The "e-rater"® automated scoring engine used at Educational Testing Service (ETS) scores the writing quality of essays. In the current practice, e-rater scores are generated via a multiple linear regression (MLR) model as a linear combination of various features evaluated for each essay and human scores as the outcome variable. This…

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…

This study investigates the relationship between test preparation and test performance on the "TOEFL iBT"® exam. Information on background variables and test preparation strategies was gathered from 14,593 respondents in China through an online survey. A Chinese standardized English test was used as a control for prior English ability.…

For many purposes, it is useful to collect a corpus of texts all produced to the same stimulus, whether to measure performance (as on a test) or to test hypotheses about population differences. This paper examines several methods for measuring similarities in phrasing and content and demonstrates that these methods can be used to identify…