  Coherence in writing, an aspect that second-language (L2) English learners
often struggle with, is crucial in assessing L2 English writing. Existing
automated writing evaluation systems primarily use basic surface linguistic
features to detect coherence in writing. However, little effort has been made
to correct the detected incoherence, which could significantly benefit L2
language learners seeking to improve their writing. To bridge this gap, we
introduce DECOR, a novel benchmark that includes expert annotations for
detecting incoherence in L2 English writing, identifying the underlying
reasons, and rewriting the incoherent sentences. To our knowledge, DECOR is the
first coherence assessment dataset specifically designed for improving L2
English writing, featuring pairs of original incoherent sentences alongside
their expert-rewritten counterparts. Additionally, we fine-tuned models to
automatically detect and rewrite incoherence in student essays. We find that
incorporating specific reasons for incoherence during fine-tuning consistently
improves the quality of the rewrites, achieving a result that is favored in
both automatic and human evaluations.
