This project develops a prototype application for analyzing logical text structures to generate reasoning-based multiple-choice questions for TMS preparation. Using Graph Neural Networks (GNNs), it captures logical connections within text to create questions that enhance logical reasoning skills. The effectiveness of GNN-based generation will be evaluated by comparing transformer models trained on questions with and without GNN analysis.