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Yao, Lili; Haberman, Shelby J.; Zhang, Mo – ETS Research Report Series, 2019
Many assessments of writing proficiency that aid in making high-stakes decisions consist of several essay tasks evaluated by a combination of human holistic scores and computer-generated scores for essay features such as the rate of grammatical errors per word. Under typical conditions, a summary writing score is provided by a linear combination…
Descriptors: Prediction, True Scores, Computer Assisted Testing, Scoring
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Breyer, F. Jay; Rupp, André A.; Bridgeman, Brent – ETS Research Report Series, 2017
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…
Descriptors: College Entrance Examinations, Scoring, Essay Tests, Writing Evaluation
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Robin, Frédéric; Bejar, Isaac; Liang, Longjuan; Rijmen, Frank – ETS Research Report Series, 2016
Exploratory and confirmatory factor analyses of domestic data from the" GRE"® revised General Test, introduced in 2011, were conducted separately for the verbal (VBL) and quantitative (QNT) reasoning measures to evaluate the unidimensionality and local independence assumptions required by item response theory (IRT). Results based on data…
Descriptors: College Entrance Examinations, Graduate Study, Verbal Tests, Mathematics Tests
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Ramineni, Chaitanya; Williamson, David – ETS Research Report Series, 2018
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…
Descriptors: Scores, Computer Assisted Testing, Test Scoring Machines, Automation
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Buzick, Heather; Oliveri, Maria Elena; Attali, Yigal; Flor, Michael – Applied Measurement in Education, 2016
Automated essay scoring is a developing technology that can provide efficient scoring of large numbers of written responses. Its use in higher education admissions testing provides an opportunity to collect validity and fairness evidence to support current uses and inform its emergence in other areas such as K-12 large-scale assessment. In this…
Descriptors: Essays, Learning Disabilities, Attention Deficit Hyperactivity Disorder, Scoring