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This chapter describes our current research efforts related to the contextualization of learners in mobile learning activities. Substantial research in the field of mobile learning has explored aspects related to contextualized learning scenarios. However, new ways of interpretation and consideration of contextual information of mobile learners are necessary. This chapter provides an overview regarding the state of the art of innovative approaches for supporting contextualization in mobile learning. Additionally, we provide the description of the design and implementation of a flexible multi-dimensional vector space model to organize and process contextual data together with visualization tools for further analysis and interpretation. We also present a study with outcomes and insights on the usage of the contextualization support for mobile learners. To conlcude, we discuss the benefits of using contextualization models for learners in different use-cases. Moreover, a description is presented in order to illustrate how the proposed contextual model can easily be adapted and reused for different use-cases in mobile learning scenarios and potentially other mobile fields.
This chapter describes our research efforts related to the design of mobile learning (m-learning) applications in cloud-computing (CC) environments. Many cloud-based services can be used/integrated in m-learning scenarios, hence, there is a rich source of applications that could easily be applied to design and deploy those within the context of cloud-based services. Here, we present two cloud-based approaches—a flexible framework for an easy generation and deployment of mobile learning applications for teachers, and a flexible contextualization service to support personalized learning environment for mobile learners. The framework provides a flexible approach that supports teachers in designing mobile applications and automatically deploys those in order to allow teachers to create their own m-learning activities supported by mobile devices. The contextualization service is proposed to improve the content delivery of learning objects (LOs). This service allows adapting the learning content and the mobile user interface (UI) to the current context of the user. Together, this leads to a powerful and flexible framework for the provisioning of potentially ad hoc mobile learning scenarios. We provide a description of the design and implementation of two proposed cloud-based approaches together with scenario examples. Furthermore, we discuss the benefits of using flexible and contextualized cloud applications in mobile learning scenarios. Hereby, we contribute to this growing field of research by exploring new ways for designing and using flexible and contextualized cloud-based applications that support m-learning.