In education systems, learners face the challenge of selecting appropriate courses that align with their academic goals or training needs. This paper introduces a hybrid course recommendation system that combines collaborative filtering and knowledge graphs to provide personalised and explainable course suggestions that guide students through their enrollment process. Unlike traditional recommendation methods, which often lack transparency and may offer unsuitable courses for students with different enrollment needs, our system helps prevent redundant suggestions and ensures that students receive appropriate course options based on their preferences and interactions. The system uses a Bernoulli matrix factorisation model to predict the course status, and a filtering method through information extracted from a knowledge graph to provide students with an effective and explainable recommendation. Empirical evaluation of a real-world dataset of 36.6K student records indicates that the proposed system achieves slightly higher levels of precision, recall and F1-score compared to Dirichlet matrix factorisation, naive Bayes collaborative filtering and neural collaborative filtering models. Furthermore, the Bernoulli matrix factorisation model also achieves good performance using the normalised discounted cumulative gain quality measure. The integration of the Bernoulli matrix factorisation model with knowledge graphs offers course recommendations that are accurate, diverse and transparent, improving the learning experience.

Collaboration is key to achieve the scientific excellence. This paper presents a top conceptual view to analyze collaboration networks. This approach is based on the semantic exploitation of open sources of knowledge hierarchically organized and collaboratively created by people. Researchers could use this model in order to find peers interested in common or related subjects, or they could use it to know the subjects of interest in a certain sector. In this paper, one application scenario is presented: discovery of popular subjects underlying to scientific production of some countries of the Andean region.

Universities and higher education institutes continually create knowledge. Hence it is necessary to keep a record of the academic and administrative information generated. Considering the vast amount of information managed by higher education institutions and the diversity of heterogeneous systems that can coexist within the same institution, it becomes necessary to use technologies for knowledge representation. Ontologies facilitate access to knowledge allowing the adequate exchange of information between people and between heterogeneous systems. This paper aims to identify existing research on the use and application of ontologies in higher education. From a set of 2792 papers, a study based on systematic mapping was conducted. A total of 52 research papers were reviewed and analyzed. Our results contribute key findings regarding how ontologies are used in higher education institutes, what technologies and tools are applied for the development of ontologies and what are the main vocabularies reused in the application of ontologies.

In an open and distributed platform as the Web there are problems associated with the heterogeneity and information overload. In this context, teaching community and learners may need some support to discover the Open Educational Resources best suited for their learning processes. In this paper, the authors propose the high-level design of a framework for the recommendation of learning content in a flexible way. In order to provide a personalized set of resources, an adaptive approach of filtering is used according to the data available of each user. To achieve this goal, the framework has been designed taking into account the best features provided by technologies of the Semantic Web in order to find online material.

The re-use of digital content is an essential part of the knowledge-based economy. The online accessibility of open materials will make possible for teachers, students and self-learners to use them for leisure, studies or work. Recent studies have focused on the use or reuse of digital resources with specific reference to the open data field. Moreover, open data can be reused - for both commercial and non-commercial purposes - for uses such as developing learning and educational content, with full respect for copyright and related rights. This work presents a rating system for open data as OER is proposed. This rating system present a framework to search, download and re-use digital resources by teachers and students. The rating system proposed is built from the ground upwards on Open data principles and Semantic Web technologies. By following open data best practices and Linked Data principles, open data initiative ensures that data hosted can be fully connected into a Web of Linked Data. This work aims at sharing good practices for administrative/academics/researchers on gathering and disseminating good quality data, using interoperable standards and overcoming legal obstacles. In this way, open data becomes a tool for teaching and educational environments to improve engagement and student learning. Designing an open data repository that manages and shares information of different catalogues and an evaluation tool to OER will allow teachers and students to increase educational contents and to improve relationship between open data initiatives and education context.

Scientific production reflects the advances of an academic or research activity; also, it reflects the efforts and issues in which people are engage. The researcher's contributions in each field of knowledge should be highlight in order to foster a systematic improvement of research and achieve recognition of researchers. In the current educational context, the role of creating knowledge is not exclusive to teachers, students are also encouraged to participate and even to lead academic and research projects. This fact, coupled with the need for universities achieve to become research entities, it increase the need for finding events or journals in order to disseminate the researches results. Therefore, specialized search tools are required for users to reach better results. With the aim of helping the academic staff to find the most appropriate media to publish his/her scientific production, in this paper, the authors present a technological platform that consolidates data from different sources as catalogs of call for papers and scientific databases. Later on, each diffusion media is enriched with open data available in the Web; this process leverages relationships established between semantic resources available in repositories created collectively. The semantic enrichment of the media has allowed implement an improved search service, which attempts to overcome the limitations of traditional engines based on matching keywords.

