree Tests): Overview

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Methodology

  • Conducted using UXtweak

  • 3 Rounds:
    • Pilot
    • Round 1
    • Round 2

Participants

  • Pilot: 4 respondents

  • Round 1: 6 respondents

  • Round 2: 6 respondents

  • Total: 16 respondents

Goal

  • Evaluate whether users could successfully navigate the site map to complete key tasks

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IA Testing (Tree Tests): Tasks

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Tasks we tested:

Task 1: Book Discovery (Filtering)

Find a book using filters (genre, theme, etc) and view a result (in rounds 2,3).

Task 2: Awards Information

Find background information about the Nebula Awards.

Task 3: Blog Content

Find an article comparing a book to its film adaptation.

Task 4: About This Site

Find information that explains the purpose of the site.

Task Level Insights:

Task 1 - Filtering

  • Pilot: 25% success → Major failure
  • Round 1: 100% success → Resolved
  • Round 2: 83.3% success → Minor friction

Clearer labeling: Find Books By → Browse by Category → Browse & Filter Books

Task 2 - Awards

  • Strong performance across all rounds
  • Round 2: 100% success

Task 3 - Blog Content

  • Users expressed confusion in the pilot between Books vs Blog
  • Round 1 and Round 2: 100% success

Task 4 - About This Site

  • Pilot: 75% success
  • Round 1: 83.3% success
  • Round 2: 66.7% success
  • Users tended to explore multiple paths

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IA Testing (Tree Tests): Results

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Pilot Findings

Overall Performance:

  • 70.6% success rate
  • 58.5% directness

Key Issues:

  • Filtering Task → 25% success rate
  • Users confused the recommendation quiz for filtering
  • Blog vs Books
  • High backtracking and looping behavior

Takeaway:

Navigation structure was inconsistent and unclear.

Round 1

Overall Performance:

  • 91.7% success rate
  • 79.2% directness

Successes by task:

  • Filtering → 100%
  • Blog → 100%
  • Awards → 83.3%
  • About → 83.3%

We improved labeling, had better category separation, and stronger first click accuracy.

Takeaway:

IA changes led to usability improvement

Round 2

Overall Performance:

  • 87.5% success rate
  • 54.2% directness

Successes by task:

  • Filtering → 83.3%
  • Blog → 100%
  • Awards →100%
  • About → 66.7%

Observed issues:

�Users tended to loop between the recommendations quiz and filtering. Some users took indirect paths leading to less directness.

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3.

Site Map

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Annotated Site Map and Description

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Site Map: Structure & Strategy

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Structure Overview

Top Level Navigation:

  • Home

  • Books

  • Hugo & Nebula Awards

  • Blog

  • About This Site

Key IA Decisions

  1. Centralized filtering system
    1. The site revolves around: Browse & Filter Books.

  1. Introduced page types
    1. Filter interface (Browse & Filter Books)
    2. Preset filter pages (Quiz Results, Explore Winners)
      1. All routes feed into the same filtering system

  1. Simplified Navigation
    1. Merged Hugo and Nebula into one category
    2. Removed redundant pathways
    3. Standardized naming across the site

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Site Map: Evolution & Revisions

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Draft #1

  • Overuse of pillar pages → Flat hierarchy
  • Award content split across multiple entry points
  • Confusing distinction between “Book Guide” and “Book Page”
  • No representation of filtering or dynamic content

Result: Too many navigation choices and no starting point for book discovery.

Draft #2

  • Consolidated into core categories:
  • Books, Awards, Blog, and About

  • Introduced structured content:
  • Book Pages
  • Blog Categories

  • Reduced redundant navigation paths

Remaining issue: The filtering system is not clearly defined.

Final Sitemap Revisions

  1. Centralized filtering system
  2. Introduced page types
  3. Consolidated award structure
  4. Refined labels from testing
    1. Not Sure Where to Start? → Find Your Next Epic Read
    2. Reviews → Critic Reviews

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Site Map: Iteration & Testing Impact

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Content Inventory

The findings from our content inventory revealed duplicate pathways, fragments award content, and unclear labels.

