An Ontology Network for Educational Recommender Systems

2012

The rapid growth of Internet technology and the explosion of educational resources, show the increasing importance of e-learning systems. Despite the importance of these systems, they suffer from the enormous learning materials. In recent years, recommender systems appeared to improve the quality of learning. Such systems were used in learning systems to provide the facilities during the learning process and help learners with a more accurate learning. Different recommendation techniques such as collaborative filtering, content based and the hybrid filtering were employed for e-learning domain. In addition to the importance of learner's needs in the learning process, also the training method for recommended learning materials should be important in this learning process. This paper aims to develop the knowledge based personalized e-learning recommendation system based on ontology. Furthermore, this study discusses about appropriate recommendation technique based on learning syst...

Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18

Academic advising is limited in its ability to assist students in identifying academic pathways. Selecting a major and a university is a challenging process rife with anxiety. Students at high school are not sure how to match their interests with their working future or major. Therefore, high school students need guidance and support. Moreover, students need to filter, prioritize and efficiently get appropriate information from the web in order to solve the problem of information overload. This paper represents an approach for developing ontology-based recommender system improved with machine learning techniques to orient students in higher education. The proposed recommender system is an assessment tool for students' vocational strengths and weaknesses, interests and capabilities. The main objective of our ontology-based recommender system is to identify the student requirements, interests, preferences and capabilities to recommend the appropriate major and university for each one.

2000

A professional career selection is a complicated process for university student candidates and often little technical tolls are available for who aim to enter to the superior education system, since it is necessary to consider the incidence of a multiplicity of variables to obtain a "satisfactory answer" that comes near to the idea that they have preconceived. These variables build up a complex relations map that requires the formulation of an exhaustive and rigorous conceptual scheme. In this research a domain ontological model is presented as support to the student's decision making for opportunities of University studies level of the Venezuelan education system. For the declaration of the domain ontological model developed, the information provided by two organisms (OPSU & CNU) is used. Both are responsible to design the policies and strategies for the superior education in Venezuela. The ontology is designed and created using Methontology approach, since this methodology offers the possibility of improving the progressive creation or captures and knowledge articulation, its elements and relations. In order to represent the ontology Protégé 3.1.1 tool is used, based on the ontological language for the Web: OWL (Web Ontology Language) and; finally, to accede and to visualize the ontology, an application based on the Semantic Web is developed. In the field of the computation, computer science and systems, the concept of profiles or users models has many meanings and connotations, its first and greater diffusion arise with the development and use of on-line increasing systems; however, they have gain great preponderance recently, not only to refer and/or to respond to the passive user who approaches "the system", but for the possibility of taking care of a user stimulated and attracted by "the system". In that sense, the possibility of this "personalized attention" and/or recommendations from "the system" will be obviously conditioned by the user context. Centered on the possibility of giving that "customized attention" from which they must select an option between many, it is tried in the future to construct a meta-ontology that integrates the domain ontology with a user profile ontology, thus aiming towards to a Semantic Recommendation System under Multiagent approach in the future, that could be useful to support students decision making process for career selection over different study opportunities in Higher Education level in Venezuela.

In spite of the fact that the field of applying ontological research in education is fairly young it is already quite broad and fuzzy. The set of technologies used and developed there have roots in a variety of diverse areas of information and pedagogical sciences. To facilitate the process of scientific and scholastic search the domain needs to be structured. This paper presents two main results: an ontological overview of the Ontologies for Education field and an initial report on the development of an ontology-driven web portal providing a single network place, where researchers, students, and practitioners can find information about available research projects and successful practices in this field.

International Journal of Emerging Technologies in Learning (iJET)

The continuous growth of the internet has given rise to an overwhelming mass of learning materials. Which has increased the demand for a recommendation system to filter information and to deliver the learning materials that fit learners learning context. In this paper, we propose an architecture of a semantic web based recommender system. The proposed architecture is a redesigned architecture of the classical 3-tiers web application architecture with an additional semantic layer. This layer holds two semantic subsystems: an Ontology-based subsystem and SWRL (Semantic Web Rule Language) rules one. The Ontology subsystem is used as a reusable and sharable domain knowledge to model the learning content and context. The SWRL rules are used as a recommendation and filtering technique based on learning object relevance and weighting. These rules are organized into four categories: Learning History Rules (LHR), Learning Performance Rules (LPR), Learning Social Network Rules (LSNR) and Lear...

