Ursa Coding
A More Efficient Way to Learn Professional Coding with AI
Coding has become an essential subject in K-12 education. Yet, transiting from fun block-based languages to professional text-based environments can be challenging. Many young students struggle with concepts or debugging, and needs real time, personalized support. However, not every child has access to the resources for this tailored approach.
As the UX designer at UrsaTech, I collaborated with project managers and engineers to design UrsaCoding, an AI-powered tool that helps young learners tackle professional coding with customized content and real-time feedback.
Product Design
UX Research
Usability Testing
UX/UI Designers (Me!)
Product Managers
Engineer Team
Figma
FigJam
Adobe CS
2023
Provide customized coding education for K-12 students, make the learning more efficient and accessible for all.
The code editor's performance in the incremental feature release:
increase in User Satisfaction Rate
increase in Task Completion Rate
The platform's target user was K12 students (ages 6 - 18) who were beginner in coding or coders who wish to study text-based coding language. In order to craft a engaging coding learning experience for young learners, I need to first understand their learning habits, pain points, and needs.
After researching school curriculums in the United States, I found that computer science (CS) and programming have become essential components of K-12 education.
of public high schools in US offered foundational CS
of 5th to 12th grade students are interested in learning CS
of parents feel that to learn CS is good use of school resources
I looked at other youth coding learning platforms to see their approaches and features for young code learners.
Active Engagements
Leverage gamification elements, let users learn through various games and exercises.
Tutorials and Notes
Use interactive tutorial videos, code examples, and notes to guide through learning process.
Professional Code editors
Professional code editors features like code completion, debugging, and task running.
Make it fun
After the research on young audiences' learning habits and coding education market, the team's initial approach was to build active learning experience through hands-on exercises and gamification mechanisms.
Users will learn and master coding knowledge from practices. They will be given prompts to solve or design. Once users successfully solved the given challenges, they would collect points as rewards.
"I am stuck on this one question for an hour, and then I just give up."
In order to fully understand users' biggest needs and frustrations during their learning experience, I crafted a user survey, asking young code learners about their experience on code learning. I recruited 90 participants in the process.
User Journey Map based on the survey results
The user survey results revealed that failed to identify and fix errors is the top reason that lead to frustration and lost of motivation.
The majority of users were looking for real-time guidance and support when they fail to debug or understand concepts.
After analyzing the results from primary research, I discovered that one of the most significant pain points was that users failed to identify errors and debug their code.
The team's initial approach was to use exercises and a reward system to keep users engaged. However, if users cannot write the correct code, they get stuck during their practice and cannot move forward, which leads to frustration and a loss of learning motivation.
Students need "someone" or "something" to answer their questions and help them identify their errors immediately to keep moving forward and staying motivated.
How might we provide real-time support and feedback to users?
The code editor's performance in the incremental feature release:
increase in User Satisfaction Rate
increase in Task Completion Rate
1. The team is progressing with the coding and structuring of the online editor.
2. Design onboarding experience for the editor to lower learning curve, especially for first time user.
3. Giving the AI assistant characteristics to help form more engaging learning experience.
4. The team is planning on extending the AI assistant functions over the entire platform's ecosystem, such as the teaching end (PPT and Quiz generation).
