Skip to main content
Presentation
On Improving the Accuracy of Readability Classification using Insights from Second Language Acquisition
The 7th Workshop on the Innovative Use of NLP for Building Educational Applications (2012)
  • Sowmya Vajjala, Universitat Tubingen
  • Detmar Meurers, Universität Tübingen
Abstract
We investigate the problem of readability assessment using a range of lexical and syntactic features and study their impact on predicting the grade level of texts. As empirical basis, we combined two web-based text sources, Weekly Reader and BBC Bitesize, targeting different age groups, to cover a broad range of school grades. On the conceptual side, we explore the use of lexical and syntactic measures originally designed to measure language development in the production of second language learners. We show that the developmental measures from Second Language Acquisition (SLA) research when combined with traditional readability features such as word length and sentence length provide a good indication of text readability across different grades. The resulting classifiers significantly outperform the previous approaches on readability classification, reaching a classification accuracy of 93.3%.
Publication Date
2012
Location
Montreal, Canada
Comments
Copyright 2012 The Authors
Citation Information
Sowmya Vajjala and Detmar Meurers. "On Improving the Accuracy of Readability Classification using Insights from Second Language Acquisition" The 7th Workshop on the Innovative Use of NLP for Building Educational Applications (2012)
Available at: http://works.bepress.com/sowmya-vajjala/5/