Using Fuzzy Logic for Recommending Groups in E-Learning Systems

Autor:	Krzysztof Myszkorowski, Danuta Zakrzewska
Rok vydání:	2013
Předmět:	Group (mathematics) Computer science business.industry Learning environment Joins Recommender system Machine learning computer.software_genre Fuzzy logic Cardinality Similarity (psychology) Fuzzy number Artificial intelligence business computer
Zdroj:	Computational Collective Intelligence. Technologies and Applications ISBN: 9783642404948 ICCCI
DOI:	10.1007/978-3-642-40495-5_67
Popis:	Performance of Web-based learning environment depends on the degree it is adjusted into needs of virtual learning community members. Creating groups of students with similar needs enables to differentiate appropriately the environment features. Each new student, who joins the community, should obtain the recommendation of the group of colleagues with similar characteristics. In the paper, it is considered using fuzzy logic for modeling student clusters. As the representation of each group, we assume fuzzy numbers connected with learner attributes ranked according to their cardinality. Recommendations for new students are determined taking into account similarity of their dominant features and the highest ranked attributes of groups. The presented approach is investigated, taking into considerations learning style dimensions as student attributes. The method is evaluated on the basis of experimental results obtained for data of different groups of real students.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a6d10db6fb1559cf62b43efa702b29cf https://doi.org/10.1007/978-3-642-40495-5_67 Zobrazit plný text záznamu