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Language Technologies Mash- Ups Wolfgang Greller (OUNL) Bernhard Hoisl (WUW) Kamakshi Rajagopal (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

Language Technologies Mash-Ups

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

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Language Technologies Mash-Ups

Wolfgang Greller (OUNL)Bernhard Hoisl (WUW)Kamakshi Rajagopal (OUNL)

JTEL WinterschoolInnsbruck

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

Set of Tools

Addressing two areas of TEL:- help people learn- help tutors/teachers support learners

Three Themes

Positioning the learnerFeedback SupportKnowledge retrieval and sharing

Tutor/Learner support not fully automated system

Innovative New DesignsCreate next-generation support and advice services for

individual and collaborative learning using language technologies (LSA, NLP, etc)

Personalised Services

Individual feedback and support

Different Languages

Language corpora

Personal Learning Environment

Mash-up PLEWidgets to mix and match

Fitness for PurposeAnalysing stakeholder needsValidation loops and pilots

Scenario-Based Design

Real problems

Practical solutions

Development Cycle

Milestone

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Milestone

2008 2011

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ServicesPositioning the learner• Accreditation of Prior Learning, Position in Curriculum• Feedback on the conceptual development of the learnerFeedback Support• Feedback and assessing the contribution of learners in online discussions• Supporting individuals in their understanding through reading texts and

making summariesKnowledge 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

Positioning the Learner

Accreditation of Prior Learning in formal learning

Matching learner’s evidences with course content

Positioning the LearnerProblem-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)

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.

Feedback Support

Learners’ reading and writing

Live feedback on summary-writing by the learner

Knowledge Retrieval and Sharing

Creating Learning Resources

Semantic, text and ontology-based searches can identify suitable learning objects (enhancing received quality)

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).

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

Development Cycle2008 2011

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