An increasing number of language testing companies are developing and deploying deep learning-based automated essay scoring systems (AES) to replace traditional approaches that rely on handcrafted feature extraction. However, there is hesitation to accept neural network approaches to automated essay scoring because the features are automatically…

As automated scoring systems for spoken responses are increasingly used in language assessments, testing organizations need to analyze their performance, as compared to human raters, across several dimensions, for example, on individual items or based on subgroups of test takers. In addition, there is a need in testing organizations to establish…

Automated essay scoring can produce reliable scores that are highly correlated with human scores, but is limited in its evaluation of content and other higher-order aspects of writing. The increased use of automated essay scoring in high-stakes testing underscores the need for human scoring that is focused on higher-order aspects of writing. This…