Modeling prompt adherence in student essays

Abstract

Recently, researchers have begun exploring methods of scoring student essays with respect to particular dimensions of quality such as coherence, technical errors, and prompt adherence. The work on modeling prompt adherence, however, has been focused mainly on whether individual sentences adhere to the prompt. We present a new annotated corpus of essaylevel prompt adherence scores and propose a feature-rich approach to scoring essays along the prompt adherence dimension. Our approach significantly outperforms a knowledge-lean baseline prompt adherence scoring system yielding improvements of up to 16.6%. © 2014 Association for Computational Linguistics.