The Use of the Recommended Learning Path in the Personalized Adaptive E-Learning System

Vagale, Vija; Niedrite, Laila; Ignatjeva, Svetlana

doi:10.1007/978-3-030-57672-1_21

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…L'adaptabilité, par définition, est la capacité de s'adapter à de nouveaux milieux ou à de nouvelles situations 9 , et la personnalisation est l'adaptation d'un produit, d'un service, etc., à la personnalité de celui à qui il est destiné 10 . Ceci dit un système d'apprentissage en ligne adaptatif personnalisé doit permettre aux utilisateurs de prendre le contrôle de leurs propre processus d'apprentissage et offrir un contenu adapté à leurs besoins spécifiques [57].…”

Section: Intégration De L'adaptabilitéunclassified

Towards a semantic platform for adaptive and collaborative e-learning

Sabeima

Lamolle²,

Anghour³

et al. 2023

Revue Africaine De Recherche en Informatique Et Mathématiques Appliquées

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soumission à Episciences In the world of e-learning, learning systems have sought to adapt the user's profile and the content offered to them. However, from the point of view of collaboration between learners based on adaptation to the learner profile, this adaptation has not been sufficiently explored as an important aspect of the e-learning process. Adaptation will allow users with similar or very similar profiles to be grouped together to learn in harmony while maintaining motivation and commitment to learning. This should increase the success rate of learners. This will also allow us to reuse learning paths with good success rates for future recommendations to users with the same profile. In this paper, we focus on this aspect and propose a learning system that controls learning paths adapted to the users' profile and that allows collaborative learning of users in a synchronous way. After an overview of the existing work in the field of adaptive e-learning, we propose an architecture for the piloting of this type of collaborative adaptive learning based on ontologies and orchestrated by a multi-agent system. The latter is responsible for the piloting of learning paths, the recommendation of paths in collaborative or non-collaborative mode through communication between the different agents involved, and the management of events captured by the system. Dans le monde de la formation en ligne, les systèmes d'apprentissage ont cherché à proposer un contenu adapté à tout utilisateur selon son profil.Cette adaptation a comme objectif général de permettre à l'apprenant de tirer le meilleur parti du contenu exposé des ressources d'apprentissage.Cependant, du point de vue de la collaboration entre apprenants selon l'adaptation au profil des apprenants, cette adaptation n'a pas été suffisamment explorée comme un aspect important du processus d'apprentissage en ligne.L'adaptation va permettre de grouper des utilisateurs de profil similaire ou très proche pour apprendre en harmonie tout en gardant la motivation et l'engagement nécessaire afin d'augmenter le taux de réussite des apprenants. Cet état de fait doit permettre aussi de réutiliser certains parcours d'apprentissage avec de bons taux de réussite pour de futures recommandations aux utilisateurs ayant le même profil. Dans cet article, nous mettons l'accent sur cet aspect et proposons un système d'apprentissage qui recommande des parcours d'apprentissage adaptés au profil des utilisateurs et qui permet un apprentissage collaboratif des utilisateurs de façon synchrone. Après un tour d'horizon de l'existant dans le domaine de l'apprentissage adaptatif en ligne, nous proposerons une architecture pour le pilotage de ce type d'apprentissage adaptatif collaboratif. Cette solution est fondée sur des ontologies et orchestrée par un système multi-agents. Ce dernier est responsable du pilotage des parcours d'apprentissage, de la recommandation de parcours en mode collaboratif ou non par le biais d'une communication entre les différents agents intervenants et de la gestion des événements captés par le système.

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Section: Intégration De L'adaptabilitéunclassified

Towards a semantic platform for adaptive and collaborative e-learning

Sabeima

Lamolle²,

Anghour³

et al. 2023

Revue Africaine De Recherche en Informatique Et Mathématiques Appliquées

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“…The idea of managing the learning process in the e-learning system is considered [17]. This study uses a personalized adaptive eLearning system that includes three developed theme sequences: teacher, student, or optimal theme sequences.…”

Section: Introductionmentioning

confidence: 99%

Trainable generator of educational content

Rotkin

2021

IJAAS

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<p>As the main problem of the research, the possibility of creating a universal educational platform that combines the possibilities of an online generation of educational content with the interface of the training process itself was considered. The methodology of the educational platform has been developed, in which the mass generation of content is carried out at random, based on simulation models of educational objects. A matrix interface is used, which allows performing custom operations by entering a sequence of typical operators. The system forms a reference base of operators, replenishing it from user solutions, which makes it possible to train and improve the system in order to provide methodological support to student users. An active demo layout of an educational content generator was created and tested, using the example of a specific problem from school mathematics. All methodological options function in the layout. There are three interface options: administrative, training and control. It was concluded that the approach based on the simulation of educational objects makes it possible to create a unified algorithmic platform that combines the functions of content generation with educational training. The system contains a unique option to teach yourself based on its interaction with students.</p>

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The Use of the Recommended Learning Path in the Personalized Adaptive E-Learning System

Cited by 2 publications

References 5 publications

Towards a semantic platform for adaptive and collaborative e-learning

Towards a semantic platform for adaptive and collaborative e-learning

Trainable generator of educational content

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