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Ariadne Pfad:

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Title
Adopting trust in learning analytics infrastructure. A structured literature review
Authors ORCID; GND-ID ORCID; ORCID; GND-ID ORCID
SourceJournal of Universal Computer Science 25 (2019) 13, S. 1668-1686 ZDB
Document  (1.410 KB)
License of the document In copyright
Keywords (German)E-Learning; Learning analytics; Vertrauen; Datenschutz; Infrastruktur; Software; Datensicherheit; Bildung; Literaturbericht
sub-disciplineOther Thematic Areas
Document typeArticle (journal)
ISSN0948-695X
LanguageEnglish
Year of creation
review statusPeer-Reviewed
Abstract (English):One key factor for the successful outcome of a Learning Analytics (LA) infrastructure is the ability to decide which software architecture concept is necessary. Big Data can be used to face the challenges LA holds. Additional challenges on privacy rights are introduced to the Europeans by the General Data Protection Regulation (GDPR). Beyond that, the challenge of how to gain the trust of the users remains. We found diverse architectural concepts in the domain of LA. Selecting an appropriate solution is not straightforward. Therefore, we conducted a structured literature review to assess the state-of-the-art and provide an overview of Big Data architectures used in LA. Based on the examination of the results, we identify common architectural components and technologies and present them in the form of a mind map. Linking the findings, we are proposing an initial approach towards a Trusted and Interoperable Learning Analytics Infrastructure (TIILA). (DIPF/Orig.)
additional URLsDOI: 10.3217/jucs-025-13-1668
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Checksumschecksum comparison as proof of integrity
Date of publication08.03.2022
CitationCiordas-Hertel, George-Petru; Schneider, Jan; Ternier, Stefaan; Drachsler, Hendrik: Adopting trust in learning analytics infrastructure. A structured literature review - In: Journal of Universal Computer Science 25 (2019) 13, S. 1668-1686 - URN: urn:nbn:de:0111-pedocs-233124 - DOI: 10.25656/01:23312
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