Reference model for adaptive and intelligent educational systems supported by learning objects
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Abstract: Computer Aided Learning, known more widely with the generic name of e-learning, has become a powerful tool with lots of potentialities within educational field. Even though, one of the main critics that it receives is that in most cases the implemented courses follows a “one size fits all” approach, which means that all students receive the same content in the same way being unaware of their particular needs. This problem is not due only to the absence of direct interaction between student and tutor, but also because of the lack of an appropriate instructional design. There are several approaches which deal with this issue and look for adapt the teaching process to students. One could say that in the top of those approaches the Adaptive and Intelligent Educational Systems are situated, which merges the functionalities of two approaches: the Adaptive Educational Hypermedia Systems and the Intelligent Tutoring Systems. Nevertheless, after an extensive literature review, a major inconvenience is still found for this kind of systems and particularly for their reference models: or they are too simple, including just a few functionalities; or they are too complex, which difficult their design and implementation. Considering this panorama, the main objective of this dissertation thesis was the definition of a reference model trying to reach such an elusive equilibrium, in such a way that allows the design of courses which adapt themselves in an intelligent and effective way to the progress and characteristics of each student but without being too complex. Another important feature is that this model integrates Learning Objects, promoting this way flexibility and reusability. In order to achieve this general objective, three sub-models were considered: a domain model, a student model and a tutor model. The first one serves to structure the knowledge domain and was defined using the notion of learning goal and a flexible multilevel schema with optional prerequisite operations. The second one aids to characterize students and considered personal, knowledge and psycho-cognitive information. The third one may be considered as the hearth of the system and defines the adopted adaptive functionalities: sequencing and navigation, content presentation, assessment, and collaborative support. With the aim of clarify the three sub-models, as well as all their components and relationships, an instantiation example was also presented. Such an instantiation was called Doctus, an authoring tool for adaptive courses. Doctus was not only helpful to exemplify the setup of the referece model as a whole, but also to refine sub-models and several procedures envolved. As final part of the dissertation, the implementation and preliminary validation of Doctus was performed. This was done with 51 subjects, teachers from different formation levels. The obtained results in this stage were outstanding, all the adaptive functionalities were well evaluated and all of those polled felt enthusiastic about counting with a tool for helping them in their teaching practices considering students as particular individuals.