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Autor/inn/enMuslim, Arham; Chatti, Mohamed Amine; Schroeder, Ulrik
TitelSupporting Indicator Personalization and Platform Extensibility in Open Learning Analytics
QuelleIn: Technology, Knowledge and Learning, 27 (2022) 2, S.429-448 (20 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN2211-1662
DOI10.1007/s10758-021-09543-0
SchlagwörterLearning Analytics; Lifelong Learning; Delivery Systems; Ecology; Individualized Instruction; Users (Information); Educational Indicators; Visualization
AbstractThe demand for Open learning analytics (OLA) has grown in recent years due to the increasing interest in the usage of self-organized, networked, and lifelong learning environments. However, platforms that can deliver an effective and efficient OLA are still lacking. Most OLA platforms currently available do not continuously involve end-users in the indicator definition process and follow design patterns which make it difficult to extend the platform to meet new user requirements. These limitations restrict the scope of such platforms where users regulate their own learning process according to their needs. In this paper, we discuss the Open learning analytics platform (OpenLAP) as a step toward an ecosystem that addresses the indicator personalization and platform extensibility challenges of OLA. OpenLAP follows a user-centered learning analytics approach that involves end-users in the process of defining custom indicators that meet their needs. Moreover, it provides a modular and extensible architecture that allows the easy integration of new analytics methods and visualization techniques. (As Provided).
AnmerkungenSpringer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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