Teaching and Learning takes place in (or in a combination of) different educational environments: classroom, online, or mobile. Blended learning, or hybrid learning, is a formal educational program that integrates face-to-face learning with technology-based, digital instruction. On the other hand, Open Educational Resources (OER) provides a strategic opportunity to improve the quality of education as well as facilitate policy dialog, knowledge sharing, and capacity building. OERs are actual resources/tools that can help enrich any classroom environment and push student thinking and comprehension. One of the fundamental concepts of OER is "the ability to freely adapt and reuse existing pieces of knowledge", and therefore be a way to create more economic and personalized learning. The OER movement has challenged the traditional value chain by employing new methods to deliver high-quality educational content. The purpose of this work is to show a way to enhance the face-to-face classrooms with integration of OERs, and thus create blended learning instruction. Reuse of OERs by both individuals and organizations may have significant creative and economic benefit for learning environments. The approach is based on Linked Data for describe and publish OER. In this new paradigm for educational content consumption and integration, OER are expected to play a decisive and productive role for blended learning. The approach presented can be used to support different blended-learning models.

One of the fundamental concepts of Open Educational Resources (OER) is “the ability to freely adapt and reuse existing pieces of knowledge.” The application of Semantic Web approach and Linked Data technologies to Open Education seeks to turn data and metadata from open educational repositories into actionable interoperability for the improvement of discovering, using and reusing of OER. Interoperability is not an end in itself. Instead, optimizing the level of interoperability has societal and educational value as a means to others purposes. Interoperability can have a positive impact on open innovation, user choice, ease to reuse and adapt educational materials, global discovery of open and diverse content, among other things. This paper reports on the implementation of Linked Open Data for open access repositories in a new interoperable and global open educational ecosystem. The goal is to improve the metadata interoperability between various collections of open material, so as to facilitate the discoverability and subsequent combining, remixing, or adapting OER; that is, OER data should be easily accessible to any user: human being or a machine agent. This work addressed two challenges in the OER ecosystem: providing evidence of globally discoverability and reusability academic resources. Although there is much further potential for teaching and learning to realize, linked open data is a critical enabler of global and interoperable OER ecosystem.

The OER movement poses challenges inherent to discovering and reuse digital educational materials from highly heterogeneous and distributed digital repositories. Search engines on today's Web of documents are based on keyword queries. Search engines don't provide a sufficiently comprehensive solution to answer a query that permits personalization of open educational materials. To find OER on the Web today, users must first be well informed of which OER repositories potentially contain the data they want and what data model describes these datasets, before using this information to create structured queries. Learning analytics requires not only to retrieve the useful information and knowledge about educational resources, learning processes and relations among learning agents, but also to transform the data gathered in actionable e interoperable information. Linked Data is considered as one of the most effective alternatives for creating global shared information spaces, it has become an interesting approach for discovering and enriching open educational resources data, as well as achieving semantic interoperability and re-use between multiple OER repositories. In this work, an approach based on Semantic Web technologies, the Linked Data guidelines, and Social Network Analysis methods are proposed as a fundamental way to describing, analyzing and visualizing knowledge sharing on OER initiatives

Open Educational Resources include a diverse range of materials making it the most representative icon arisen within the Open Content movement. Users who access and use OERs could be classified into one of these three groups: instructor, student and self-learner. To provide personalized lists of OERs according to the user profile and personal preferences, the user should be characterized by an open and scalable model. In this paper, an open linked vocabulary is proposed to describe user profiles of the open educational resources, which take into account the challenges and opportunities that an open and extensible platform as the Web can provide to learn about the OER users, and from this knowledge, offer the most appropriate resources.

The arrival of Massive Open Online Courses (MOOCs) and the growth of open and online education - Open Educational Resources (OER), OpenCourseWare (OCW)- is increasingly the focus to self-learners as the primary target group. The OER movement has tended to define “openness” in terms of access for use and reuse to educational materials, and to address the geographical and financial barriers, between students, teachers and self-learners with distinguished educational institutions. MOOC initiatives emphasize free access and interactive features rather than static content. The dominant message is of the quantity of access rather than the openness of educational resources for use, re-use, adaptation or repurpose. The purpose of this paper is to present the main aspects to considerer building a framework based on semantic web technologies to support the inclusion of open materials in massive online courses and significantly to improve discovery, accessibility, visibility, and to promote reuse of open educational content in massive courses. This framework will provide a set of services that allows the discovery and access of open educational resources that are extracted from open repositories distributed. Our principal OER providers are OCW institutions. In this context, we opted to apply the principles of Linked Data to integrate, interoperate and mashup data from distributed and heterogeneous repositories of open educational materials.

