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eMargin Presentation given to Skills Funding Agency
 

eMargin Presentation given to Skills Funding Agency

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Presentation on the eMargin collaborative text annotation tool given to the Skills Funding Agency. Also contains description of AHRC Knowledge Transfer Fellowship project, working with A Level English ...

Presentation on the eMargin collaborative text annotation tool given to the Skills Funding Agency. Also contains description of AHRC Knowledge Transfer Fellowship project, working with A Level English Language students.

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eMargin Presentation given to Skills Funding Agency eMargin Presentation given to Skills Funding Agency Presentation Transcript

  • eMargin: a collaborative textual annotation tool rdues.bcu.ac.uk Research & Development Unit for English Studies Andrew Kehoe & Matt Gee
    • Study of a collection of electronic texts to discover new facts about the language.
    • Determining meaning by viewing a word/phrase in context: concordances / collocation
    Our Research: Corpus Linguistics MI5 was a Soviet mole . He also claims there have you got a mole on your left shoulder in love with the mole on your cheek which showed that a mole had passed them details summiteers ended atop a mole hill rather than a mountain apparently blind like a mole . The modern tank with raven and the Mafia mole , the anonymous letters and the talpa, the suspected mole who betrayed details of a mountain out of a mole hill . The House of Commons' committee could have been a mole within the KGB i tself,
  • ICT Aspects of Our Work
    • Building own large-scale search engine for linguistic study
    • 10 billion word collection of web texts
    • Extracting examples of real language use
    • www.webcorp.org.uk
    • Developing software to analyse large text collections: crawling, indexing, search, linguistic refinement
    • EPSRC-funded research projects with associated software:
    Classifying New Words Document Similarity Semantic Relations synonyms, antonyms Word Dispreference
  • New Audiences
    • Bringing Corpus Linguistic techniques and software tools to new audiences:
      • English Literature students and readers in general
      • A-Level English Language students (AHRC Knowledge Transfer Fellowship)
  • AHRC Knowledge Transfer Fellowship Introducing A-Level English Language students to empirical text study using the WebCorp Linguist's Search Engine
    • Working with partner school (Stratford Grammar) to develop open learning resources
    • Presenting basic corpus linguistic principles, tailored to A-Level Assessment Objectives (AQA Syllabus B)
    • Series of ‘master classes’, supported by learning materials, interactive online quizzes and specially-designed search tools
    • Also improving digital literacy : using a Virtual Learning Environment; learning to search more effectively
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  • Christmas fax
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  • Issue: English Literature Study How do you study a printed text? ‘ Close Reading’: detailed study of short text extracts down to individual word level.
    • (re-)read the text
    • underline important words
    • make notes in margin
    • colour-code
    • draw out themes/motifs
  • Limitations of Traditional Model
    • Annotations tied to printed copy of text
    • Difficult to share / combine in class
    • Annotations not archivable / searchable
    • Text quickly becomes cluttered with underlining/notes on each re-reading.
  • Increasing emphasis on e-texts but surprising lack of software to support close reading. Difficult to annotate (‘sticky notes’) Difficult to search annotations Difficult to share annotations
    • ‘ Book Lovers Fear Dim Future for Notes in the Margins’, New York Times, Feb 20 2011:
      • writing comments alongside passages…is a rich literary pastime , sometimes regarded as a tool of literary archaeology, …but it has an uncertain fate in a digitalized world
    Limitations of Traditional Model
  • Our Solution
    • Web-based collaborative annotation system operating down to word level .
    • Initial idea late-2007; basic prototype developed allowing simple text highlighting and commenting.
    • Trialled in English classes at BCU.
    • Pilot study at University of Leicester suggested which features of most use in full version.
  • Project
    • £50k JISC Learning & Teaching Innovation grant
    • June 2011 – May 2012
    • Building a more robust, fully-functioning, open-source collaborative text annotation system
    • System to be developed iteratively, with classroom testing and student/teacher feedback
  • Demonstration of Features
  • Proposed Features: Wiki
    • Annotation search
      • Colour
      • Tag
      • Text in comments
      • Text in wiki entries
      • User
      • Date
    • Concordancing: examples of a word / phrase shown in context
    Proposed Features: Search
    • Uploader controls the text
      • which users/groups have access
    • Roles can be assigned
      • contribute
      • moderate
      • alter access
    • Features can be enabled/disabled
      • commenting, tags, wiki entries, look-up, search
    • History of user activities is kept
    Proposed Features: Group Management & Moderation
  • Proposed Features: Text Selection / Uploading Ctrl-C http://www.website.com/text
  • Beyond English & Beyond HE
    • English Literature in first instance but transferable to any text-type and text-based discipline: Law, Social Sciences, Theology, Languages.
    • Collaborative research/editing tool.
    • Integration with existing VLEs (e.g. Moodle ); e-assessment tool.
    • Integration with e-readers.
    • Outside HE: interest from AHRC KTF partners and other schools (inc. United World College of SE Asia)
    http://emargin.bcu.ac.uk
  • Extra Content
  • An Established Tradition
    • Origins in study of religious texts dating back to Middle Ages.
    Martin Luther: Lectures on Romans (1515) Glossae: student’s notes in the margins
  • Pilot Study
    • Structured feedback collected from 25 Leicester students across 3 modules (2 BA, 1 MA).
    • 96% found word-level commenting useful.
    • 88% found highlighting useful.
    • 92% agreed that “reading others’ comments helped me formulate my own ideas”.
    • 96% found prototype ‘easy’ to use.
    • Leicester wishes to use full version with whole 1 st yr.
    • Pilot study suggested which features of most use.
    • Testing Intuitions:
    • “ Dickens is known for a rich range of writing styles-indignant, ironical, melodramatic, and sentimental, all of which appear in David Copperfield . To set the nostalgic tone for this novel, he also uses certain words like "little" and "old" more than usual , so his language seems especially sentimental.” ( Barron’s Book Notes: David Copperfield , 1985, p.32)
    Corpus Linguistic Tools
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