Janneth Chicaiza

An approach for description of Open Educational Resources based on semantic technologies

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.

Open educational practices and resources based on social software, UTPL experience

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.

Domain Categorization of Open Educational Resources Based on Linked Data

One of the main objectives of open knowledge, and specifically of Open Educational Resource movement, is to allow people to access the resources they need for learning. The first step to that a learner starts this process is to find information and resources according to his/her needs. One of the reasons why OERs could stay hidden and therefore to be underutilized is that each institution and producer of this kind of resources, labels them using tags or informal and heterogeneous knowledge schemes. This issue was identified in the Open Education Consortium (until recently called OpenCourseWare Consortium) study, where respondents noted that one way to improve the courses is to make a “major better categorization of courses according to subject areas”. In previous works, the authors present the Linked OpenCourseWare Data project, which published metadata of courses coming from different open educational datasets. So far there are over 7000 indexed courses associated to 626 topic names or knowledge fields, however, appear different names meaning similar areas or they are written in different languages and also correspond to different detail level. The semantic lack in the relations between areas and subjects make it difficult to find associations between topics and to list recommendations about resources for learners. In this work, authors present a process to support semi-automatic classification of Open Educational Resources, taking advantage from linked data available in the Web through systems made by people who can converge to a formal knowledge organization system.

Finding OERs with Social-Semantic search

Social and semantic web can be complementary approaches searching web resources. This cooperative approach lets enable a semantic search engine to find accurate results and annotate web resources. This work develops the components of a Social-Semantic search architecture proposed by the authors to find open educational resources (OER). By means of metadata enrichment and logic inference, OER consumers get more precise results from general search engines. The Search prototype has been applied to find OER related with computers and engineering in a domain provided by OpenCourseWare materials from two universities, MIT and UTPL. The semantic search answers reasonably well the queta collected.

Measuring collaboration and creativity skills through rubrics: Experience from UTPL collaborative social networks course

In this paper, we introduce several rubrics to measure a set of collaborative and creativity grading. Rubrics are powerful tools for both teaching - learning and assessment. Rubrics improve communication between teachers and students. This work relates the general criteria to measure the complexity levels in the development of creativity and collaborative work competences with concrete indicators associated with the use of Social Web tools and concepts. These indicators have been used in the assessment of competences in a particular course related with the use of collaborative networks.

Supporting openness of MOOCs contents through of an OER and OCW framework based on Linked Data technologies

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.

OCW-S: Enablers for building sustainable open education evolving OCW and MOOC

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.

OER Development and Promotion. Outcomes of an International Research Project on the OpenCourseWare Model

In this paper, we describe the successful results of an international research project focused on the use of Web technology in the educational context. The article explains how this international project, funded by public organizations and developed over the last two academic years, focuses on the area of open educational resources (OER) and particularly the educational content of the OpenCourseWare (OCW) model. This initiative has been developed by a research group composed of researchers from three countries. The project was enabled by the Universidad Politecnica de Madrid OCW Offices leadership of the Consortium of Latin American Universities and the distance education know-how of the Universidad Tecnica Particular de Loja (UTPL, Ecuador). We give a full account of the project, methodology, main outcomes and validation. The project results have further consolidated the group, and increased the maturity of group members and networking with other groups in the area. The group is now participating in other research projects that continue the lines developed here.

Design Study of OER-CC Ontology - A Semantic Web Approach to Describe Open Educational Resources

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.

OER Recommendation for Entrepreneurship Using a Framework Based on Social Network Analysis

In these days, much of the information published on the Web is published on social media, represented through social networks such as Facebook or Twitter, to name only the most prominent. Each of the media and social networks has its own scheme of operation and different working characteristics; for example, Twitter is a social network where millions of daily messages called tweets are exchanged. The message labels, called hashtags, can be used to identify the subject of the message. The message may also include links to other resources that expand the original content or show interesting information. Another kind of information present in Twitter is the relationship between users, the most common of which is a non-reciprocal relationship named “following.” The scope of this paper is to use the information that is published on Twitter to extract and recommend open educational resources, which will be used in the StartUp project. The StartUp project (intelligent training needs assessment and open educational resources to foster entrepreneurship) is co-funded with support from the European Commission under the Lifelong Learning Programme, which has a specific objective to provide effective open educational resources corresponding to individual learning needs. The extraction of information posted on social networks is solved in this paper through the use of linked data that allow retrieving resources and link them with other external sources, graphs that help represent the working scheme of a social network, and with social network analysis, a technique used to discover relevant information that goes beyond individual properties. The results obtained are a set of recommendations about users (identified as experts), hashtags (thematically related), and URLs (digital resources), according to the main competence areas defined by StartUp. This information will form part of the learning paths provided by the project platform.