  Language students are most engaged while reading texts at an appropriate
difficulty level. However, existing methods of evaluating text difficulty focus
mainly on vocabulary and do not prioritize grammatical features, hence they do
not work well for language learners with limited knowledge of grammar. In this
paper, we introduce grammatical templates, the expert-identified units of
grammar that students learn from class, as an important feature of text
difficulty evaluation. Experimental classification results show that
grammatical template features significantly improve text difficulty prediction
accuracy over baseline readability features by 7.4%. Moreover, we build a
simple and human-understandable text difficulty evaluation approach with 87.7%
accuracy, using only 5 grammatical template features.
