Grammatical Templates: Improving Text Difficulty Evaluation for Language Learners

TL;DR

This paper introduces grammatical templates as a new feature for evaluating text difficulty, significantly enhancing prediction accuracy for language learners by focusing on grammatical complexity rather than just vocabulary.

Contribution

It proposes the use of grammatical templates as an important feature for text difficulty evaluation, improving accuracy and interpretability for language learner texts.

Findings

Grammatical template features improve difficulty prediction accuracy by 7.4%.

A simple model using 5 grammatical features achieves 87.7% accuracy.

Focus on grammar enhances text difficulty assessment for language learners.

Abstract

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.