Human raters and machine scoring systems potentially have complementary strengths in evaluating language ability; specifically, it has been suggested that automated systems might be used to make consistent measurements of specific linguistic phenomena, whilst humans evaluate more global aspects of performance. We report on an empirical study that…

Recent advances in machine learning have made automated scoring of learner speech widespread, and yet validation research that provides support for applying automated scoring technology to assessment is still in its infancy. Both the educational measurement and language assessment communities have called for greater transparency in describing…

At the heart of most assessments lies a set of questions, and those who write them must achieve "two" things. Not only must they ensure that each question elicits the kind of performance that shows how "good" pupils are at the subject, but they must also ensure that each mark scheme gives more marks to those who are…