Adaptation Technologies in Mobile Learning

Adaptation Technologies in Mobile Learning

Paola Salomoni (University of Bologna, Italy) and Silvia Mirri (University of Bologna, Italy)
Copyright: © 2011 |Pages: 17
DOI: 10.4018/978-1-60960-613-8.ch002
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This chapter will introduce issues and standards for adaptation mechanisms for mobile learning resources, and it will describe some notable existing projects and software tools. Finally, it will present some case studies and open trends about m-learning.
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The term m-learning is meant to refer to learning by using mobile devices, both in anywhere/anytime context and in traditional classrooms (Clothier, 2005). During the last decade, mobile learning has grown from a research topic to a plethora of concrete projects in schools, museums, cities, and workplaces. This transformation has been facilitated by the widespread diffusion of mobile devices and connectivity. Moreover, the availability of open source technologies in this field strongly supports the diffusion of mobile learning. More recently, Web 2.0 technologies and applications have increased users’ capabilities to collaborate and to share content and knowledge through mobile devices, constructing kinds of the so-called “collective intelligence” (Levy, 1997).

The diversity of mobile device capabilities, learners’ preferences (and needs), supported content formats, and contexts of use has called for standards, metadata, and adaptation mechanisms. They have to be applied to the learning environment and content, in order to provide the best educational experience to learners. In particular:

  • device capabilities and learners’ needs have to be profiled on the basis of standards; open standards are strategically used in such a context;

  • original learning contents have to be described on the basis of metadata and standards;

  • learning contents have to be transcoded through adaptation mechanisms on the basis of device capabilities, learners’ preferences, contexts of use, and original learning content characteristics.

This chapter will motivate the need of standards and adaptation mechanisms in the mobile learning field and it will describe related standards, open source projects, and libraries. Finally, it will present how Learning Content Management Systems face m-learning instances and it will introduce m-learning open issues and trends.

The remainder of the chapter is organized as follows. The section named “Mobile device profiling standards” presents main profiling mobile device standards (W3C CC/PP and OMA UAProf) which describe mobile device capabilities and drive learning content transcoding operations. This section also introduces open source repositories of mobile device descriptions (such as WURFL) compliant to the W3C Device Description Repository Standard (DDR). The section titled “Mobile learning content adaptation mechanisms” describes main concepts related to content adaptation and transcoding, by introducing architectural approaches, standards, and formats which apply adaptation mechanisms, open source projects and libraries in charge of operating adaptations to the whole learning content or to single media which compose it. The section named “Mobile issues in LCMSs” introduces main strategies to face mobile context issues applied by two of the most widespread and well-known open source Learning Content Management Systems: Moodle and ATutor. Finally, the section titled “Open issues and future research directions” concludes the chapter, by describing some open issues and future trends. In particular, it presents the growing need of tools and applications in order to let learners collaborate with each other, and create and share mobile learning content. Moreover, the relationships between mobile learning and accessibility topics are introduced in this last section.


Mobile Device Profiling Standards

In order to meet the needs of learners who are equipped with mobile devices, the adaptation of didactical materials has to be driven by device characteristics. Hence, profiling such characteristics is fundamental in mobile learning. In fact, standards which describe mobile device capabilities allow the identification and the definition of the characteristics (i.e. formats, sizes, etc.) the learning contents should have after the transcoding operations. There are currently two main standards which are devoted to perform device profiling: W3C CC/PP (Composite Capabilities/Preferences Profile) and OMA UAProf (User Agent Profile). Both of them are based on Resource Description Framework (RDF). The RDF format implies the document schemas are extensible.

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