#Stash 2007 how to#

A brief description of the most commonly used models in e-learning literature is presented.

#Stash 2007 how to#

In the last thirty years many researchers (mainly pedagogues and psychologists) have studied how to characterize cognitive styles and how to exploit the different styles during the educational process. Alonso (1993) defines learning styles as “personal manners to perceive and process information, and how they interact and respond to educational stimuli”. Keefe (1985) defines cognitive styles as “characteristic cognitive, affective, and psychological behaviours that serve as relatively stable indicators of how learners perceive, interact with, and respond to the learning environment”. This implies that different learners approach learning tasks in different ways. For instance, some students prefer learning by doing, others, learning by images or by example. Finally, some conclusions and future works are discussed.Įach learner usually shows a tendency or a preference for one or more modalities in the way that teaching actions are received and elaborated. Section five describes the adaptation logic used by the adaptation agent in order to tailor the user navigation within a SCORM package. Section 4 describes the multi-agent architecture for a SCORM compliant distance learning environment designed using TROPOS methodology. Section 3 illustrates the methodological context, investigating the state of the art of tailoring approaches in e-learning applications and, in particular, the use of rule-based systems in defining personalised learning paths. Regarding the technological issues the section will focus on the description languages ( Roselli & Rossano, 2006) and SCORM specifications (in particular the Sequencing and Navigation rules), that are useful to understand the constraints and potentialities of the available technologies. From the pedagogical point of view, it examines the literature on the different cognitive styles theories used in the adaptive process. Section 2 presents pedagogical and technological premises of the research work. In order to better understand the research work proposed, the fundamental concepts in the technological, pedagogical and methodological context are described. In particular, the chapter focuses on methods and techniques for carrying out personalized teaching actions in SCORM (Sharable Content Object Reference Model) ( ADL, 2004) compliant Learning Management Systems. It supplies methods and techniques for both recommending the Learning Object (LO) that best fits the learner’s profile and tailoring the navigation of the content of recommended LOs on the basis of the learner's knowledge, cognitive styles and metacognitive abilities. The architecture proposed in the chapter defines a possible solution to both these problems.

In fact, they do not allow personalization of the teaching to the true needs and abilities of the individual, nor do they promote adoption of the many different existing teaching strategies ( Di Bitonto et al., 2008 ). Another problem is that these tools often do little more than present the information content, without making any attempt to subject this content to intelligent processing to tailor it to the specific needs of the learner. In fact, one of the main problems that has emerged from the e-learning literature is that if different students undertake the same search for a content the LMSs supply the same results without considering the learner profile. All the same, they are not yet sufficient to guarantee an “optimal training” experience because they do not take into account some significant variables of the learning process ( Di Bitonto & Roselli, 2008 ). On both these fronts, many advanced solutions have been proposed, and have proven undoubtedly useful and much appreciated. Attention is focused on the one hand on the definition of standards allowing interoperability and reuse (the success of Learning Objects is an example), and on the other hand on the adoption of methodologies and technologies which ensure a controlled fruition of teaching contents (such as Learning Management Systems). The E-Learning research field proposes mechanisms for managing teaching materials that are coherent with the emerging technologies.