An adaptive strategy to help students in e-Learning systems using competency-based ontology and agents

Author(s):  
V. Bremgartner ◽  
J. F. de Magalhaes Netto
Author(s):  
Malika Sedra ◽  
Samir Bennani

The expansion of computer networks has at the same time given impetus to the distance learning environments. E-learning systems are also advanced and more efficient. However, these platforms offer such complex teaching functionalities that designers find themselves poorly equipped to succeed in their engineering processes. This article presents a tool that makes it easier for designers to produce educational content according to the Competency-Based Approach (CBA). We propose an implementation of the CBA after its modeling via ontology. Our module can be grafted to any author system oriented pedagogy based skills. We have advocated for Service for Oriented Architecture as a software solution to model our business process that consists of a set of interconnected services that are modeled and implemented. The proposed system is the result of a coordina-tion of, services, incorporating the order of competences explained by a distance education, which integrates and interacts according to an orchestration plan.


Author(s):  
Mohamed Bendahmane ◽  
Brahim El Falaki ◽  
Mohammed Benattou

In most existing E-learning systems, activities' content and order are presented in a static manner without taking into consideration the learners characteristics, profiles or competencies. The challenge is to adapt and regulate learning processes according to the learner profile by applying learning models that use new information technologies. There are several adaptation approaches of E-learning environments, such as, adaptive hypermedia system, semantic web, etc. In our proposed system, we adopted a Competency Based Approach to offer each learner an individualized learning path for the acquisition of the competence targeted on the basis of the collaborative filtering. Concerning the technological aspect, the system is implemented as a web services while adhering to a service-oriented architecture. This allows interoperability with heterogeneous learning systems


2011 ◽  
Vol 57 (1) ◽  
pp. 1317-1333 ◽  
Author(s):  
Bo Cheng ◽  
Minhong Wang ◽  
Stephen J.H. Yang ◽  
Kinshuk ◽  
Jun Peng

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.


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