• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

(2012)

Cached

  • Download as a PDF

Download Links

  • [urd.let.rug.nl]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Unknown Authors
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{12,
    author = {},
    title = {},
    year = {2012}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

This study presents the results from a CALL system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system currently focuses on nouns and employs natural language processing in order to generate a large base of exercise material without extensive tuning by teachers. Language learners used the system over ten sessions, and their improvements were charted. Besides this empirical evaluation, we also sought the opinions of Runyakitara experts about the system (as a judgmental evaluation). Results from the evaluation study indicate that RU_CALL has the ability to assess users ’ knowledge of Runyitara and to enhance grammar and writing skills in the language. This computational resource can be utilized by other interested learners of Runyakitara, and the idea can be extended to other indigenous languages with emigrant populations who wish to maintain their language skills.

Keyphrases

evaluation study    mother tongue deficiency    emigrant population    computational resource    judgmental evaluation    major objective    exercise material    runyakitara expert    language learner    call system    indigenous language    language skill    empirical evaluation    natural language processing    extensive tuning    interested learner    large base    ten session    electronic language   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University