Complementing human judgment of essays written by English language learners with e-rater ® scoring

E-rater^® is an automated essay scoring system that uses natural language processing techniques to extract features from essays and to model statistically human holistic ratings. Educational Testing Service has investigated the use of e-rater, in conjunction with human ratings, to score one of the two writing tasks on the TOEFL-iBT^® writing section. In this article we describe the TOEFL iBT writing section and an e-rater model proposed to provide one of two ratings for the Independent writing task. We discuss how the evidence for a process that uses both human and e-rater scoring is relevant to four components in a validity argument: (a) Evaluation — observations of performance on the writing task are scored to provide evidence of targeted writing skills; (b) Generalization — scores on the writing task provide estimates of expected scores over relevant parallel versions of the task and across raters; (c) Extrapolation — expected scores on the writing task are consistent with other measures of writing ability; and (d) Utilization — scores on the writing task are useful in educational contexts. Finally, we propose directions for future research that will strengthen the case for using complementary methods of scoring to improve the assessment of EFL writing.