Особливості застосування методів підтримки прийняття рішень у WEBплатформах персоналізованого навчання

Abstract

The effectiveness of modern educational web platforms largely depends on the ability to provide flexible personalization of the learning process. Traditional learning management systems (LMS) are often limited to static content delivery, lacking intelligent support for adapting the learning path to individual needs, styles, and progress of each student. The solution to this problem lies in the integration of decision support methods. The purpose of the work is to analyze and determine the features of applying key decision support methods, such as recommendation systems, treebased models, and expert systems, in the context of developing web platforms for personalized learning. It has been established that successful implementation requires consideration of the specifics of the web environment, including processing streaming data, ensuring low response latency, and integration with modern web technologies.