  Developing a text readability assessment model specifically for texts in a
foreign English Language Training (ELT) curriculum has never had much attention
in the field of Natural Language Processing. Hence, most developed models show
extremely low accuracy for L2 English texts, up to the point where not many
even serve as a fair comparison. In this paper, we investigate a text
readability assessment model for L2 English learners in Korea. In accordance,
we improve and expand the Text Corpus of the Korean ELT curriculum
(CoKEC-text). Each text is labeled with its target grade level. We train our
model with CoKEC-text and significantly improve the accuracy of readability
assessment for texts in the Korean ELT curriculum.
