A New Approach to the Use of Semantic Technologies in E-Learning Platforms

Abstract

Semantic technologies have been studied and used in different areas of computer science. E-learning has been one of this, but the most frequent use of semantic technologies in this discipline has been in the extraction and indexing of contents, like forums, blogs, learning objects etc. The research presented in this paper aims at taking advantage of semantic technologies in a different way respect to the mainstream use that has been done in the past. This new approach refers to the use of semantic technologies in the management of the persistence layer of Learning Management Systems (LMS), i.e., where all the contents are stored. Our research follows the idea of using semantics technologies as a support, if not an entire replacement, of the backend and persistence mechanisms of LMSs. As a testbed, we will present the design and early results of the application of this approach to the persistence layer of a Virtual Communities System, where these technologies will enriched the platform to address two fundamental issues: a) entities disambiguation and identification inside the persisted objects b) adding new features to the platform without refactoring it.

Collaborative E-learning Environments with Cognitive Computing and Big Data

“…For example, we extended the platform towards a semantic representation of the knowledge inside the contents of the platform. We also integrated some soft computing, fuzzylogic-based decision support systems [1], to support decision makers with intelligent tools about educational processes. Moreover, we experimented new storage layers, in order to collect data not only from traditional sources inside the educational environment (i.e., files, forums, galleries, posts, photos, etc.…”

“…As a consequence, technological solutions are subjected to continuous upgrades to cope with these, to the aim of improving the quality of services, the a Corresponding author Email address: mauro.coccoli@unige.it ORCID: 0000-0001-5802-138X usability, the overall performances, the effectiveness of education, and to provide learners with a more pervasive experience. Accordingly, e-learning environments and the relevant tools have been growing in complexity, i.e., traditional Learning Management Systems (LMS), based on a centralized architecture, are moving towards clusters of Massive Open Online Courses (MOOC) platforms in cloud-based distributed architectures [1] and Learning Objects (LO) include more and more videos and multimedia interactive artifacts. Concurrently, LMSs have been exploring new spaces of possibilities; among these, we mention the adoption of users' profiling techniques and analytics to the aim of tailoring personalized learning paths and activities as well as to predict students' careers, to achieve a further empowerment of the individual learning model.…”

When E-Learning Meets Big Data, Cognitive Computing, and Collaborative Environments

“…For example, we extended the platform towards a semantic representation of the knowledge inside the contents of the platform. We also integrated some soft computing, fuzzy-logic-based decision support systems [1], to support decision makers with intelligent tools about educational processes. Moreover, we experimented new storage layers, in order to collect data not only from traditional sources inside the educational environment (i.e., files, forums, galleries, posts, photos, etc.…”

“…Specifically, with reference to the Technology Enhanced Learning (TEL) scenario, we observe significant steps ahead in techniques and methodology; consequently, the relevant technological solutions are subjected to continuous upgrades to cope with these, to the aim of improving the quality of services, the usability, the overall performances, the effectiveness of education, and to provide learners with a more pervasive experience. Accordingly, e-learning environments and the related tools have been growing in complexity, i.e., traditional Learning Management Systems (LMS), based on a centralized software architecture, are moving towards clusters of Massive Open Online Courses (MOOC) platforms in cloud-based distributed architectures [1] and Learning Objects (LO) include videos and multimedia interactive artifacts. Concurrently, LMSs have been exploring new spaces of possibilities; among these, we mention the adoption of users' profiling techniques and analytics to the aim of tailoring personalized learning paths and activities as well as to predict students' careers, to achieve a further empowerment of the individual learning model.…”