Using Device Detection Techniques in M-Learning Scenarios

Using Device Detection Techniques in M-Learning Scenarios

Ricardo Queirós, Mário Pinto
DOI: 10.4018/978-1-4666-2669-0.ch007
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Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.
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Mobile Content Adaptation

Mobile learning (m-learning) applications extend the electronic learning (e-learning) experience into the mobile context (Chang & Sheu, 2002; Chen, et al., 2002; Liu, et al., 2002). M-learning uses mobile devices to enhance the teaching-learning process. However, it should not be seen as just another e-Learning channel for delivering the same content. In fact quality M-learning can only be delivered with an awareness of the special limitations and benefits of mobile devices (Parsons & Hyu, 2007). Due to those constraints, the learning content must be adapted to suit the mobile device characteristics. Adaptation means a process of selection, generation or modification of content (text, images, audio, and video) to suit the user’s computing environment and usage context (Parupalli, 2009). The concept of Content Adaptation is commonly related to mobile devices. Due to the variety of types and technologies supported they require special handling through a series of content transformations, in the deliver process, made by the content provider (server) (Zhang, 2007). Instead of authors having to create specialised pages for each kind of device, content adaptation automatically transforms an author's content to match the device characteristics. Some examples of such features are related with their limited computational power, small screen size, constrained keyboard functionality, and media content type supported. The W3C Device Independence Working Group described many of the issues (Lewis, 2003) that authors must face in an environment in which there is an increasingly diverse set of devices used to access Web sites.

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