• In the initial phase of my research, I examined the navigation systems and maps at various public spaces and institutions, such as museums, shopping malls, university buildings, subway stations, and grocery stores.


• I noticed that maps of most museums, shopping malls, and university buildings rely heavily on assigning numbers to different areas within the space. Grocery stores use different colors to differentiate between different food sections and aisles.


• I also attended a symposium, Making the Inclusive Museum, by the Architectural League. At this event, members of JSA/MIXdesign shared the MIXmuseum Study and the conflicting inclusive design challenges they faced at the Queens Museum. I skimmed through their research document, which guided some of my design decisions for symbols and museum maps, such as gender-inclusive icons, keeping linguistic diversity in mind, and avoiding the usage of too many QR codes.

My project centers on two categories of museum visitors, New Yorkers and tourists, as museums attract diverse visitors daily. I applied different observational research methods, such as photo study, think-aloud protocol, and behavioral mapping, to understand visitor frustrations and goals. I used the data collected from these research methods and secondary research to redesign navigation maps, signage and symbols, and artwork descriptions.

• Photo Study
  I visited the MET to take photos of signage, maps, current exhibitions, and popular spots. After the shadowing method, I revisited my photo study to take more pictures to document observations made by my research participants. Later, I created a zine to present the obstacles, positive visitor experiences, and feedback.





• Shadowing and Think-Aloud Protocol
  I recruited three first-time MET visitors to carry out the think-aloud protocol method. I visited the museum separately with each participant and asked them to walk around at their own pace while assuming I was their shadow. They were asked to describe their observations, thoughts, and reactions verbally. Meanwhile, I took notes of their experience. My note-taking method had five categories: location, time, observations, and quotes.
  
  
  
  
  Observing visitors from diverse cultural backgrounds and artistic viewpoints was an exciting experience that made me experience the museum in a new way. I witnessed pain points I hadn’t noticed during my solo photo study visit. A shadowing method approach was a great idea as I could collect a lot of data, which I later used in different coding methods. Later, I used the data collected to lay out position and behavioral maps.


• Behavioral Mapping
  The behavioral maps were used to identify which parts of the museum each participant visited and for how long. This helped me understand why each participant spent more time in one section than the others. In the follow-up interview, I learned that two out of three participants like to check out artwork or artists they are interested in or already familiar with. One also mentioned visiting museums to learn about her cultural history. One of the participants was an artist who likes to visit museums for inspiration and to check out new artwork or artists she is unfamiliar with.





• Position Maps
  These position maps support my finding that visitors faced difficulty finding the ticket counter and spent most of their time with artwork that was most familiar to them or most inspirational.

NYU’s fine arts museum, the Grey Art Museum, has no maps or guides, which is something I wanted to design for this space. Even for a smaller space, I believe a map will be helpful and can work as a filter for visitors if they only visit for specific artwork or artists.

• It is a fine arts museum, which is something I find exciting and fun;


• There are enough areas and challenges (such as navigation, translations, and visual descriptions) for me to explore and try to fix;


• It is not too big, and the feasibility of developing an AR navigation system with cost-friendly technology will be manageable.

• The main challenge with this project was the AR navigation system, as I decided to use Snap AR’s Lens Studio software, which has several limitations (for example, we cannot scan large indoor spaces).


• Going into the project, I assumed I would just have to redesign an existing museum map, but the Grey Art Museum does not already have a map, so I had to design the map from scratch.


• I aimed to make the museum experience linguistically inclusive, so I translated the description texts and information into different languages. Since I only speak and understand three languages, I needed help to carry out this part of the project. I ended up utilizing AI, specifically ChatGPT, for the translations.

The primary aim of this project is to make the visitors feel included in the museum experience and improve the wayfinding or navigation system. Through this project, I want to highlight the scope of cost-friendly and easy-to-use technologies to improve museum experiences. This project will provide a direction and framework for museums and galleries to apply to their spaces to offer an inclusive museum experience to visitors regardless of their socioeconomic, cultural, or linguistic background. Thus, I present enhancements that only require a smartphone to access all the information, museum maps, and wayfinding tools.

• I designed multiple museum maps to improve the visitor experience and help them find their way around the space. I acknowledge that some visitors prefer to find their way around alone. Thus, the main museum map only shows the basic layout of the museum and other vital areas, such as the restroom, benches, information desk, and museum store.


• However, many visitors need help or clarification in museums and more directions to find their way around; the other three maps use different approaches to highlight a suggested route. I identified the suggested route based on the year the artworks were made and the description that presents the initial context of the artist and artwork. For example, if there are two artworks by the same artist, it would be more helpful to first read the description label that provides the artist's background instead of the label that just lists the name of the artwork.


