"Biometrics" are physical or behavioral human characteristics that can be used to identify a person. It is widely known that keystroke or typing dynamics for short, fixed texts (e.g., passwords) could serve as a behavioral biometric. In this study, we investigate whether keystroke data from essay responses can lead to a reliable…

In this research report, we present an empirical argument for the use of a contributory scoring approach for the 2-essay writing assessment of the analytical writing section of the "GRE"® test in which human and machine scores are combined for score creation at the task and section levels. The approach was designed to replace a currently…

Notable mean score differences for the "e-rater"® automated scoring engine and for humans for essays from certain demographic groups were observed for the "GRE"® General Test in use before the major revision of 2012, called rGRE. The use of e-rater as a check-score model with discrepancy thresholds prevented an adverse impact…

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 paper explores automated methods for measuring features of student writing and determining their relationship to writing quality and other features of literacy, such as reading rest scores. In particular, it uses the "e-rater"™ automatic essay scoring system to measure "product" features (measurable traits of the final…

This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.

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 experiment involved college students (N = 464) working on an authentic learning task (writing an essay) under 3 conditions: no feedback, detailed feedback (perceived by participants to be provided by the course instructor), and detailed feedback (perceived by participants to be computer generated). Additionally, conditions were crossed with 2…

This study examined the construct validity of the "e-rater"® automated essay scoring engine as an alternative to human scoring in the context of TOEFL® essay writing. Analyses were based on a sample of students who repeated the TOEFL within a short time period. Two "e-rater" scores were investigated in this study, the first…

Eighty-three Test of English as a Foreign Language™ (TOEFL®) CBT writing prompts that were administered between July 1998 and August 2000 were examined in order to identify differences in scores that could be attributed to the response mode chosen by examinees (handwritten or word processed). Differences were examined statistically using…

This study examined scores from 133,906 operationally scored Test of English as a Foreign Language™ (TOEFL®) essays to determine whether the choice of composition medium has any impact on score quality for subgroups of test-takers. Results of analyses demonstrate that (a) scores assigned to word-processed essays are slightly more reliable than…