Kinetica

Inspiration

The biggest inspiration for this project came from the frustration of trying to mentally visualize complex textbook problems while studying. Whenever I got stuck and asked ChatGPT or another AI for help, it would always spit out a dense block of text or a long paragraph. While that might give me the formula, it didn't help me see what the problem was actually asking.

I wanted a tool that could take a specific question and immediately run an interactive simulation tailored right to it. More than just finding the final number, I wanted to conceptually visualize how my answer—whether right or wrong—actually affects the whole system in general. Furthermore, practice problems online don't always match what a specific professor emphasizes, so I wanted a way to throw in my own textbook to practice with the exact style of questions that would actually show up on my tests.

What it does

The platform transforms static textbooks into interactive, visual learning environments for both high school and university students:

• Textbook-to-Simulation Ingestion: Users can upload their own textbook chapters or problems to generate custom study modules that match their professor's exact curriculum.

  • Theory Sandbox Mode: Instead of just reading static theory, students can interact with an open sandbox to manipulate variables and conceptually visualize how the underlying system behaves in real time.
  • Interactive Challenge Mode: Students solve practice problems pulled directly from their textbook material. When they plug in an answer, the simulation runs it—showing not only why the right answer works, but visually demonstrating what happens to the system if they input the wrong answer.
  • High School & University Level Toggle: To cater to different educational stages, users can seamlessly toggle explanations and conceptual depth between a High School Level (focused on core intuition) and a University Level (focused on rigorous theory and advanced math).
  • Real-World Connections: Every concept and problem is paired with practical, real-world examples so students understand how classroom theory applies outside of an exam.

How we built it

It was built using html, CSS and Vanilla JS. Initially, the planning occurred by bouncing ideas back and forth and further refining ideas to see which one would make a great product before the proceeding with the development with the stack

Challenges we ran into

There were some bugs that would have ruined the user experience if it were a live app such as the fact that it would just ignore the fact that the question is actually asking for the minimum and not at least along with the fact that there was also overlap in some of the UI. These were then discovered and corrected through thorough testing and getting the agent to iterate based on the feedback being received.

Accomplishments that we're proud of

A working prototype with little to no bugs currently known was able to be created that gives the app a direction and foundation to be able to build off of with the goal of making this widely available for everyone to use.

What we learned

Coding with AI agents involves iterating and going back to keep adjusting until the proper function or design has been achieved. You also need to be able to plan what you want to build as it makes whatever you end up building feel more complete and not like no thought was put into the product.

What's next for Kinetica

Next steps would be to create the import multiple textbooks along with being able to read, understand and process the context to be able to properly create the scenario for textbook concept. Then eventually moving to user accounts and login along with a community page to share insights and maybe textbooks.

Built With

• css3
• html5
• javascript
• vanilla