Argo is an augmented reality application that helps people to learn a new language by challenging them to identify objects around them in the language that they want to learn. It facilitates peer-to-peer learning that is engaging, fun and takes advantage of user’s environment.

3 months

Adobe XD - Design and Prototyping - Usability Testing
Adobe Indesign - Final Report
Adobe After Effects - Video Prototype
Keynote - Presentation Deck
Qualtrics - Survey
Excel - Data Analysis
Asana - Project Management

Mona Mishra(Me) - Researcher and Designer
Tim Salau - Researcher and Designer
Weixuan Fu - Researcher
Han Han - Researcher
Shih-Tsai Wei - Researcher and Designer


Our brain stores visual information in a way that is easy to recall because visual images have more things that we instantly associate with and hence, that connection makes the information more memorable and easy to recollect. In this day and age where people rely heavily on smartphone and smart devices to learn independently, mobile applications like Duolingo, Babble and Rosetta Stone have made tremendous progress in the eld of language learning. They have taken advantage of visual memory to help users learn a new language that requires very less e ort. They use the vector images of food, people and items that most users are familiar with, and connect them with the word in a foreign language. Although, they have made the language learning process far easier than before, they still fail to engage most users for a longer period of time. We recognized this gap and made use of the principles of contextual augmented reality to engage and motivate users to construct their knowledge during real-world observation.

The popularity of augmented reality applications has been increasingly recognized, especially in the field of education, because it has made possible for virtual objects to co-exist in the real environment. This has made it easy for learners to visualize concepts and spatial relationships that cannot be easily realized or enacted. With the help of pattern recognition, an application can be triggered to do something. Argo recognizes images as patterns and triggers the application to identify its label with the help of computer vision technology. We have also used the concepts of gamification and the process of peer-to-peer learning in order to increase engagement.




Given the technical challenge we had, we needed to investigate current Computer Vision technology to and the feasibility of realizing the app. We concluded the requirements as below:

As we were investigating for requirement (a), we found that there were already some apps in the market that had implemented this functionality, for example, CamFind. This application takes a picture of an object and within seconds provides us with the best guess for that object. Hence, we realized that there aren’t many technical barriers for implementing requirement (a), as there already exists a mature product in market that has the functionality.
There are some open source object recognition APIs, like TensorFlow and Yolo, that demonstrates the basic feasibility that resolved our requirement (b), for real time object recognition.


Argo has three main users groups, namely casual language learners, gamers and travellers.



  • Need to learn a new language when they move to a place where most people speak in a different language.
  • Some others said that it was a mandatory course in college. Motivated due to a TV shows or sports commentary.
  • Duolingo is the most popular language learning app because it is easy to learn and teaches language from scratch
  • Apps don’t provide in depth knowledge
  • Too many reminders and same kinds of questions
  • There is no one to practice the language with.


Before jumping into any design tool, our team decided to start with storyboarding and diagramming what we wanted the Argo experience to be like for our users. When we conducted initial interviews with users, we learned that people enjoy language learnings apps that kept them engaged, was easy to learn, and allowed them to track their daily progress. In addition, we discovered that some of the biggest challenges to learning a new language for people was nding the time, staying engaged throughout gameplay. Feedback from our interviews also indicated that people are motivated to learn a new language based on job-related goals, if they are traveling and want to learn more about culture, or if they are learning a new language for school.


Storyboarding and sketching allowed each individual member of our team the opportunity to articulate and share their vision of Argo.


From this point on, we moved forward towards wireframing the design for the following task flows: app sign-up, setting language preference, exploration mode, browsing through the gallery, playing round types, and finding nearby friends. Then we created functional prototypes and a test plan, where we had users atempt to complete set tasks and talk aloud while completing those tasks.


The purpose of this testing was to garner feedback from users and evaluate what they find confusing or delightful about the app. By utilizing, we were able to complete 3 rounds of user testing with around 20 participants. We outlined 7 tasks and some follow up questions after each task and a few post-test question. We noted the time taken by them to complete the task, their difficulty level for performing each task.


  • Prototype should be made more efficient or the task should be a little more detailed.
  • Matching should be in less number of steps.
  • ‘Get Started’ button was confusing.
  • For a great AR experience, homepage should start with a camera.
  • Change nearby friends to ‘invite nearby friends to play’ and change ‘other friends’ to ‘all friends’


  • Make the “start game” button look more prominent by changing colors or adding icons to it.
  • Could have some instructions about the tap and tap matching method before start the game
  • The label should be shown on the image after successfully matched instead of disappearing
  • Change the hamburger menu


  • Finding Round 1 was difficult with this prototype, hence all the following tasks became difficult. But other than that there were no other difficulties with the game
  • Make the tips button bigger and more prominent
  • Tutorial for on-boarding


Please follow this link for the working prototype


Cultural Strategy Designer