Personalised Multimedia Educational Content for M-learning Environments.

Thanks to the latest technological advances of mobile devices and web technologies, mobile learning (m-learning) has started to be adopted by an increasing community as an educational platform. There are several challenges in m-learning due to the high variety of mobile devices with different characteristics, different user profiles and various and variable network types and conditions, including the need to provide content suitable to user expectations. Solutions focus on adapting the educational material to suit user interests, goals and expectations, particularities of different user devices, or existing network conditions. As multimedia content usage in m learning has seen an exponential growth in the recent years, and as delivering multimedia content to learners is a high resource intensive task, adaptation of multimedia based educational content has become a very interesting research topic. Very few researchers in adaptive mlearning have addressed multimedia content adaptation based on mobile device characteristics or network connectivity, and to the knowledge of the author, none has studied the impact of video quality on the m-learning process. The latest is of much importance as most mechanisms for video quality adaptation involve content quality decrease. In this context, the research presented in this thesis, complements current research on adaptive mechanisms for multimedia educational content delivery with applicability in m-learning. The thesis proposes a strategy for grouping mobile learning devices in classes with similar characteristics. Each class was associated to a video profile meant to support an optimum level of quality on the National College of Ireland target devices. This research also presents a study conducted on a significant number of educational multimedia clips which makes recommendations in terms of optimum quality levels for each of the proposed video profiles. Experiments with different types of educational clips were conducted in order to determine how much the quality of the proposed video profiles can be decreased, while still maintaining good user perceived quality level. Results from a subjective study conducted on a number of participants, have validated the results from the experimental studies, and have confirmed that the learners ability to acquire knowledge is not impacted by a controlled decrease of the video quality