Data mining techniques in education and learning are still in their infancy. Even academic references in this area are limited, although some education-related publications are already beginning to pay attention to this new area and its research potential. Unluckily, the authors are mostly focused on developing data mining and text mining techniques and usually somewhat neglect educational content and intent. The present article describes findings within a medium-scale (N = 56) study, using log files from open remote laboratory at Charles University in Prague, Faculty of Mathematics and Physics, to observe secondary school students’ behaviour during their work in virtual environment. The simple data mining and text mining techniques were used to reveal individual user’s behavioural patterns, to detect disengagement, and to compare learning outcomes and student preferences. The results will be used mainly to improve remote laboratory systems’ adaptability to students’ requirements and capacities.