Prediction and Optimization of Student Grades Based on Genetic Algorithm and Graph Convolutional Neural Networks

• Published in: International journal of computational intelligence systems Vol. 18; no. 1; pp. 1 - 21
• Main Author: Li, Ting
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 17.03.2025; Springer
• Subjects: Artificial Intelligence; Computational Intelligence; Control; Dependency measure and academic performance; Engineering; Genetic algorithm; Graph convolution neural networks; Graph structure; Mathematical Logic and Foundations; Mechatronics; Research Article; Robotics; Student grade; Graph structure; Genetic algorithm; Student grade; Graph convolution neural networks; Dependency measure and academic performance

Due to limited support in registered courses, students frequently struggle to complete their courses in higher education institutions. To combat this, educational systems are incorporating intelligent prediction tools to help students improve their academic performance by predicting their grades. St...