MathCoach AI

Inspiration

Many students struggle with math not because they lack effort, but because they don’t know where their reasoning went wrong. Most AI tools provide final answers, which limits real learning. This inspired me to build an AI system that focuses on mistakes and reasoning rather than solutions.

What it does

MathCoach AI is an AI-powered problem-solving coach designed to help students learn how to think, not just what the answer is. Instead of solving problems outright, it analyzes a student’s step-by-step math solution—typed or handwritten—identifies the first incorrect step, explains why it is wrong, and provides a targeted hint without revealing the final answer.

How I built it

The application is built using the Gemini 3 API and Google AI Studio. Gemini 3’s advanced reasoning and multimodal capabilities are used to interpret handwritten math work, evaluate logical consistency across solution steps, detect extraneous solutions, and generate structured, schema-validated feedback.

Challenges I ran into

One of the main challenges was learning how to design prompts and response schemas that enforce educational behavior—guidance without giving away answers. Working with multimodal inputs and structured JSON outputs required careful iteration.

Accomplishments that I’m proud of

I’m proud that MathCoach AI behaves like a real coach instead of a solver. It highlights reasoning errors, provides meaningful hints, and encourages students to think independently.

What I learned

I learned how powerful Gemini 3 is for reasoning-heavy and educational applications, especially when combined with multimodal inputs and structured outputs.

What’s next for MathCoach AI

Future plans include supporting more math domains, adaptive difficulty, and classroom-focused features for teachers and students.

Why Gemini?

Gemini’s reasoning and multimodal capabilities make it especially suitable for educational feedback. In MathCoach AI, Gemini is used not to generate answers, but to analyze reasoning across steps, interpret handwritten math input, and provide structured, schema-validated feedback that supports learning rather than shortcuts.

Built With

• css
• gemini-3-api
• google-ai-studio
• html
• react
• typescript