AI-Enhanced Educational Platform for Personalized Learning Paths, Automated Grading, and Real-Time Feedback

An AI-enhanced educational platform can significantly improve learning outcomes by tailoring instruction to individual needs. Studies indicate that personalized learning can boost student performance by up to 30% and enhance engagement by over 60% [20] . Automated grading can reduce instructors' grading time by nearly 40%, allowing more focus on student interaction [21] while real-time feedback has been shown to improve retention rates by approximately 50%[22], making education more adaptive and effective. This research presents an AI-enhanced educational platform designed to offerpersonalized learning paths, automate grading, and provide real-time feedback.The platform leverages advanced machine learning models, including Gradient Boosting, XGBoost, and Random Forest, topredict student performance and tailoreducational experiences to individual needs. A dataset containing student information, including age, grade level, learning style, and academic performance, was used to train and evaluate these models. The results demonstrate the platform's effectiveness in improving learning outcomes by adapting to students' unique requirements. The challenges faced during implementation, such as dataset limitations,real-time feedback generation, and model interpretability [4] . Future directions for enhancing the platform and expanding its scope are also outlined. Keywords: Gradient.Boosting Classifier, XGBoost, Random Forest, Student performance prediction, Data- driven education, AI in personalized learning, Educational technologyinnovation