DigiTwin

💡 Inspiration

The GPA guessing game is a universal source of stress for students. We often calculate our grades in a vacuum while ignoring the reality of work and sleep. We wanted to build a tool that helps students predict their GPA, tailor their lifestyle, and ask questions through our platform.

🛠️ What it does

DigiTwin is a predictive simulation dashboard that models the complexities of student life by integrating academic data with lifestyle variables to generate a virtual semester. The core engine calculates a projected GPA while simultaneously visualizing mental bandwidth through a Burnout Battery and a Dynamic Risk Score, providing a holistic view of a student's potential journey. Rather than just presenting raw numbers, the platform analyzes the interplay between grades and well-being to offer tailored advice, including hyper-local study spot recommendations and features an integrated AI Advisor that suggests strategic schedule pivots based on real-time simulation data. By bridging the gap between data-driven projections and daily habits, DigiTwin delivers the supplemental resources and actionable insights necessary to proactively manage academic fatigue and ensure long-term student success.

🏗️ How we built it

The project is powered by a Flask backend and Python logic. We developed a custom weighted math engine to handle GPA projections and risk algorithms. The frontend uses HTML to structure the complex multi step forms and CSS for the modern layout. We integrated Machine Learning principles and AI via the Claude API to provide intelligent, conversational feedback and answer student questions.

⚖️ Challenges we ran into

The biggest technical hurdle was developing the right formulas for the GPA projection and making sure the model was trained well enough for the Academic Risk and Burnout Risk. We had to calibrate the Machine Learning logic to ensure that lifestyle variables accurately weighed against academic performance. Debugging these complex calculations required several rounds of testing to prevent skewed results. We also spent time fixing CSS issues to ensure the UI remained on theme and aesthetic.

🏆 Accomplishments that we're proud of

We are proud of the seamless integration between the mathematical simulation and the conversational AI. Seeing DigiTwin provide contextually aware advice based on a specific GPA feels like a major success. We successfully implemented a clean HTML architecture that allows for easy data entry across six different course modules. The tool feels tailor made for our campus community, especially with Knightro displaying UCF themed phrases throughout the application and suggested study spots.

🧠 What we learned

This project was a deep dive into full stack development and AI implementation. We learned how to use CSS variables to maintain a consistent UCF yellow and black theme throughout the app. Managing state across a multi step web form was a valuable lesson in software architecture. Most importantly we learned how to leverage Machine Learning logic to translate lifestyle stress into actionable insights.

🚀 What's next for DigiTwin

Our primary goal is to expand DigiTwin into a web application or mobile app for the UCF student body. We plan to refine our predictive algorithms and launch the site officially to help our peers manage their academic journey. Future updates will include API integration to sync real time grades and a feature for students to save their information and results in a personal profile with a secure username and password.