• Finally, the final map uses numbers to represent the artists whose works are displayed at the museum. Visitors can search for the artist's name from a list and find them on the map. This map was designed based on the feedback that some friends and research participants shared, that sometimes they only go to a museum to check out a specific artwork or exhibition.


• The ‘Salon’ section of the map does not have any numbers as there are over 40 artworks in that space, which makes the map look cluttered. The museum has two corners where visitors can find the maps for the ‘Salon,’ I have highlighted those corners using map icons.

• Most of the signage and symbols at the Grey Art Museum were inclusive and accessible. However, there is a need for braille signage on walls and gender-inclusive symbols. For the museum map, I used a ‘toilet’ symbol instead of gendered ‘man/woman’ symbols to represent all-gender restrooms.


• At the Give Me a Sign: The Language of Symbols exhibition in Cooper Hewitt, I learned that most visitors prefer representational symbols and icons instead of abstract symbols; this also supported my primary and secondary research findings. Thus, in my designs, I used representational symbols (for example, the bench in the above museum maps) to tackle linguistic diversity and meet universal symbol needs.


• I researched more about universal iconography and language only to realize that it’s not a reality, no matter how hard we try to believe it. Icons are also like a foreign language, and they, too, take birth from existing languages—usually English. I concluded that running behind a ‘universal iconography’ solution is not the best choice. The better path is to try to make graphics and icons less abstract and more representational so it’s more intuitive for visitors.

• To develop an AR navigation system, I used Lens Studio and Polycam. I scanned the museum's indoor space with Snapchat’s Custom Location Landmarker tool, which utilizes LiDAR technology. Due to the limitations of the technology, I had to scan different rooms or sections of the museum separately, and then I combined them in the software with the help of the Polycam scan.


• I used Mixamo to download a 3D character with a walking animation. The character is an obj file that I put into the scene, and I used Lens Studio’s TweenManager to make the character move from one point to another. This character works as a guide that takes the visitor around the museum along the suggested route (as shown in Figure 10). Visitors can easily access this AR navigation on their smartphones by scanning the code on Snapchat.

• The Grey Art Museum does not have tickets as it is free to the public, so there was no way to identify the most spoken languages by the visitors. I used the data from the NYC Consensus to determine the most spoken languages in the city and the neighborhood, as the associate director mentioned that most visitors are locals living in the neighborhood. Thus, I translated all the prominent description labels and nine artwork description labels into four languages: Hindi, French, Spanish, and Chinese.


• At first, I tried using language translation APIs (mostly Google Translate API because only that has all these languages available); however, after implementing them, I realized the translations were inaccurate. The major issue with the translations was that they lacked context and output literal translations that didn’t make sense.


• I was frustrated for many hours trying to figure out a way to fix this, and in the process, I forgot that my user is not technology but the people visiting the museums. Trying to fit my problem into a technological solution wasn’t the way forward. So, I realized the best user experience will be designed with the users, by translating the information manually. I translated a lot of the Hindi text myself, but eventually, I used ChatGPT-4 for my translations. I still had to verify all the AI-generated translations. The Hindi translations had no factual errors; they sometimes used different words to convey the same meaning.


• I chose French due to the exhibition's theme, i.e., “Americans in Paris,” while Spanish and Chinese are two of the most spoken languages in NYC.

For the visual descriptions of nine paintings, I used ChatGPT-4. I had to explicitly ask it not to interpret the painting but to describe what is visible. Then, I translated these visual descriptions into four languages. I had to edit the visual descriptions to remove any interpretations left by ChatGPT.

The website brings all the elements together, i.e., information about the exhibition, information about the museum, information about artists, museum maps, AR navigation, translations, and visual descriptions. For this project, I designed the high-fidelity prototype of the website, which has the layout and UI of an app, using Figma.

• This project highlights the need for inclusive museum experiences and the techniques or methodologies that can be applied to make museums more fun, accessible, informative, and easy to navigate. This project provides a framework and approaches for achieving these goals at art galleries and museums. I believe this project is important because everyone should have equal access to art, and visitors should not feel bored, frustrated, or dumb at museums. A museum should be a fun and easy place to learn about art and history.


• Next Steps: I plan to get visitor feedback on these museum maps, translations, visual descriptions, and AR navigation and to check if they spend more time trying to learn more about the art after the intervention of these elements and designs. At the end, with the help of a survey, I will check if the overall visitor satisfaction increases or frustration increases.