Albarillo CUNY Conference On Best Practices
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Albarillo CUNY Conference On Best Practices

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Academic librarians have a long tradition of working with non-native speakers of English in the library. This presentation will explore recent developments in search technology that benefit non-native ...

Academic librarians have a long tradition of working with non-native speakers of English in the library. This presentation will explore recent developments in search technology that benefit non-native speakers of English, focusing on library database resources available at CUNY.

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  • CUNY Library Portal
  • Language personalization most common / subject terms also common ; machine translation (newest) machine reading (new)Databases are adding features that supplement the lack of specialized vocabulary (not only for English Language Learners)--filtering, subject terms
  • Interface language changeInconsistent non-English language search (articles with non-roman scripts difficult to find)Non-English content varies with database
  • Preferred term, vary by database
  • For translating search terms and abstracts

Albarillo CUNY Conference On Best Practices Presentation Transcript

  • 1. Helping ESL Students in the Library: A Look at Language Features in Library Databases Frans Albarillo Librarian for Business and Sociology Brooklyn College
  • 2. Background Applied Linguistics & ESL, French, Linguistics Business students in Hawaii Immigrant (Heritage speaker of Tagalog, French 3rd language) Language technologies in education Not computational linguist
  • 3. Library Vocabulary Vendors: EBSCO, ProQuest, Gale, JSTOR, Elsevier These are companies that sell libraries digital content like journals, e-books, audio, and images
  • 4. Outline CUNY Library Databases http://www.cuny.edu/libraries.html Google Translate (brief) http://translate.google.com/ i2Type (brief) http://www.sciweavers.org/i2type
  • 5. You can find at least one, but usually two of these features in most databases: • language personalization • subject terms (thesaurus) • machine translation • machine reading
  • 6. EBSCO
  • 7. Supports 30 Languages
  • 8. French Example EBSCO
  • 9. Non-English content Search in English Then filter by language Articles with non-roman scripts are difficult to find
  • 10. Scope notes help with search vocabulary
  • 11. Gale
  • 12. French Example Gale (supports 34 languages)
  • 13. No scope notes or definition, clicking on the subject term takes you to articles
  • 14. Gale item record
  • 15. Newer Gale Platform Not all databases have the same features, and features are always being added, so look around
  • 16. ProQuest
  • 17. French Interface
  • 18. Suggest using Google Translate http://translate.google.com/
  • 19. Suggest using i2Type http://www.sciweavers.org/i2type
  • 20. Non-English Journals and Magazines Data from Ulrichs Web August 2012
  • 21. Summary • Look for language/features options, ask your librarian • Machine translation is not perfect, but will help the student do better searches and understand their results • Machine reading builds listening and speaking skills • Google Translate and i2Type are good tools to use when there is no machine translation or subject term lookup • Internet searches in their first language to build concept comprehension (Wikipedia in their language) • More non-English scholarly material will be available
  • 22. Thank you falbarillo@brooklyn.cuny.edu CUNY Library Databases http://www.cuny.edu/libraries.html Google Translate http://translate.google.com/ i2Type http://www.sciweavers.org/i2type