Universitat de Girona (SPAIN)
About this paper:
Appears in: EDULEARN09 Proceedings
Publication year: 2009
Pages: 5743-5754
ISBN: 978-84-612-9801-3
ISSN: 2340-1117
Conference name: 1st International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2009
Location: Barcelona ,Spain
Mobile and ubiquitous computing are changing the way how the students are learning. Heterogeneity of learner preferences in learning processes using Learning Management Systems (LMS) is a problem that researchers have been focused in the last few years. With the existence of different devices to access, technologies to interact, learning styles, competences to acquire, among others, the interest and motivation among students can be lost if personalization processes are not defined. Nowadays, the adaptation of learning contents considering these characteristics has become a research area to generate solutions for heterogeneity issues. Decide which variables can be addressed in adaptive processes to define how the contents in a LMS can be presented according to user preferences is one of the main challenges to design instructional models for e-learning courses. In order to build a context-aware content adaptation process on learning designs, a model that integrates different tools to provide adaptive contents when the learners perform different learning activities following the structure of a unit of learning is proposed. This unit of learning meets the specification of the standard IMS-Learning Design (IMS-LD). To obtain this model some existing tools such as specifications and content transcoding technologies that can be used to achieve the adaptation of contents considering different context features such as access device, location, access time, performance of the network connection, interaction preferences, mood, etc., are used. Also, some elements of the IMS-LD standard that allow adaptive conditions to be defined are considered, in order to set up properties of learning content to be presented according to context features and device capabilities captured from learners.
mobile learning, ubiquitous learning, adaptive hypermedia systems, adaptive content.