This study investigates the dynamics of knowledge acquisition in small student groups through the application of the Knowledge Acquisition Monitoring (KAM) methodology and the Knowledge Acquisition Surface (KAS) learning analytics tool. The research highlights the challenges educators face due to the gradual accumulation of learning data and the need for personalized approaches tailored to individual student needs and engagement levels. By assessing students’ knowledge before and after course completion, and analyzing behavior changes during the learning process, the study aims to enhance the effectiveness of online learning environments. Utilizing data from real educational courses, the research validates the KAM methodology and KAS tool's ability to accurately differentiate between actively engaged students and those exhibiting presenteeism. The findings underscore the importance of adaptive learning strategies and timely interventions in optimizing student engagement and knowledge retention, ultimately contributing to improved educational outcomes in e-learning contexts.