A Hybrid Trust-Based Recommender System for Online Communities of Practice

Autor/inn/en	Zheng, Xiao-Lin; Chen, Chao-Chao; Hung, Jui-Long; He, Wu; Hong, Fu-Xing; Lin, Zhen
Titel	A Hybrid Trust-Based Recommender System for Online Communities of Practice
Quelle	In: IEEE Transactions on Learning Technologies, 8 (2015) 4, S.345-356 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1939-1382
DOI	10.1109/TLT.2015.2419262
Schlagwörter	Metacognition; Communities of Practice; Computer Mediated Communication; Comparative Analysis; Social Networks; Case Studies; Electronic Learning; Trust (Psychology); Programming; Computer Software; Information Systems + Suchen Sie Ihr Suchwort? Meta cognitive ability; Meta-cognition; Metakognitive Fähigkeit; Metakognition; Community; Computerkonferenz; Social network; Soziales Netzwerk; Case study; Fallstudie; Case Study; Programmierung
Abstract	The needs for life-long learning and the rapid development of information technologies promote the development of various types of online Community of Practices (CoPs). In online CoPs, bounded rationality and metacognition are two major issues, especially when learners face information overload and there is no knowledge authority within the learning environment. This study proposes a hybrid, trust-based recommender system to mitigate above learning issues in online CoPs. A case study was conducted using Stack Overflow data to test the recommender system. Important findings include: (1) comparing with other social community platforms, learners in online CoPs have stronger social relations and tend to interact with a smaller group of people only; (2) the hybrid algorithm can provide more accurate recommendations than celebrity-based and content-based algorithm and; (3) the proposed recommender system can facilitate the formation of personalized learning communities. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01