An Adaptive M-learning Architecture for Building and Delivering Content based on Learning Objects

Mobile learning solutions have become a real interest due to the fact that mobile devices have a growing market share and have become somewhat indispensable to modern life. We propose an architecture for a context adaptive m-learning system based on learning object that, even if created by different standards, can be retrieved and combined with the help of semantic metadata processing. Our goal is to personalize the course content according to user context and preferences and deliver it bearing in mind the specific characteristics of the mobile device. We have developed the architecture starting from the results of a survey regarding mlearning environments and student’s expectations from such a system.

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