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.…

Research and development of a new type of scoring rubric for the integrated speaking tasks of "TOEFL iBT"® are described. These "analytic rating guides" could be helpful if tasks modeled after those in TOEFL iBT were used for formative assessment, a purpose which is different from TOEFL iBT's primary use for admission…

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…

Because there is no commonly accepted view of what makes for good writing, automated essay scoring (AES) ideally should be able to accommodate different theoretical positions, certainly at the level of state standards but also perhaps among teachers at the classroom level. This paper presents a practical approach and an interactive computer…

This study addressed concerns about the potential for differential gains in reading during the first 2 years of formal schooling (K-1) versus the next 2 years of schooling (1st-3rd grade). A multilevel piecewise regression with a node at spring 1st grade was used in order to define separate regressions for the two time periods. Empirical Bayes…

This report is the first of four that stem from a study of The Impact of Approved Induction Programs on Student Learning (IAIPSL), conducted by Educational Testing Service (ETS) and funded by the California Commission on Teacher Credentialing (CCTC). The IAIPSL study began in July 2002 and continued through April 2004. The purpose of the study is…