skip to main content
10.1145/2993412.3003389acmotherconferencesArticle/Chapter ViewAbstractPublication PagesecsawConference Proceedingsconference-collections
short-paper

Bootstrapping an ubiquitous monitoring ecosystem for accelerating vocabulary acquisition

Published:28 November 2016Publication History

ABSTRACT

Learning the vocabulary of a new language is a very slow and time consuming process which can take many years of dedicated study. Free reading is known to be important for improving vocabulary and so are optimally timed repetitions of learned concepts. However, these two have not been put together until now.

This paper presents the architecture of a monitoring ecosystem of applications which tracks the reading activities of a learner and builds a model of their evolving knowledge. Based on this model it can steer their future reading and studying sessions in such a way as to accelerate the speed with which they acquire new vocabulary.

The paper describes several requirements for such an ecosystem, together with a prototpye implementation, and component applications. Finally a series of open questions that highlight opportunities for future research are discussed.

References

  1. M. Lungu, K. Sethi, S. Marti, and L. Schwab, "The Zeeguu API - Modeling Learner Progress to Accelerate Vocabulary Acquisition," Jul. 2016. {Online}. Available:Google ScholarGoogle Scholar
  2. L. Schwab, "Using RSS feeds to support second language acquisition," University of Bern, Bachelor's thesis, Jun. 2016. {Online}. Available: http://scg.unibe.ch/archive/projects/Schw16a.pdfGoogle ScholarGoogle Scholar
  3. P. Giehl, "Zeeguu translate application --- extending the Zeeguu platform to the Android device," University of Bern, Bachelor's thesis, Aug. 2015. {Online}. Available: http://scg.unibe.ch/archive/projects/Gieh15a.pdfGoogle ScholarGoogle Scholar
  4. J. Oosterhof, "Making reading in a second language more enjoyable," Aug. 2016, bachelor's Thesis, University of Groningen.Google ScholarGoogle Scholar
  5. D. Dearman and K. Truong, "Evaluating the implicit acquisition of second language vocabulary using a live wallpaper," in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2012, pp. 1391--1400. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. R. Nienhuis and N. Haan, "Time to learn - A new way of learning with the use of a smartwatch," Aug. 2016, bachelor's Thesis, University of Groningen.Google ScholarGoogle Scholar
  7. S. Jansen, A. Finkelstein, and S. Brinkkemper, "A sense of community: A research agenda for software ecosystems," in Presented at the 31st International Conference on Software Engineering - Companion Volume, 2009. ICSE-Companion 2009, IEEE, 2009, pp. 187--190.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    ECSAW '16: Proccedings of the 10th European Conference on Software Architecture Workshops
    November 2016
    234 pages
    ISBN:9781450347815
    DOI:10.1145/2993412

    Copyright © 2016 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 28 November 2016

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • short-paper

    Acceptance Rates

    Overall Acceptance Rate80of120submissions,67%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader