Design of a Big Data-Driven Cryptocurrency Trading System for Financial Education of University Students in the AI Era

This study presents a practical financial education model for university students through the development of an AI- and big data-driven automated cryptocurrency trading system. Despite growing engagement with digital financial tools such as mobile payments and virtual asset investments, students often lack access to structured financial education. To address this gap, the proposed system employs a deep learning-based Long Short-Term Memory (LSTM) model to predict cryptocurrency closing prices and execute automated trades. The system is further integrated with the Telegram API to facilitate real-time notifications, enhancing user interactivity and system transparency. Experimental validation using the STPT token yielded returns exceeding 20%, alongside effective risk management, highlighting its potential as a hands-on educational tool. The findings suggest that AI-based financial education can extend beyond theoretical instruction, offering experiential learning through investment simulation and informing future curriculum and policy development.