4th WSEAS/IASME …, 2008

A professional career selection is a complicated process for university student candidates and often little technical is available for who aim to enter to the superior education system, since it is necessary to consider the incidence of a multiplicity of variables to obtain a "satisfactory answer" that comes near to the idea that they have preconceived. These variables build up a complex relations map that requires the formulation of an exhaustive and rigorous conceptual scheme. In this research a domain ontological model is exposed as support to the student's decision making for opportunities of University studies level of the Venezuelan education system. For the declaration of the domain ontological model developed, the information provided by two organisms (OPSU & CNU) is used. Both are responsible to design the policies and strategies for the superior education in Venezuela. The ontology is designed and created using Methontology approach, since this methodology offers the possibility of improving the progressive creation or captures and knowledge articulation, its elements and relations. In order to represent the ontology Protégé 3.1.1 tool is used, based on the ontological language for the Web: OWL (Web Ontology Language) and; finally, to accede and to visualize the ontology, an application based on the Semantic Web is developed. In the field of the computation, computer science and the systems, the concept of profiles or users models has many meanings and connotations, his first and greater diffusion arise with the development and use of on-line increasing systems; however, they have gain great preponderance recently, not only to refer and/or to respond to the passive user who approaches "the system", but for the possibility of taking care of a user stimulated and attracted by "the system". In that sense, the possibility of this "personalized attention" and/or recommendations from "the system" will be obviously conditioned by the user context. Centered in the possibility of giving that "customized attention" from which they must select an option between many, it is tried in the future to construct a meta-ontology that integrates the domain ontology with a user profile ontology, thus aiming towards to a recommendation system in the future, that serves as support to students decision making process of selection of study opportunities to this education level in Venezuela.

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.

The Semantic Web – ISWC 2021, 2021

With the increased dependence on online learning platforms and educational resource repositories, a unified representation of digital learning resources becomes essential to support a dynamic and multi-source learning experience. We introduce the EduCOR ontology, an educational, career-oriented ontology that provides a foundation for representing online learning resources for personalised learning systems. The ontology is designed to enable learning material repositories to offer learning path recommendations, which correspond to the user’s learning goals and preferences, academic and psychological parameters, and labour-market skills. We present the multiple patterns that compose the EduCOR ontology, highlighting its cross-domain applicability and integrability with other ontologies. A demonstration of the proposed ontology on the real-life learning platform eDoer is discussed as a use case. We evaluate the EduCOR ontology using both gold standard and task-based approaches. The com...

Journal of Information Systems and Technology Management, 2018

Ontologies occupy a central position in any conceptual model of the Semantic Web, aiming fundamentally to add explicit semantics to the contents available in the Web. In the domain of Brazilian higher education, especially with regard to the National System for the Evaluation of Higher Education (SINAES), still lacks a reference ontology that can provide a basic conceptualization common to the different stakeholders of the domain. In this work we discuss the role of an ontology network developed with the purpose of improving the quality of the data produced by the different actors, institutions and systems within the domain of SINAES, in addition to facilitating their publication as open and connected data. In particular, we highlight the importance of the NeOn methodology to be followed during the development of an ontology network, demonstrating its role in defining the life cycle and in the articulation of the various processes and activities in the OntoSINAES ontological network development process.

IEEE Access

Choosing a higher education course at university is not an easy task for students. A wide range of courses is offered by individual universities whose delivery mode and entry requirements all differ. A personalised recommendation system can be an effective way of suggesting relevant courses to prospective students. This paper introduces a novel approach that personalises course recommendations that will match the individual needs of users. The proposed approach developed a framework of an ontology-based hybridfiltering system called OPCR. This approach aims to integrate information from multiple sources based on hierarchical ontology similarity with a view to enhancing efficiency and user satisfaction and to provide students with appropriate recommendations. OPCR combines collaborative based filtering with contentbased filtering. It also considers familiar related concepts that are evident in the profiles of both the student and the course, determining the similarity between them. Furthermore, OPCR uses an ontology mapping technique, recommending jobs that will be available following completion of each course. This method can enable students to gain a comprehensive knowledge of courses based on their relevance, using dynamic ontology mapping to link course profiles and student profiles with job profiles. Results show that a filtering algorithm that uses hierarchically related concepts produces better outcomes compared to a filtering method that considers only keyword similarity. In addition, the quality of the recommendations improved when the ontology similarity between the items' profiles and the users' profiles were utilised. This approach, using a dynamic ontology mapping, is flexible and can be adapted to different domains. The proposed framework can be used to filter items for both postgraduate courses and items from other domains.