文章基本信息

标题：On Recommending Web 2.0 Tools to Personalise Learning
本地全文：下载
作者：Anita JUSKEVICIENE ; Eugenijus KURILOVAS
期刊名称：Informatics in Education
印刷版ISSN：1648-5831
出版年度：2014
卷号：13
期号：1
页码：17-31
出版社：Institute of Mathematics and Informatics
摘要：The paper aims to present research results on using Web 2.0 tools for learning personalisation. In the work, personalised Web 2.0 tools selection method is presented. This method takes into account student's learning preferences for content and communication modes tailored to the learning activities with a view to help the learner to quickly and accurately find the right educational tools, and to implement this method in prototype of knowledge-based recommender system. In the research, first of all, personalised e-learning technological peculiarities i.e. recommender systems applications for learning personalisation and those systems components were investigated. After that, selection methods for Web 2.0 tools suitable for implementing learning activities were analysed. The novel method of integrating Web 2.0 tools into personalised learning activities according to students learning styles was created, and prototype of the recommender system that implements the method proposed was developed. Finally, the expert evaluation of the developed system prototype that implements the method proposed was performed
关键词：Web 2.0 tools; personalisation; VARK learning styles; learning activities; ontology; recommender system.