When refining the sitemap, we focused on consolidating and creating a clearer structure.

Card Sort Insights

  1. Simplified top level navigation based on the consistent grouping in our Round 2 card sort.

  1. Replaced confusing labels that were revealed in our Pilot card sort.

  1. Removed external links from the IA since users treated them separately in our Round 1 card sort.

  1. Introduced system-based structure since users groups discovery tools like the recommendation quiz under books.

  1. Structured the blog content to fix the catch-all blog issue from round 1.

Tree Test Insights

  1. Prioritized filtering as a primary entry point as a result of the confusion we seen in our pilot test.

  1. We separated the discovery paths. The quiz does not equal filtering. This reduces the looping behavior we saw in Round 2 of our testing.

  1. Simplified award navigation by grouping Hugo & Nebula with clear hierarchy. This had a 100% success rate in Round 2 of testing.

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4.

Wireframes

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Tasks and Annotated Wireframes

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WIREFRAMES

Process

Challenges

Success

Our wireframing process was highly iterative and grounded in research at every stage.

We used insights from our heuristic evaluations, content inventory, usability testing to continuously inform design decisions. These methods helped us identify usability issues, gaps in structure, and pain points, which we translated into tangible design changes in our wireframes. Each iteration allowed us to refine, improve, and better align with user expectations.

We selected tasks to wireframe based on areas where users experienced most friction or confusion.

A key limitation was the inability to conduct prototype testing on our wireframes. We couldn’t observe how users interacted with our proposed designs or validate them. While our design decisions were informed by prior research, it lacked the final feedback that helps refine interaction details.

Our wireframes were effective because they were directly rooted in user data.

  • We streamlined navigation and reduced cognitive load
  • We improved consistency in labeling and structure, which helped users better predict where to find information

Our iterative process resulted in designs that more closely matched users’ needs.

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Task 1

You want to browse books and narrow the results by genre, subgenre, decade, theme, and awards. How would you go about applying filters? Then select a book you’d like to learn more about.

WIREFRAMES

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Task 2

You’re writing a paper and want to learn more about the Nebula Awards and their background. Where would you find information about the Nebula Awards?

WIREFRAMES

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6.

Retrospective

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Overall Process

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Retrospective: Process & Learnings

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What We Learned:

Throughout the project, our team gained a better understanding of how users’ mentally organize content. Particularly regarding book discovery tools like the recommendation quiz vs. filtering and the difference between content and features like Blog vs. Books. We developed experience conducting iterative IA testing; completing a content inventory, card sorting, and tree testing. This process emphasized how even small changes in labeling can significantly impact user success and usability.

What We Would Change:

If we were to approach this project again, we would increase the number of participants in our testing to strengthen the reliability of our data. We would also conduct moderated testing or interviews to better understand what users made certain navigation choices. Lastly, we would refine the relationship between filtering and recommendation tools earlier on, since this confusion persisted in our later rounds of testing and impacted efficiency.

Reflection:

This project reinforced the idea that effective information architecture requires continuous testing and iteration. Our final project design reflects a system that is user centered and data driven. From our work on this project, we have learned how to design not just for organization but for discovery and efficiency in order to ensure that users can easily navigate and explore the site.

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Appendix

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1.0 Content Inventory

Content that exists on the current version of the site: https://robotsandrunes.netlify.app

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1.1 Card Sort Raw Data

Pilot Test

Categories: 7

Cards: 21

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1.1 Card Sort Raw Data

Round 1

Categories: 6

Cards: 10

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1.1 Card Sort Raw Data

Round 2

Categories: 4

Cards: 16

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1.2 Heuristic Analysis

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Page 1

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1.2.1 Heuristic Analysis

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Page 2

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1.2.2 Heuristic Analysis

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Page 3

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1.2.3 Heuristic Analysis

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Page 4

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1.3 IA Testing Raw Data

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Task 1: You just finished reading a sci-fi novel and want to find another award-winning book, but you’re not sure what to read next. You want to find a fantasy novel for your next read. Where would you go to filter only for fantasy novels?

