Switch

Inspiration

Many students, especially those with dyslexia or reading challenges, are taught to memorize words instead of understanding how they are built. Structured Word Inquiry teaches students to analyze words scientifically by breaking them into bases, prefixes, and suffixes, but these tools are currently manual, slow, and difficult to scale. We wanted to make SWI interactive, visual, and accessible so that students can explore language in a more intuitive and engaging way.

What it does

Our software allows a user to upload a book or text and click any word to explore it in depth. When a word is selected, the system generates a word sum, identifies the base and affixes, and displays a word family matrix. The user can also view definitions, listen to the pronunciation of the word, hear the word broken down into syllables, and see a simple visual icon representing the concept. In some cases, the user can also access an AI-generated explanation of the word’s history or etymology. The goal is to turn reading into an interactive learning experience that builds real linguistic understanding, particularly for students who may otherwise feel more averse to reading.

How we built it

The frontend was built using Next.js and React to create an interactive reading interface where individual words can be selected and analyzed dynamically. The backend was written in Python, and Claude API to extract base morphemes, generate word matrices, verify derived words, and produce etymology explanations. Additional features such as text-to-speech for pronunciation and syllable breakdown were integrated using OpenAI's API, and we used the Noun Project API to source the images that accompany the definitions and provide a simple visual representation of each word.

Challenges we ran into

One of the biggest challenges we had was integrating the front- and backend, since we all split up our work based on our strengths, and then had to merge all of our separate work into our cohesive final product. The time constraint was another challenge, since there were numerous features we would have loved to incorporate before the deadline, but we do plan to implement them in the future. We also encountered difficulty with parsing PDFs into clean text and when designing word matrices that display clearly and dynamically.

Accomplishments that we're proud of

We are proud that we built a working Structured Word Inquiry matrix generator and a click-to-analyze reading experience. We successfully implemented an AI-driven morphology pipeline that produces structured linguistic analysis in real time. We also built a robust backend with caching to improve performance and integrated pronunciation and visual aids to make the learning experience more accessible and engaging.

What we learned

Through this project, we learned that linguistics and morphology are more complex than they initially appear. We also discovered how important prompt engineering is when structured outputs are required. Designing tools for education requires clarity, reliability, and thoughtful constraints to ensure that students receive accurate and meaningful information. We also gained experience coordinating a full-stack system that integrates frontend interaction with backend AI services.

What's next for Switch

In the future, we would like to add a student reading analytics dashboard that helps teachers track progress and identify areas of difficulty. We also plan to build a classroom mode designed specifically for educators and to develop a prebuilt matrix library for commonly taught curriculum words. We have also considered adding gamified learning exercises, a mobile version for classroom use, and the possibility of combining AI with curated linguistic databases to improve reliability and speed.

Why this matters:

Reading struggles affect millions of students, particularly those with dyslexia. Tools that explain how language works, rather than relying on memorization, can dramatically improve literacy outcomes. By making Structured Word Inquiry interactive and scalable, we hope to make deeper language understanding accessible to many more learners.