New Perspective of Learning Objects in e-Learning System

Autor/inn/en	Amane, Meryem; Aissaoui, Karima; Berrada, Mohammed
Titel	New Perspective of Learning Objects in e-Learning System
Quelle	In: International Journal of Information and Learning Technology, 40 (2023) 3, S.269-279 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Amane, Meryem)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2056-4880
DOI	10.1108/IJILT-08-2022-0161
Schlagwörter	Electronic Learning; Resource Units; Metadata; Algorithms; Artificial Intelligence; Classification; Web 2.0 Technologies + Suchen Sie Ihr Suchwort? Metadaten; Algorithm; Algorithmus; Künstliche Intelligenz; Classification system; Klassifikation; Klassifikationssystem
Abstract	Purpose: Together, learning objects (LOs) and e-pedagogical practices have the potential to improve the performance of e-learning systems in several ways. They can make e-learning more personalised and adaptable, providing students with a more engaging and effective learning experience. Design/methodology/approach: The development of LOs and e-pedagogical practices have significantly influenced and changed the performance of e-learning systems. LOs are self-contained, reusable units of instructional content that create instructional materials, such as online courses, tutorials and assessments. They provide a flexible and modular approach to designing and delivering e-learning content, allowing educators to easily customise and adapt their materials to the needs of their students. e-pedagogical practices refer to the use of technology to enhance and support the teaching and learning process. They include strategies such as online collaboration, gamification and adaptive learning to improve student engagement, motivation and achievement. Findings: To achieve this objective, this study consists of two main phases. First, the authors extract metadata from LOs using latent semantic analysis algorithms, which are considered a strong tool in web-mining exploration techniques. Second, they identify LOs according to a particular form of similarity using fuzzy c-means (FCM) algorithms. To improve classification accuracy, the FCM is used as a clustering algorithm. Originality/value: Finally, in order to assess the effectiveness of LOs with FCM, a series of experimental studies using a real-world dataset are conducted. The results of this study indicate that the proposed approach exceeds the traditional approach and produces good results. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01