Over the past 10 years, we have created attractive self-learning materials and a motivating didactical model to teach our 1st semester natural science students in computer science, which opens the possibility to discover important basic digital literacy competences on a scientific level. The aim of this project is to investigate how we can provide our learning materials and services for different student groups (e.g. novices, advanced, repeaters, etc.) on the basis of data from learning analytics. In order to achieve this goal we have planned three complementary activities: Firstly, a gamification concept in the form of a bonus system is to be implemented to our courses. The idea is, that active learners are provided with attractive materials and services (e.g. repetition questions, mock exams, possibility for a preliminary grade, personal Feedback on current performance, etc.) depending on their learning activity. As a second development a student learning dashboard is planned, which is also based on data from learning analytics. It allows visualizing the individual learning progress in small steps, so that even short activities lead to visible progress and put it into the context of the learning goals of the whole course. Thirdly, another dashboard helps the lecturers to monitor learning progress of large distributed cohorts in real-time. As a basis for the above-mentioned developments, a framework for learning analytics has to be created, which allows the collection and aggregation of student data from different data sources. This new structure could be of broad interest for many lecturers and learning professionals at ETH.