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Wang, Wei; Dorans, Neil J. – ETS Research Report Series, 2021
Agreement statistics and measures of prediction accuracy are often used to assess the quality of two measures of a construct. Agreement statistics are appropriate for measures that are supposed to be interchangeable, whereas prediction accuracy statistics are appropriate for situations where one variable is the target and the other variables are…
Descriptors: Classification, Scaling, Prediction, Accuracy
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Chen, Jing; Fife, James H.; Bejar, Isaac I.; Rupp, André A. – ETS Research Report Series, 2016
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…
Descriptors: Scoring, Models, Artificial Intelligence, Automation
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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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Chen, Jing; Zhang, Mo; Bejar, Isaac I. – ETS Research Report Series, 2017
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…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essay Tests
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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M. – ETS Research Report Series, 2015
Automated scoring models were trained and evaluated for the essay task in the "Praxis I"® writing test. Prompt-specific and generic "e-rater"® scoring models were built, and evaluation statistics, such as quadratic weighted kappa, Pearson correlation, and standardized differences in mean scores, were examined to evaluate the…
Descriptors: Writing Tests, Licensing Examinations (Professions), Teacher Competency Testing, Scoring
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Rios, Joseph A.; Sparks, Jesse R.; Zhang, Mo; Liu, Ou Lydia – ETS Research Report Series, 2017
Proficiency with written communication (WC) is critical for success in college and careers. As a result, institutions face a growing challenge to accurately evaluate their students' writing skills to obtain data that can support demands of accreditation, accountability, or curricular improvement. Many current standardized measures, however, lack…
Descriptors: Test Construction, Test Validity, Writing Tests, College Outcomes Assessment
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Zhang, Mo – ETS Research Report Series, 2013
Many testing programs use automated scoring to grade essays. One issue in automated essay scoring that has not been examined adequately is population invariance and its causes. The primary purpose of this study was to investigate the impact of sampling in model calibration on population invariance of automated scores. This study analyzed scores…
Descriptors: Automation, Scoring, Essay Tests, Sampling
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Breyer, F. Jay; Attali, Yigal; Williamson, David M.; Ridolfi-McCulla, Laura; Ramineni, Chaitanya; Duchnowski, Matthew; Harris, April – ETS Research Report Series, 2014
In this research, we investigated the feasibility of implementing the "e-rater"® scoring engine as a check score in place of all-human scoring for the "Graduate Record Examinations"® ("GRE"®) revised General Test (rGRE) Analytical Writing measure. This report provides the scientific basis for the use of e-rater as a…
Descriptors: Computer Software, Computer Assisted Testing, Scoring, College Entrance Examinations
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Attali, Yigal; Sinharay, Sandip – ETS Research Report Series, 2015
The "e-rater"® automated essay scoring system is used operationally in the scoring of "TOEFL iBT"® independent and integrated tasks. In this study we explored the psychometric added value of reporting four trait scores for each of these two tasks, beyond the total e-rater score.The four trait scores are word choice, grammatical…
Descriptors: Writing Tests, Scores, Language Tests, English (Second Language)
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Heilman, Michael; Madnani, Nitin – ETS Research Report Series, 2012
Many writing assessments use generic prompts about social issues. However, we currently lack an understanding of how test takers respond to such prompts. In the absence of such an understanding, automated scoring systems may not be as reliable as they could be and may worsen over time. To move toward a deeper understanding of responses to generic…
Descriptors: Writing Evaluation, Scoring, Prompting, Responses
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Fu, Jianbin; Chung, Seunghee; Wise, Maxwell – ETS Research Report Series, 2013
The Cognitively Based Assessment of, for, and as Learning ("CBAL"™) research initiative is aimed at developing an innovative approach to K-12 assessment based on cognitive competency models. Because the choice of scoring and equating approaches depends on test dimensionality, the dimensional structure of CBAL tests must be understood.…
Descriptors: Cognitive Measurement, Cognitive Ability, Scoring, Grade 4
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Attali, Yigal; Sinharay, Sandip – ETS Research Report Series, 2015
The "e-rater"® automated essay scoring system is used operationally in the scoring of the argument and issue tasks that form the Analytical Writing measure of the "GRE"® General Test. For each of these tasks, this study explored the value added of reporting 4 trait scores for each of these 2 tasks over the total e-rater score.…
Descriptors: Scores, Computer Assisted Testing, Computer Software, Grammar
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Deane, Paul – ETS Research Report Series, 2014
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…
Descriptors: Writing Processes, Writing Evaluation, Student Evaluation, Writing Skills
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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent – ETS Research Report Series, 2012
Scoring models for the "e-rater"® system were built and evaluated for the "TOEFL"® exam's independent and integrated writing prompts. Prompt-specific and generic scoring models were built, and evaluation statistics, such as weighted kappas, Pearson correlations, standardized differences in mean scores, and correlations with…
Descriptors: Scoring, Prompting, Evaluators, Computer Software
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Zhang, Mo; Breyer, F. Jay; Lorenz, Florian – ETS Research Report Series, 2013
In this research, we investigated the suitability of implementing "e-rater"® automated essay scoring in a high-stakes large-scale English language testing program. We examined the effectiveness of generic scoring and 2 variants of prompt-based scoring approaches. Effectiveness was evaluated on a number of dimensions, including agreement…
Descriptors: Computer Assisted Testing, Computer Software, Scoring, Language Tests
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