The course structure that we propose in WELSA is a hierarchical one: each course consists of several chapters, and each chapter can contain several sections and subsections.
In order to support the teacher in creating courses conforming to WELSA internal format, we have designed a course editor tool, which allows authors to easily assemble and annotate learning resources, automatically generating the appropriate file structure.
As mentioned in section 2, WELSA is based not on a single learning style model, like the rest of the similar systems, but on a complex of features extracted from several such learning style models (called ULSM--Unified Learning Style Model).
For the identification of these ULSM preferences, WELSA uses an implicit modeling mechanism, by analyzing the interaction of the students with the educational system, in the form of behavioral patterns.
These tasks are accomplished by a researcher who interacts with the Analysis tool in the experimental version of WELSA. All the intermediate data (duration of learner actions, pattern values, pattern thresholds, reliability and confidence values) can be visualized by the researcher.
The learners studied an AI course module on "Search strategies and solving problems by search" and all of their interactions with WELSA were recorded by the course player.
WELSA course player is responsible with the generation of individualized web pages for each student; furthermore, it incorporates some basic LMS (learning management system) functions, such as: administrative support (registration and authentication) and communication and collaboration tools (discussion forum, chat).
WELSA doesn't store the course web pages but instead generates them on the fly, following the structure indicated in the XML course and chapter files.
The WELSA system described in this paper is an intelligent e-learning platform, aimed at adapting the course to the learning preferences of each student.