The contribution of GICAC UPM group in the eMadrid initiative has focused to the application of semantic web technologies in the Open Education context. This work presents the main results obtained through different applications and models according to a roadmap followed by the group.

The access to information is essential to learning as much as instruction. The evolution of the Web, from Web 1.0, where we were consumers of information, to a Web 2.0 where now we are producers and consumers of information, has allowed the Web becomes a huge database and in constant expansion. In these days much of the information published on the Web is published on social media, represented through social networks such as Facebook, Twitter, to name only the most prominent. Each of the media and social networks has its own scheme of operation and different working characteristics, ranging from the length of text that can be used, the use of different forms to identify topics until reaching the reciprocity of relationship between the participants. For example Twitter is a social network where millions of daily messages called Tweets are exchanged, within the message can be used labels, called hashtags, to identify the subject of the message, the message also may include links to other resources that expand the original content or showing interesting information and the relationships between users are represented as non reciprocal relationships named "Following". The extraction of information posted on social networks is solved in this research through the use of linked data, that allow retrieving resources and link with other external sources, graphs databases that help represent the working scheme of a social network, and with social network analysis (SNA), technique to discover relevant information that goes beyond the individual properties. The scope of this paper is to use information that is published on Twitter to extract and recommend Open Educational Resources in order to help with the learning process. The results obtained are a set of recommendations on users (identified as experts) and virtual communities (lists of Twitter users) and related events, according to the learning needs described as tags.

MOOCs (Massive Open Online Courses) promote mass education through collaboration scenarios between participants. The purpose of this paper is to analyze the characteristics of MOOCs that can be incorporated into environments such as OpenCourseWare. We develop a study on how the concept of OCW evolves nowadays: focused on the distribution of open educational resources, towards a concept of collaborative open massive training (as with the MOOC), that not all current learning platforms provide. This new generation of social OCW will be called OCW-S.

In this paper, authors apply the Linked Data Design Issues to describe and retrieve information that is semantically related to open educational resources related to the Engineering Education, that are accessible via the OCW Higher Institutions. Linked data have the potential of create bridges between OCW data silos. To assess the impact of Linked Data in OCW, the authors present an interface of faceted search for open educational content. The authors demonstrate that OCW resource metadata related to engineering open courses can be consumed and enriched using datasets hosted by the LinkedOpenData cloud.

As the Web becomes increasingly populated with diverse data, it continues evolving from a Web of linked documents to a Web Linked Data. This evolution allows relationships to be expressed between content in distributed data sets, enabling the way for integration of raw data from multiple knowledge domains and heterogeneous datasets. However, as the Web becomes increasingly populated with linked data, there is also a need to support users with applications to visualize or to explore available data for a specific task, especially in mobile applications. Examples of these tasks are consuming linked data, or creating new semantic relations between data entities, people and places. With the advent of mobiles, our views and behaviors about access/interaction the Internet are shifting. Specialized applications are available as an important alternative to replace a standard web browser for mobile access. In this article, authors show a three-tier client-server architecture using Android framework. This architecture relies on the RDF data from Linked OpenCourseWare Dataset. Additionally, authors show three proof-of-concept based on architecture which integrates into a common used interface for RDF data management on mobile devices.

Through the application of semantic technologies to describe Open Educational Resources, any agent (human or software-based) could process and understand its contents, therefore, the agent could perform tasks autonomously or in a more effective way. In this paper, we describe the design and validation of the OER-CC ontology, which models the domain knowledge of educational resources licensed under Creative Commons Licenses. One of the most important contributions of this work is that we implement different rules and axioms to identify inconsistencies between rights provided by a licensed on an learning material and particular uses that are performed on it.

Open Educational Practices and Resources are a direct response to privatization of knowledge; they promote their exchange across the world with the aim of increasing human intellectual capacity. In this document we will discuss the Open Educational Practices and Resources Movement and the notion that knowledge is a public good where technology in general, and specifically Web 2.0, provide an extraordinary opportunity for people to acquire key competences in a knowledge society while they share, use, and re-use digital contents. We will describe the key function of tools and services based on Social Software in the Web 2.0 environment in the OERs production, based on experiences gained at the Universidad Técnica Particular de Loja (Ecuador). Moreover, we describe the commitment of the University to the promotion of open educational practices and resources and their impact on society and knowledge economy. This is accomplished through the use of Social Software as a potential key to producing changes in the actual production model, moving from a hierarchical transfer of knowledge from the teacher to a new range of open and collaborative educational practices centered on the student.

Open Educational Resources (OER) are a direct reaction to knowledge privatization; they foment their exchange to the entire world with the aim of increase the human intellectual capacity.In this document, we describe the committment of Universidad Técnica Particular de Loja (UTPL), Ecuador, in the promotion of open educational practices and resources and their impact in society and knowledge economy through the use of Social Software.