Interoperable user tracking logs using {Linked Data} for improved Learning Analytics

Learning analytics can provide adaptive learning and performance support by analyzing user tracking logs. However, data-driven learning is usually confined to a specific context (e.g., learning English within one application), and thus not interoperable across systems or domains. In this paper, we investigate ways to improve integration of data across applications and educational domains, by means of Linked Data, using existing standards such as the Experience API. Using JSON-LD, existing Learning Record Store tools can be used to store the tracking logs, which are then interpreted and aligned as Linked Data. We have applied the solution in an initial data capture resulting in more than two million statements spanning two different applications. This way, we aim to enrich adaptive learning and performance support across contexts.