26 research outputs found

    Supporting the Reuse of Open Educational Resources through Open Standards

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    Glahn, C., Kalz, M., Gruber, M., & Specht, M. (2010). Supporting the Reuse of Open Educational Resources through Open Standards. In T. Hirashima, A. F. Mohd Ayub, L. F. Kwok, S. L. Wong, S. C. Kong, & F. Y. Yu (Eds.), Workshop Proceedings of the 18th International Conference on Computers in Education: ICCE2010 (pp. 308-315). November, 29 - December, 3, 2010, Putrajaya, Malaysia: Asia-Pacific Society for Computers in Education.In this paper we analyse open standards for supporting the reuse of OER in different knowledge domains based on a generic architecture for content federation and higher-order services. Plenty OER are available at different institutions. We face the problem that the mere availability of these resources does not directly lead to their reuse. To increase the accessibility we integrated existing resource repositories to allow educational practitioners to discover appropriate resources. On top of this content federation we build higher order services to allow re-authoring and sharing of resources. Open standards play an important role in this process for developing high-level services for lowering the thresholds for the creation, distribution and reuse of OER in higher education.This paper has been partly sponsored by the GRAPPLE project (www.grapple-project.org) that is funded by the European Union within the Framework Programme 7 and the following European Projects funded in the eContentPlus Programme: MACE (ECP-2005-EDU-038098, portal.mace-orject.org), OpenScout (grant ECP-2008-EDU-428016, cf. www.openscout.net), and Share.TEC (ECP-2007-EDU-427015/Share.TEC, www.share-tec.eu)

    A novel approach towards skill-based search and services of Open Educational Resources

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    Ha, K.-H., Niemann, K., Schwertel, U., Holtkamp, P., Pirkkalainen, H., Börner, D. et al (2011). A novel approach towards skill-based search and services of Open Educational Resources. In E. Garcia-Barriocanal, A. Öztürk, & M. C. Okur (Eds.), Metadata and Semantics Research: 5th International Conference MTSR 2011 (pp. 312-323), Izmir, Turkey, October 12-14, 2011. Springer.Open educational resources (OER) have a high potential to address the growing need for training materials in management education and training. Today, a high number of OER in management are already available in a large number of repositories. However, users face barriers as they have to search repository by repository with different interfaces to retrieve the appropriate learning content. In addition, the use of search criteria related to skills, such as learning objectives and skill-levels is not generally supported. The European co-funded project OpenScout addresses these barriers by intelligently connecting leading European OER repositories and providing federated, skillbased search and retrieval web services. On top of this content federation the project supports users with easy-to-apply tools that will accelerate the (re-) use of open content

    Implementing infrastructures for managing learning objects

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    Klemke, R., Ternier, S., Kalz, M., & Specht, M. (2010). Implementing infrastructures for managing learning objects. British Journal of Educational Technology, 41(6), 873-882. doi: 10.1111/j.1467-8535.2010.01127.x PrePrint Version. Original available at: http://dx.doi.org/10.1111/j.1467-8535.2010.01127.x Retrieved October 20, 2010.Making learning objects available is critical to reuse learning resources. Making content transparently available and providing added value to different stakeholders is among the goals of the European Commission's eContentPlus programme. This article analyses standards and protocols relevant for making learning objects accessible in distributed data provider networks. Types of metadata associated with learning objects and methods for metadata generation are discussed. Experiences from European projects highlight problems in implementing infrastructures and mapping metadata types into common application profiles. The use of learning contents and its associated metadata in different scenICOPER, Share.TEC, OpenScou

    The Simple Publishing Interface (SPI)

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    Ternier, S., Massart, D., Totschnig, M., Klerkx, J., & Duval, E. (2010). The Simple Publishing Interface (SPI). D-Lib Magazine, September/October 2010, Volume 16 Number 9/10, doi:10.1045/september2010-ternierThe Simple Publishing Interface (SPI) is a new publishing protocol, developed under the auspices of the European Committee for Standardization (CEN) workshop on learning technologies. This protocol aims to facilitate the communication between content producing tools and repositories that persistently manage learning resources and metadata. The SPI work focuses on two problems: (1) facilitating the metadata and resource publication process (publication in this context refers to the ability to ingest metadata and resources); and (2) enabling interoperability between various components in a federation of repositories. This article discusses the different contexts where a protocol for publishing resources is relevant. SPI contains an abstract domain model and presents several methods that a repository can support. An Atom Publishing Protocol binding is proposed that allows for implementing SPI with a concrete technology and enables interoperability between applications.European Committee for Standardization (CEN), CEN/Expert/2009/3

    Hybrid Multiagent System for Automatic Object Learning Classification

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    The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives

    Exploring the Relevance of Europeana Digital Resources: Preliminary Ideas on Europeana Metadata Quality

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    Europeana is a European project aimed to become the modern “Alexandria Digital Library”, as it targets providing access to thousands of resources of European cultural heritage, contributed by more than fifteen hundred institutions such as museums, libraries, archives and cultural centers. This article aims to explore Europeana digital resources as open learning repositories in order to re-use digital resources to improve learning process in the domain of arts and cultural heritage. To carry out this purpose, we present results of metadata quality based on a study case associated to recommendations and suggestions that provide this type of initiatives in our educational context in order to improve the access of digital resources according to a specific knowledge areas

    A System for Multi-label Classification of Learning Objects

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    The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of Learning Object (LO), which provides ubiquitous access to multiple and distributed educational resources in many repositories. This article presents a system that enables the recovery and classification of LO and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives. For this classification, it is used a special multi-label data mining designed for the LO ranking tasks. According to each position, the system is responsible for presenting the results to the end user. The learning process is supervised, using two major tasks in supervised learning from multi-label data: multi-label classification and label ranking

    Retrieving Learning Resources over the Cloud

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    Reusing resources has been on the rise recently in the ICT sector. In fact, this trend is expanding into other areas such as the educational sector. Learning objects have made it possible to create digital resources that can be reused in various didactic units. These resources are stored in repositories, and thus require a search process that allows them to be located and retrieved. The present study proposes the AIREH tool, which was deployed into a cloud environment and facilitates the retrieval of learning objects by integrating virtual organizations and agents with CBR systems that implement collaborative filtering techniques. Workshop on Learning Technology for Education in Cloud (LTEC'12) Workshop on Learning Technology for Education in Cloud (LTEC'12) Look Inside MyCopy Softcover Edition 24.99 EUR/USD/GBP/CHFEuropean Commision (EC). Funding FP7/SP1/ICT. Project Code: 25741

    Retrieving Learning Resources over the Cloud

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    Reusing resources has been on the rise recently in the ICT sector. In fact, this trend is expanding into other areas such as the educational sector. Learning objects have made it possible to create digital resources that can be reused in various didactic units. These resources are stored in repositories, and thus require a search process that allows them to be located and retrieved. The present study proposes the AIREH tool, which was deployed into a cloud environment and facilitates the retrieval of learning objects by integrating virtual organizations and agents with CBR systems that implement collaborative filtering techniques

    A Federated Recommender System for Online Learning Environments

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    From e-commerce to social networking sites, recommender systems are gaining more and more interest. They provide connections, news, resources, or products of interest. This paper presents a federated recommender system, which exploits data from different online learning platforms and delivers personalized recommendation. The underlying educational objective is to enable academic institutions to provide a Web 2.0 dashboard bringing together open resources from the Cloud and proprietary content from in-house learning management systems. The paper describes the main aspects of the federated recommender system, including its adopted architecture, the common data model used to harvest the different learning platforms, the recommendation algorithm, as well as the recommendation display widget
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