Sowmya Vajjala and Detmar Meurers
Proceedings of the 7th Workshop on Innovative Use of NLP for Building Educational Applications (BEA7). 2012..
We investigate the problem of readability assessment using a range of lexical and syntac- tic features and study their impact on predicting the grade level of texts. As empirical ba- sis, 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%.
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Bibtex entry:
@InProceedings{Vajjala.Meurers-12,
author = {Sowmya Vajjala and Meurers, Detmar},
title = {On Improving the Accuracy of Readability Classification
using Insights from Second Language Acquisition},
booktitle = {Proceedings of the 7th Workshop on
Innovative Use of NLP for Building Educational Applications
(BEA7)},
year = {2012},
address = {Montreal, Canada},
publisher = {Association for Computational Linguistics},
pages = {163–-173},
url = {http://purl.org/dm/papers/vajjala-meurers-12.html}
}