Collaborative e-learning systems using semantic data interoperability

In a collaborative e-learning content management environment, the heterogeneity of data in different learning management systems presents many difficulties for data sharing; some of these difficulties are how to integrate data, produce results for user queries, and find the correct data from heterogeneous learning management systems. Over the last few years, numerous e-learning system architectures have been proposed; however, issues related to sharing and integrating data from different e-learning systems have been given less attention. Considering this need, this paper presents solutions for semantic data interoperability, distributed metadata management, and an agent-based query processing approach for supporting the exchange of learning content from different e-learning systems. The paper presents an empirical evaluation of the user acceptability of the proposed solutions to find qualitative measures of the users' acceptability and satisfaction; our proposed solutions resulted in high user satisfaction. (C) 2016 Elsevier Ltd. All rights reserved.