Semantic technologies and learning (original) (raw)
Semantic Technologies for Semantic Applications. Part 1. Basic Components of Semantic Technologies
Scientific and Technical Information Processing, 2019
This paper discusses the basic aspects of the modern understanding of semantic computations, semantic technologies, and semantic applications in the field of artificial intelligence. The basic terminology accepted in the work is introduced and specific examples of semantic applications, including industrial-level ones, are given. The paper demonstrates that the basic components of semantic technologies of artificial intelligence are ontologies and semantic models of their use, semantic resources, and the semantic component of the technology. The semantic resources contain information about the semantics of words and other entities, as well as means of refinement of these semantics. The semantic component is used to create formal descriptions of the meanings of natural language entities and numerically evaluate their pairwise semantic similarity. The available semantic resources are discussed and a comparative analysis of them is given. Information on natural language entity types (primitives) is given and then used for the practical purposes of building models of formal description of the meaning of texts in various semantic applications. The latter components of description of text semantics constitute the contents of the second part of this paper.
Employing Semantic Web Technologies to Leverage Learning and Research
The Web has always been a set of resources (such as web pages, files, etc) connected to each other by hypertext links which are untyped. By untyped we mean that the relationships between the linked resources are not easily discernible and are not necessarily machineinterpretable. Adding meaning (i.e. semantics) to these resources and their linkages will make them more machine-interpr etable thereby making it easier to find relevant information from related social structures. In this paper, we present how semantic web technologies offer potentials for impr oving the interactivity of today' s learning and research while putting students/teachers in control of their learning process spanning across disparate tools and services. This, we consider as a Better By Far (BBF) approach to research and general learning. Ontologies and ontology languages are the key concepts used in this study to provide additional meaning to these resources and their links. Also in this paper, popular ontology technological tools like Resource Description Framework (RDF) and Extensible Markup Language (XML) were used to discuss the implementation of Semantic Web (SemWeb).
IJAEDU- International E-Journal of Advances in Education, 2016
There was a time when it was thought that the more information someone has, the better it is. Nowadays, there has been a change in the mindset of people where what they want is meaningful and personalized information. The semantic web is an advancement of the current web that is being used, the web 2.0, which comprises mainly of metadata i.e. data about data. The semantic web is a new technology which is being developed and it is seen as the future web where everything will be much more accurate as per our needs. Semantic Web technologies and applications are getting increasingly popular and adopted in different fields, including education. Research on software and education has already shown some of the features expected to be embedded in the next generation of learning support systems. Such features include: more adaptive and personalized learning environment, a better use of pedagogies to enhance instruction/learning, effective information sharing, storage and retrieval, new forms of collaboration with peers, and many other characteristics that enable the realization of AAAL: Anytime, Anywhere, Anybody Learning. Information on the Web is commonly represented in natural-language for human understanding. However, in order for the computer to understand its meaning, it is necessary to represent the information in a form that can be interpreted syntactically and semantically. Such representation helps the process of analyzing, extracting, and integrating information on the Web, making it easier the creation of solid knowledge bases that intelligent services can rely on to support users' needs. Nowadays, research on ontologies has been considered as one of the keys to provide information in a computer-understandable way. This paper focuses on the different Semantic Web Technologies that play an important role in education and learning.
Semantics is seen as the key ingredient in the next phase of the Web infrastructure as well as the next generation of information systems applications. In this context, we review some of the reservations expressed about the viability of the Semantic Web. We respond to these by identifying a Semantic Technology that supports the key capabilities also needed to realize the Semantic Web vision, namely representing, acquiring and utilizing knowledge.
An Investigation of the Usage of Semantic Web Technologies to Support Learning
2005
Abstract This report is about the intersections between narrative hypermedia and semantic web technologies for eLearning. Although various research has enhanced the hypermedia field by making use of semantic web technologies, there is little work in order to pitch this approach to an educational perspective. Actual eLearning technologies, focusing on the definition and re-use of learning objects (LO), often sacrifice the expressiveness of the metadata descriptors to the reusability of a resource.
APPLYING SEMANTIC WEB TECHNOLOGIES TO SERVICES OF E-LEARNING SYSTEM By
Although of the semantic web technologies utilization in the learning development field is a new research area, some authors have already proposed their idea of how an effective that operate. Specifically, from analysis of the literature in the field, we have identified three different types of existing applications that actually employ these technologies to support learning. These applications aim at: Enhancing the learning objects reusability by linking them to an ontological description of the domain, or, more generally, describe relevant dimension of the learning process in an ontology, then; providing a comprehensive authoring system to retrieve and organize web material into a learning course, and constructing advanced strategies to present annotated resources to the user, in the form of browsing facilities, narrative generation and final rendering of a course. On difference with the approaches cited above, here we propose an approach that is modeled on narrative studies and on their transposition in the digital world. In the rest of the paper, we present the theoretical basis that inspires this approach, and show some examples that are guiding our implementation and testing of these ideas within e-learning. By emerging the idea of the ontologies are recognized as the most important component in achieving semantic interoperability of e-learning resources. The benefits of their use have already been recognized in the learning technology community. In order to better define different aspects of ontology applications in e-learning, researchers have given several classifications of ontologies. We refer to a general one given in that differentiates between three dimensions ontologies can describe: content, context, and structure. Most of the present research has been dedicated to the first group of ontologies. A well-known example of such an ontology is based on the ACM Computer Classification System (ACM CCS) and defined by Resource Description Framework Schema (RDFS). It"s used in the MOODLE to classify learning objects with a goal to improve searching. The chapter will cover the terms of the semantic web and e-learning systems design and management in e-learning (MOODLE) and some of studies depend on e-learning and semantic web, thus the tools will be used in this paper, and lastly we shall discuss the expected contribution. The special attention will be putted on the above topics.
Learning Technologies and Semantic Integration of Learning Resources
IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 2015
Virtual learning environments are developed nowadays as digital ecosystems based on existing resources, applications and web services. Even if they are not hosted in a centralized course management system, they are usually highly coupled. In this paper we show how semantic technologies can help decoupling them. We build an e-learning web ecosystem enriched with educational information according to an educational information model and a domain-specific model, so we provide teachers and students with a common user interface. We implemented our proposal in the ASCETA project, integrating well-known open-source systems like wikis, blogs, microblogging services, content management systems and task management systems. Index Terms-Semantic web, virtual learning environments, web services.
An approach for description of Open Educational Resources based on semantic technologies
2010
Open Educational Resources are accessed through the web, whose real setting shows an explosion in the use and development of tools and services based on Social Software. However, the growth of this data repository makes it difficult to find information of value, and reduces the possibilities of sharing and exchanging resources. Using semantic technologies to describe educational resources enables any agent (human or software-based) to process and understand its content (applying inference rules on more structured knowledge). Metadata standards can be used to annotate educational resources; they facilitate their interoperability and discovery. In this work, we propose, OER-CC ontology, for the description of Open Educational Resources under Creative Commons Licenses. This approach is based on standard technology and metadata standards. The ontology could be utilized in higher education institutions (and organizations) to facilitate sharing and discovery of their digital content. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document. (Abstract)