Logo Oapen
  • Join
    • Deposit
    • For Librarians
    • For Publishers
    • For Researchers
    • Funders
    • Resources
    • OAPEN
        View Item 
        •   OAPEN Home
        • View Item
        •   OAPEN Home
        • View Item
        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Computer-Driven Instructional Design with INTUITEL

        Proposal review

        Thumbnail
        Download PDF Viewer
        Contributor(s)
        Fuchs, Kevin (editor)
        Henning, Peter A. (editor)
        Collection
        EU collection
        Language
        English
        Show full item record
        Abstract
        INTUITEL is a research project that was co-financed by the European Commission with the aim to advance state-of-the-art e-learning systems via addition of guidance and feedback for learners. Through a combination of pedagogical knowledge, measured learning progress and a broad range of environmental and background data, INTUITEL systems will provide guidance towards an optimal learning pathway. This allows INTUITEL-enabled learning management systems to offer learners automated, personalised learning support so far only provided by human tutors INTUITEL is - in the first place - a design pattern for the creation of adaptive e-learning systems. It focuses on the reusability of existing learning material and especially the annotation with semantic meta data. INTUITEL introduces a novel approach that describes learning material as well as didactic and pedagogical meta knowledge by the use of ontologies. Learning recommendations are inferred from these ontologies during runtime. This way INTUITEL solves a common problem in the field of adaptive systems: it is not restricted to a certain field. Any content from any domain can be annotated. The INTUITEL research team also developed a prototype system. Both the theoretical foundations and how to implement your own INTUITEL system are discussed in this book.
        URI
        https://library.oapen.org/handle/20.500.12657/59737
        Keywords
        Computer programming / software engineering; Energy
        DOI
        10.1201/9781003337690
        ISBN
        9781000794236, 9781000794236, 9788793519510, 9781003337690
        Publisher
        Taylor & Francis
        Publisher website
        https://taylorandfrancis.com/
        Publication date and place
        2017
        Grantor
        • European Commission - [...]
        Imprint
        River Publishers
        Classification
        Computer programming / software engineering
        Energy
        Pages
        178
        Rights
        http://creativecommons.org/licenses/by-nc/4.0
        • Imported or submitted locally

        Browse

        All of OAPENSubjectsPublishersLanguagesCollections

        My Account

        LoginRegister

        Export

        Repository metadata
        Logo Oapen
        • For Librarians
        • For Publishers
        • For Researchers
        • Funders
        • Resources
        • OAPEN

        Newsletter

        • Subscribe to our newsletter
        • view our news archive

        Follow us on

        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

        OAPEN is based in the Netherlands, with its registered office in the National Library in The Hague.

        Director: Niels Stern

        Address:
        OAPEN Foundation
        Prins Willem-Alexanderhof 5
        2595 BE The Hague
        Postal address:
        OAPEN Foundation
        P.O. Box 90407
        2509 LK The Hague

        Websites:
        OAPEN Home: www.oapen.org
        OAPEN Library: library.oapen.org
        DOAB: www.doabooks.org

         

         

        Export search results

        The export option will allow you to export the current search results of the entered query to a file. Differen formats are available for download. To export the items, click on the button corresponding with the preferred download format.

        A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

        To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

        After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.