1 research outputs found
A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System
The implementation of teaching interventions in learning needs has received
considerable attention, as the provision of the same educational conditions to
all students, is pedagogically ineffective. In contrast, more effectively
considered the pedagogical strategies that adapt to the real individual skills
of the students. An important innovation in this direction is the Adaptive
Educational Systems (AES) that support automatic modeling study and adjust the
teaching content on educational needs and students' skills. Effective
utilization of these educational approaches can be enhanced with Artificial
Intelligence (AI) technologies in order to the substantive content of the web
acquires structure and the published information is perceived by the search
engines. This study proposes a novel Adaptive Educational eLearning System
(AEeLS) that has the capacity to gather and analyze data from learning
repositories and to adapt these to the educational curriculum according to the
student skills and experience. It is a novel hybrid machine learning system
that combines a Semi-Supervised Classification method for ontology matching and
a Recommendation Mechanism that uses a hybrid method from neighborhood-based
collaborative and content-based filtering techniques, in order to provide a
personalized educational environment for each student