<b>Adaptive Gamification of Financial Literacy Using Deep Reinforcement Learning</b>

This research proposes an innovative framework that combines <b>gamification principles</b> with <b>deep reinforcement learning (DQN)</b> to enhance financial literacy education, especially among Gen Z. The system treats learners as dynamic environments and adapts content delivery in real-time using user behavior data, biometric inputs, and performance metrics. By modeling the learning process as a Markov Decision Process (MDP), the paper introduces a working prototype that intelligently personalizes educational content—resulting in a <b>2.2× improvement in knowledge retention</b>and <b>1.9× longer session durations</b> compared to static learning systems. The study leverages modern edtech stacks and RL frameworks (PyTorch, Gym, Stable-Baselines3) to validate results through both synthetic and real user simulations.