In recent years, the use of recommender systems has become popular on the web. To improve recommendation performance, usage, and scalability, the research has evolved by producing several generations of recommender systems. There is much literature about it, although most proposals focus on traditional methods’ theories and applications. Recently, knowledge graph-based recommendations have attracted attention in academia and the industry because they can alleviate information sparsity and performance problems. We found only two studies that analyze the recommendation system’s role over graphs, but they focus on specific recommendation methods. This survey attempts to cover a broader analysis from a set of selected papers. In summary, the contributions of this paper are as follows: (1) we explore traditional and more recent developments of filtering methods for a recommender system, (2) we identify and analyze proposals related to knowledge graph-based recommender systems, (3) we present the most relevant contributions using an application domain, and (4) we outline future directions of research in the domain of recommender systems. As the main survey result, we found that the use of knowledge graphs for recommendations is an efficient way to leverage and connect a user’s and an item’s knowledge, thus providing more precise results for users.

Purpose: – The aim of this paper is to present an initiative to apply the principles of Linked Data to enhance the search and discovery of OpenCourseWare (OCW) contents created and shared by the universities. Design/methodology/approach: – This paper is a case study of how linked data technologies can be applied for the enhancement of open learning contents. Findings: – Results presented under the umbrella of OCW-Universia consortium, as the integration and access to content from different repositories OCW and the development of a query method to access these data, reveal that linked data would offer a solution to filter and select semantically those open educational contents, and automatically are linked to the linked open data cloud. Originality/value: – The new OCW-Universia integration with linked data adds new features to the initial framework including improved query mechanisms and interoperability.

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.

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.