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Despite the rise in services generating learning analytics, there is a lack of standard models and guidelines for data integration and aggregation to inform the design choices of applications supporting learning analytics. We propose a bottom-up, user-driven approach enabling educators to select, match, and contextualize activity traces from several data sources to perform and visualize meaningful learning analytics. To facilitate the process, the proposed approach recommends building customized auxiliary plugins that can be shared and re-purposed. We present the implementation of a use case following this approach. This use case focuses on supporting the import and side-by-side comparison of activity traces from multiple data sources that teachers might use in their practice. Implications of this approach on cross-platform learning analytics and future work are discussed.
Athanasios Nenes, Paraskevi Georgakaki