Correct Answer: Books → Find Books By

Directness

Median Time Taken (measured in minutes)

Pilot Test

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1.3.1 IA Testing Raw Data

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Task 2: You’re writing a paper and want to learn more about the Nebula Awards and their background. Where would you find information about the Nebula Awards?

Correct Answer: Hugo & Nebula Awards → Explore Nebula History

Directness

Median Time Taken (measured in minutes)

Pilot Test

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1.3.2 IA Testing Raw Data

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Task 3: You recently watched a sci-fi movie and heard it was based on a book. You want to read an article comparing the original book to the film. Where would you go to compare books and film adaptations?

Correct Answer: Blog → Book vs. Fim Adaptations

Directness

Median Time Taken (measured in minutes)

Pilot Test

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1.3.3 IA Testing Raw Data

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Task 4: You just discovered Robots and Runes and want to understand its purpose and who created it. Where would you find information explaining what the site is and why it exists?

Correct Answer: About This Site → Where Did This Site Come From?

Directness

Median Time Taken (measured in minutes)

Pilot Test

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1.3.4 IA Testing Raw Data

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Task 1: You want to browse books and narrow the results by genre, subgenre, decade, theme, and awards. Where would you go to apply filters?

Correct Answer: Books → Browse by Category

Directness

Median Time Taken (measured in minutes)

Round 1

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1.3.5 IA Testing Raw Data

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Task 2: You’re writing a paper and want to learn more about the Nebula Awards and their background. Where would you find information about the Nebula Awards?

Correct Answer: Hugo & Nebula Awards → Explore Nebula History

Directness

Median Time Taken (measured in minutes)

Round 1

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1.3.6 IA Testing Raw Data

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Task 3: You recently watched a sci-fi movie and heard it was based on a book. You want to read an article comparing the original book to the film. Where would you go to compare books and film adaptations?

Correct Answer: Blog → Book vs. Film Adaptations

Directness

Median Time Taken (measured in minutes)

Round 1

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1.3.7 IA Testing Raw Data

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Task 4: You just discovered Robots and Runes and want to understand its purpose and who created it. Where would you find information explaining what the site is and why it exists?

Correct Answer: About This Site → Where Did This Site Come From?

Directness

Median Time Taken (measured in minutes)

Round 1

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1.3.8 IA Testing Raw Data

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Task 1: You’re interested in books about artificial intelligence and want to find a book that explores this theme. Use filtering tools to narrow down the

books, browse the results, and view a book to learn more about it.

Correct Answer: Books →Browse & Filter Books →Book Page

Directness

Median Time Taken (measured in minutes)

Round 2

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1.3.9 IA Testing Raw Data

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Task 2: You’re writing a paper and want to learn more about the Nebula Awards and their background. Where would you find information about the Nebula Awards?

Correct Answer: Hugo & Nebula Awards → Nebula Awards → Explore Nebula History

Directness

Median Time Taken (measured in minutes)

Round 2

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1.3.10 IA Testing Raw Data

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Task 3: You recently watched a sci-fi movie and heard it was based on a book. You want to read an article comparing the original book to the film. Where would you go to compare books and film adaptations?

Correct Answer: Blog → Books vs. Film

Directness

Median Time Taken (measured in minutes)

Round 2

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1.3.11 IA Testing Raw Data

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Task 4: You just discovered Robots and Runes and want to understand its purpose and who created it. Where would you find information explaining what the site is and why it exists?

Correct Answer: About This Site → Where Did This Site Come From?

Directness

Median Time Taken (measured in minutes)

Round 2

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2.0 Site Map Draft #1

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2.1 Site Map Draft #2

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2.2 Site Map Final

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3.0 Task 1 Wireframes

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3.1 Task 2 Wireframes

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