Despite the current potential to use computers to automatically generate a large range of text-based indices, many issues remain unresolved about how to apply these data in established language teaching and assessment contexts. One way to resolve these issues is to explore the degree to which automatically generated indices, which are reflective…

Researchers have found numerous differences in the approaches raters take to the complex task of essay rating including differences when rating native (L1) and non-native (L2) English writing. Yet less is known about raters' reading practices while scoring those essays. This small-scale study uses eye-tracking technology and reflective protocols…

Background: Marking of essays is mainly carried out by human raters who bring in their own subjective and idiosyncratic evaluation criteria, which sometimes lead to discrepancy. This discrepancy may in turn raise issues like reliability and fairness. The current research attempts to explore the evaluation criteria of markers on a national level…

This study investigates the potential for linguistic microfeatures related to length, complexity, cohesion, relevance, topic, and rhetorical style to predict L2 writing proficiency. Computational indices were calculated by two automated text analysis tools (Coh- Metrix and the Writing Assessment Tool) and used to predict human essay ratings in a…