Today’s education faces many challenges related to learning and teaching efficiency, effectiveness, and costs. Contemporary research shows that the learning environment with the ability to adapt to individual needs, requirements, and competencies of students, facilitates the learning process and leads to improved learning outcomes and achievements. Nevertheless, learning management systems (LMS) that are often used in e-learning typically provide a limited level of adaptivity. The goal of this paper is to introduce an adaptive e-learning model which enables personalized learning experience and more intelligent decision making. It consists of the students’ model, the adaptation module, the expert system for data analysis and decision making, the repository of learning objects, and database of educational methods. The designed model provides adaptivity through a learning management system, considering individual characteristics of the student, such as their learning styles and prior knowledge. It is capable to adapt course content, structure, and assessment based on the specific student’s needs and performance. The model is implemented within the widely used open-source LMS, which makes it more usable and easier to deploy. The process of applying the proposed model is illustrated with a higher education case study that shows how the recommended method is applied for a successful transition to an adaptive form of learning. The model has been tested through experiment during which a group of students attended traditional non-adaptive e-learning course, and the other group attended the adaptive e-learning course. The results of data analysis showed that students who learned from an adaptive course achieved better performance in various aspects. The proposed adaptive model can enhance educational processes in terms of improving learning performance, personalized application of teaching/learning methods, as well as continuous improvement cycle.

当今的教育面临与学习效率，有效性和成本有关的许多挑战。当代研究表明，学习环境具有适应学生的个性化需求，要求和能力的能力，可以促进学习过程并改善学习成果和成就。但是，经常在电子学习中使用的学习管理系统（LMS）通常只能提供有限的适应性。本文的目的是介绍一种自适应的电子学习模型，该模型可实现个性化的学习体验和更明智的决策。它由学生模型，适应模块，用于数据分析和决策的专家系统，学习对象的存储库以及教育方法的数据库组成。设计的模型通过学习管理系统提供适应性，考虑学生的个人特征，例如他们的学习风格和先验知识。它能够根据特定学生的需求和表现来调整课程内容，结构和评估。该模型是在广泛使用的开源LMS中实现的，这使其更易用且易于部署。高等教育案例研究说明了应用建议的模型的过程，该案例显示了如何将推荐的方法成功地应用到适应性学习形式。该模型已通过实验进行了测试，一组学生参加了传统的非自适应电子学习课程，另一组学生参加了自适应电子学习课程。数据分析的结果表明，从适应性课程中学习的学生在各个方面都有较好的表现。所提出的自适应模型可以在改善学习绩效，个性化应用教学方法和学习方法以及持续改进周期方面增强教育过程。