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Chan, Kinnie Kin Yee; Bond, Trevor; Yan, Zi – Language Testing, 2023
We investigated the relationship between the scores assigned by an Automated Essay Scoring (AES) system, the Intelligent Essay Assessor (IEA), and grades allocated by trained, professional human raters to English essay writing by instigating two procedures novel to written-language assessment: the logistic transformation of AES raw scores into…
Descriptors: Computer Assisted Testing, Essays, Scoring, Scores
Latifi, Syed; Gierl, Mark – Language Testing, 2021
An automated essay scoring (AES) program is a software system that uses techniques from corpus and computational linguistics and machine learning to grade essays. In this study, we aimed to describe and evaluate particular language features of Coh-Metrix for a novel AES program that would score junior and senior high school students' essays from…
Descriptors: Writing Evaluation, Computer Assisted Testing, Scoring, Essays
Plakans, Lia; Gebril, Atta; Bilki, Zeynep – Language Testing, 2019
The present study investigates integrated writing assessment performances with regard to the linguistic features of complexity, accuracy, and fluency (CAF). Given the increasing presence of integrated tasks in large-scale and classroom assessments, validity evidence is needed for the claim that their scores reflect targeted language abilities.…
Descriptors: Accuracy, Language Tests, Scores, Writing Evaluation
Enright, Mary K.; Quinlan, Thomas – Language Testing, 2010
E-rater[R] 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[R] writing…
Descriptors: Second Language Learning, Scoring, Essays, Language Processing