Adopting trust in learning analytics infrastructure. A structured literature review.

Autor/inn/en	Ciordas-Hertel, George-Petru; Schneider, Jan; Ternier, Stefaan; Drachsler, Hendrik
Titel	Adopting trust in learning analytics infrastructure. A structured literature review.
Quelle	In: Journal of universal computer science, 25 (2020) 13, S. 1668-1686 PDF als Volltext kostenfreie Datei (1); PDF als Volltext kostenfreie Datei (2); PDF als Volltext kostenfreie Datei (3); PDF als Volltext kostenfreie Datei (4) Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; gedruckt; Zeitschriftenaufsatz
ISSN	0948-695X; 0948-6968
DOI	10.25656/01:23312 10.3217/jucs-025-13-1668
URN	urn:nbn:de:0111-pedocs-233124
Schlagwörter	Bildung; Learning Analytics; Vertrauen; Datensicherheit; Datenschutz; E-Learning; Infrastruktur; Literaturbericht
Abstract	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).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2021/3