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 adaptivee-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 performancein various aspects. The proposed adaptive model can enhance educational processes in terms ofimproving learning performance, personalized application of teaching/learning methods, as well as continuousimprovement cycle.