A Multicontext-aware Resource Recommendation Mechanism for Service-oriented Ubiquitous Learning Environment

As it is very difficult for learners to find the most proper contents according to their preferences from massive resources in U-Learning environment, the resource recommendation mechanism as a core component must be introduced. On the other hand, traditional recommendation mechanisms have been widely studied in e-business and personalized service fields in which most of them only take into account the single learner's preference. However, in service-oriented u-learning environment, the dynamic features of resources and services may implicitly affect the recommendation results; meanwhile the other learners' preferences may also make a significant effect on the recommendation process. Based on these limitations, in our study, a multicontext-aware resource recommendation model and strategy for service-oriented ubiquitous learning environment is proposed with taking into consideration not only the services and learners' dynamic context information Finally, by presenting our prototype system and illuminating a typical scenario, we could show that our proposal can help learners obtain the proper resources to enhance the learning efficiency.