Prof. Dr.-Ing. Dietrich Kammer

The OLEANDER – Opal Learning Analytics Data Development project aimed to harness the potential of Learning Analytics for the Saxon learning management system OPAL. Building on the prior work of the LEAC (2022/23) subproject, which developed platform-independent concepts and initial analyses, OLEANDER focused on the systematic acquisition and preparation of OPAL usage data. A key objective was the provision and GDPR-compliant processing of OPAL data, including data that had previously been insufficiently captured. By relying on OPAL’s existing data structures, the project was largely able to forgo the integration of external tools such as Learning Record Stores. Instead, platform-specific statistical analyses were generated within OPAL and prepared for sustainable storage to enable long-term analysis and extensibility of learner data. In parallel, BPS GmbH carried out major revisions to the existing course statistics and deployed them productively. These included new configuration options for displaying direct or aggregated views of course elements, as well as an additional setting for visualizing structural levels to enhance transparency and differentiation of course activities. Moreover, the underlying data model for future course statistics was substantially restructured and expanded. A unique user ID is now stored for each page view while preserving user affiliation data, enabling future determination of enrollment or group membership.