A Probabilistic Approach for the Generation of Learning Sessions Tailored to the Learning Styles of Learners

Abstract

In this paper we present an audacious solution based on Bayesian networks and educational approach for the construction of evolutionary personalized learning paths. We mean by evolutionary learning paths, paths that are composed gradually as learners advance in their learning, i.e in real time. To do this, the system selects the hypermedia units of learning to apprehend based on the results of formative assessments, psychological and cognitive characteristics of learner.
 The architecture that we propose is based, firstly, on the semantic web, First, in order to model the domain model and to index learning resources so as to maximize their reuse, and then to represent the personal and cognitive traits of learners in a learner model while integrating their learning styles according to the Felder and Silverman model; and secondly, a probabilistic approach based on Bayesian networks that calculates the probability of success of each candidate hypermedia unit, for selecting those who are most appropriate for the construction of evolutionary personalized learning paths. 
 The proposed Bayesian model is validated with real data collected from an experimental study with a specimen of students.

GODeM: A Graphical Ontology Design Methodology

“…OntoDesign Graphics integration having aim to have graphical notation that allows standardizing ontologies designs for clarity, as with the use of UML notation. For example, authors such as Rezgui, Mhiri, Ghédira, Ali,Tawil, Jahankhani, Yarandi, Mencke, Dumke, Bouhdidi, Ghailani, and Fennan [29][30][31][32], show a great diversity in the graphical representation of ontologies designs proposed which complicates interpretation between one notation and another.…”

Modeling of a Smart University Social Network for the Development of Soft Skills in a Professional Environment (SUSN)

“…Primacy of the relational: Referring to the axiomatic model of Palo Alto, in particular to the axiom which argues that all communication has two aspects: content and relationship, such that the second includes the first and is therefore a metacommunication [41], we believe that the relationship should govern this educational project. Indeed, the relationship (which involves mutualisation and negotiation) should occupy the first rank in relation to technical content.…”

“…Our technical architecture is based on Multi-Agent Systems, ontologies [41] and learning machine algorithms. The use of an SMA, highly recommended in the case where the problem is very complex, heterogeneous but decomposable, makes it possible to have a certain robustness and to reduce the processing time of the programs using parallelism.…”

Towards an Adaptive e-Learning Solution based on Ontologies and Competencies Approach

“…The system includes the result of the evaluation as another parameter of adaptation. If the objective in question is considered complete, the system will present the following teaching unit taking advantage of the principle of evolutionary learning paths [21].The objectives of operational competence do not give the learner empowerment to acquire the next skill because this passage is determined by its success in an assessment presented as synthesis exercises. These exercises are simple problems situations favouring the linkage of different HUL.…”

“… Remedial phase: this stage is for students in difficulties. These later benefit from adapted hypermedia units to correct their weaknesses [21]. After remediation, the system offers the learner another integration situation which is similar to the first to redo the training phase in order to continue his learning.…”