  To bridge the digital skills gap, we need to train more people in Software
Engineering techniques. This paper reports on a project exploring the way
students solve tasks using collaborative development platforms and version
control systems, such as GitLab, to find patterns and evaluation metrics that
can be used to improve the course content and reflect on the most common issues
the students are facing. In this paper, we explore Learning Analytics
approaches that can be used with GitLab and similar tools, and discuss the
challenges raised when applying those approaches in Software Engineering
Education, with the objective of building a pipeline that supports the full
Learning Analytics cycle, from data extraction to data analysis. We focus in
particular on the data anonymisation step of the proposed pipeline to explore
the available alternatives to satisfy the data protection requirements when
handling personal information in academic environments for research purposes.
