Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…

Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…

This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…