Personalized recommendation strategies in mobile educational systems

Recent technological advancements shifted the trends of learning from e-learning to mobile learning, thus added new dimensions such as learning process can take place at anytime and anywhere. However this shifts faces some technological and design issues in m-learning and e-learning (i.e personalization). The factors that lead towards personalisation are the frequent growth of learning resources as well as differences in the characteristics of learners. Recently, recommender systems have been exploited as a new form of personalisation. This paper proposed a hybrid recommendation approach for mobile learning environment, based on identified user's learning style for providing more personalized recommendation. The reported results indicate significant differences in the performance of learners having personalized recommendations.