The study of interaction data and learning experiences in education has the potential to allow the analysis of why students pass or fail a course or where a course can be improved. In the special case of programming courses for beginners, analyzing the behaviour of students while coding, is essential but not always possible. To avoid the need to install and setup a programming environment by the students, a web-based environment like the open source JupyterLab can be used. This paper presents Juxl, an extension of this online programming environment, allowing a modular, performant and secure way of logging user interactions and learning experiences. The logs are generated as xAPI statements and stored in a Learning Record Store to be further analyzed.

As learning scenarios include more digital parts and often more than one online platform is used, Learning Analytics becomes more challenging to perform on these distributed data. In this paper, the Learning Analytics infrastructure EXCALIBUR LA is presented. It receives data from arbitrary platforms as xAPI statement, performs pro-active analyses by using various analytics engines and provides the analysis results via a REST API for each authorized platform. This concept allows to perform analyses adjusted to the needs of an institution and also to analyze data from multiple platforms combined.