Development of a method and software for enhancing personalized education in private educational institutions

Abstract

Personalizing educational experiences is essential in improving learning outcomes, especially in private educational institutions. This research focuses on developing a method and accompanying software tool that enhances the quality of personalized education for students. The proposed solution addresses the growing demand for customized learning experiences that cater to individual student needs by leveraging adaptive learning algorithms and data-driven insights. The study utilizes a combination of artificial intelligence (AI) models, predictive analytics, and student performance metrics to deliver tailored educational content. Also, the proposed method leverages advanced data-driven techniques to assess individual student needs and tailor educational content dynamically. The developed software enables educators to monitor student progress in real-time and adapt instruction accordingly. Initial results demonstrate an improvement in both student engagement and academic outcomes. The software integrates machine learning algorithms and adaptive learning strategies, allowing educators to adjust pedagogical approaches in real-time. The primary goal is to improve engagement, comprehension, and retention by catering to each student`s unique learning profile. Initial results indicate significant improvements in academic performance and student satisfaction. Future work will involve expanding the system to support additional learning environments and integrating more advanced AI techniques for further personalization.