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RWTH Aachen
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Data Warehousing for Lifelong Learning Analytics

Year 2013
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Lifelong learning aims at improving our personal knowledge, skills, and competences during our professional life. Traces or historical data of our lifelong learning processes are stored in a number of distributed portfolios. Lifelong learning analytics (LLA) involves harnessing these portfolios. However, data management of heterogeneous learning portfolios can become cumbersome and therefore limiting LLA, if done manually. Data warehousing is a data management technology ideally suited for automatic extraction, transformation and loading (ETL) of LLA data from heterogeneous portfolios making it perfectly suitable to be employed as a backend for visual LLA. A case study on teacher networks in Europe is demonstrating the feasibility of our data warehouse approach. We employed the data warehouse to analyze the interaction between teachers using social network analysis (SNA) for competence management and assessment of teachers’ performance via measuring social capital of teachers in the networks over time. Since all core ETL processes are running automatically, only little maintenance effort is needed to run the LLA processes.

Details

Bulletin of the Technical Committee on Learning Technology, Volume 15, Issue 2, April 2013, 6-9.

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Bulletin of the Technical Committee on Learning Technology , issue 2 , volume 15 , p. 6-9 .

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