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Language Technologies Mash-Ups

Language Technologies Mash-Ups. Wolfgang Greller (OUNL) Bernhard Hoisl (WUW) Kamakshi Rajagopal (OUNL). JTEL Winterschool Innsbruck 4 February 2010.

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Language Technologies Mash-Ups

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  1. Language Technologies Mash-Ups Wolfgang Greller (OUNL) Bernhard Hoisl (WUW) KamakshiRajagopal (OUNL) JTEL Winterschool Innsbruck 4 February 2010 The LTfLL project is partially supported/co-funded by the European Union under the Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D

  2. Set of Tools • Addressing two areas of TEL: • help people learn • help tutors/teachers support learners

  3. Three Themes • Positioning the learner • Feedback Support • Knowledge retrieval and sharing Tutor/Learner support not fully automated system

  4. Innovative New Designs Create next-generation support and advice services for individual and collaborative learning using language technologies (LSA, NLP, etc)

  5. Personalised Services Individual feedback and support

  6. Different Languages Language corpora

  7. Personal Learning Environment Mash-up PLE Widgets to mix and match

  8. Fitness for Purpose Analysing stakeholder needs Validation loops and pilots

  9. Scenario-Based Design Real problems Practical solutions

  10. Development Cycle 2008 2011 ROUND 1 ROUND 2 ROUND 3 Scenarios v 1.0 Validation Scenarios v 2.0 Validation Development V 1.0 Scenarios v 3.0 Validation Development V 2.0 Roadmap Milestone Milestone Milestone

  11. Services Positioning the learner • Accreditation of Prior Learning, Position in Curriculum • Feedback on the conceptual development of the learner Feedback Support • Feedback and assessing the contribution of learners in online discussions • Supporting individuals in their understanding through reading texts and making summaries Knowledge retrieval and sharing • Supporting teachers in finding online resources to design courses • Supporting knowledge discovery through semantic searches and ontologies • Knowledge discovery through finding relevant expertise (either of teachers or peers) in learning networks

  12. Positioning the Learner Accreditation of Prior Learning in formal learning Matching learner’s evidences with course content

  13. Positioning the Learner Problem-based learning – workplace learning Give formative feedback on conceptual development of learner Benefit for individual learner (coverage of domain concepts and comparison with peer group) Benefit for tutor (recognition of individual coverage, assist in personal feedback. Identify topics missed by group as a whole)

  14. Feedback Support Use of social media in formal learning Provide more feedback (through analyses and information) on the interactions on chat and forums between learners, to the tutor and learner.

  15. Feedback Support Learners’ reading and writing Live feedback on summary-writing by the learner

  16. Knowledge Retrieval and Sharing Creating Learning Resources Semantic, text and ontology-based searches can identify suitable learning objects (enhancing received quality)

  17. Knowledge Retrieval and Sharing Creating Learning Resources with input of network Enhance formal ontologies with informal folksonomies and tags to extend search, incl. visualisation of related concepts. Finding relevant expertise (teacher or peers) within networks that the person knows, crawling the user’s networks (friends, FOAFs).

  18. Hands-on Task Identify challenges to the potential adoption of the tools for teachers, lifelong learners, institutions Identify added-value integration possibilities between two or more tools

  19. Development Cycle 2008 2011 Validation Design v 3.0 Validation Development V 2.0 Threads

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