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Ruben Verborgh

Linked Data Generation for Adaptive Learning Analytics Systems

by Sven Lieber, Ben De Meester, Anastasia Dimou, and Ruben Verborgh

According to the Learning Analytics (LA) reference model, LA is used to collect, explore and analyze diverse types and interrelationships of data. Specifications like the Experience API (xAPI) work towards interoperability with respect to interrelationship of diverse learning data. Algorithms for adaptive learning could be improved by incorporation of user-related data, not present in learning activities. Linking these user-related data with learning activity data would fully exploit the potential of interrelationships with data. Conventional solutions, as well as current Linked Data-based solutions focus purely on learning activity data, whereas solutions based on Linked Data could be used to integrate data of different domains. We propose a provenance-aware pipeline to transform xAPI learning activity statements to Linked Data. The integration of learning activities with other user data, provides a more complete set of user data, improving an adaptive learning analytics system. We use the proposed pipeline to build a Linked Learning Record Store based on the Resource Description Framework (RDF). SPARQL queries are used to link data about learning activities, enriched with fine-grained exercise descriptions, with data describing the abilities of users. In this paper, we show how Linked Data can be generated from xAPI statements in a streaming approach, based on existing tools and interfaces. Our solution demonstrates the usage of Linked Data to combine learning activity data with user ability data, to get a more complete set of user data aiming to assist in adaptive learning.

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Published in 2018 in Proceedings of the Linked Learning Workshop.

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Cite this article easily using its BibTeX entry:

@inproceedings{lieber_lile_2018,
  author = {Lieber, Sven and De Meester, Ben and Dimou, Anastasia and Verborgh, Ruben},
  title = {{Linked Data} Generation for Adaptive Learning Analytics Systems},
  year = 2018,
  month = may,
  booktitle = {Proceedings of the Linked Learning Workshop},
}

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IEEE
S. Lieber, B. De Meester, A. Dimou, and R. Verborgh, “Linked Data Generation for Adaptive Learning Analytics Systems,” in Proceedings of the Linked Learning Workshop, 2018.
ACM
Sven Lieber, Ben De Meester, Anastasia Dimou, and Ruben Verborgh. 2018. Linked Data Generation for Adaptive Learning Analytics Systems. In Proceedings of the Linked Learning Workshop.
LNCS
Lieber, S., De Meester, B., Dimou, A., Verborgh, R.: Linked Data Generation for Adaptive Learning Analytics Systems. In: Proceedings of the Linked Learning Workshop (2018).
APA
Lieber, S., De Meester, B., Dimou, A., & Verborgh, R. (2018). Linked Data Generation for Adaptive Learning Analytics Systems. In Proceedings of the Linked Learning Workshop.
MLA
Lieber, Sven et al. “Linked Data Generation for Adaptive Learning Analytics Systems.” Proceedings of the Linked Learning Workshop. 2018. Print.

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