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Showing 1 to 15 of 18 results Save | Export
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Paul Deane; Duanli Yan; Katherine Castellano; Yigal Attali; Michelle Lamar; Mo Zhang; Ian Blood; James V. Bruno; Chen Li; Wenju Cui; Chunyi Ruan; Colleen Appel; Kofi James; Rodolfo Long; Farah Qureshi – ETS Research Report Series, 2024
This paper presents a multidimensional model of variation in writing quality, register, and genre in student essays, trained and tested via confirmatory factor analysis of 1.37 million essay submissions to ETS' digital writing service, Criterion®. The model was also validated with several other corpora, which indicated that it provides a…
Descriptors: Writing (Composition), Essays, Models, Elementary School Students
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Carol Eckerly; Yue Jia; Paul Jewsbury – ETS Research Report Series, 2022
Testing programs have explored the use of technology-enhanced items alongside traditional item types (e.g., multiple-choice and constructed-response items) as measurement evidence of latent constructs modeled with item response theory (IRT). In this report, we discuss considerations in applying IRT models to a particular type of adaptive testlet…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Scoring
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Loukina, Anastassia; Zechner, Klaus; Yoon, Su-Youn; Zhang, Mo; Tao, Jidong; Wang, Xinhao; Lee, Chong Min; Mulholland, Matthew – ETS Research Report Series, 2017
This report presents an overview of the "SpeechRater"? automated scoring engine model building and evaluation process for several item types with a focus on a low-English-proficiency test-taker population. We discuss each stage of speech scoring, including automatic speech recognition, filtering models for nonscorable responses, and…
Descriptors: Automation, Scoring, Speech Tests, Test Items
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Zechner, Klaus; Chen, Lei; Davis, Larry; Evanini, Keelan; Lee, Chong Min; Leong, Chee Wee; Wang, Xinhao; Yoon, Su-Youn – ETS Research Report Series, 2015
This research report presents a summary of research and development efforts devoted to creating scoring models for automatically scoring spoken item responses of a pilot administration of the Test of English-for-Teaching ("TEFT"™) within the "ELTeach"™ framework.The test consists of items for all four language modalities:…
Descriptors: Scoring, Scoring Formulas, Speech Communication, Task Analysis
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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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van Rijn, Peter W.; Ali, Usama S. – ETS Research Report Series, 2018
A computer program was developed to estimate speed-accuracy response models for dichotomous items. This report describes how the models are estimated and how to specify data and input files. An example using data from a listening section of an international language test is described to illustrate the modeling approach and features of the computer…
Descriptors: Computer Software, Computation, Reaction Time, Timed Tests
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Rupp, André A.; Casabianca, Jodi M.; Krüger, Maleika; Keller, Stefan; Köller, Olaf – ETS Research Report Series, 2019
In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…
Descriptors: Automation, Foreign Countries, English (Second Language), Language Tests
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Ackerman, Debra J. – ETS Research Report Series, 2020
Over the past 8 years, U.S. kindergarten classrooms have been impacted by policies mandating or recommending the administration of a specific kindergarten entry assessment (KEA) in the initial months of school as well as the increasing reliance on digital technology in the form of mobile apps, touchscreen devices, and online data platforms. Using…
Descriptors: Kindergarten, School Readiness, Computer Assisted Testing, Preschool Teachers
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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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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent – ETS Research Report Series, 2012
Automated scoring models for the "e-rater"® scoring engine were built and evaluated for the "GRE"® argument and issue-writing tasks. Prompt-specific, generic, and generic with prompt-specific intercept scoring models were built and evaluation statistics such as weighted kappas, Pearson correlations, standardized difference in…
Descriptors: Scoring, Test Scoring Machines, Automation, Models
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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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Evanini, Keelan; Heilman, Michael; Wang, Xinhao; Blanchard, Daniel – ETS Research Report Series, 2015
This report describes the initial automated scoring results that were obtained using the constructed responses from the Writing and Speaking sections of the pilot forms of the "TOEFL Junior"® Comprehensive test administered in late 2011. For all of the items except one (the edit item in the Writing section), existing automated scoring…
Descriptors: Computer Assisted Testing, Automation, Language Tests, Second Language Learning
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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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DeCarlo, Lawrence T. – ETS Research Report Series, 2008
Rater behavior in essay grading can be viewed as a signal-detection task, in that raters attempt to discriminate between latent classes of essays, with the latent classes being defined by a scoring rubric. The present report examines basic aspects of an approach to constructed-response (CR) scoring via a latent-class signal-detection model. The…
Descriptors: Scoring, Responses, Test Format, Bias
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Rock, Donald A. – ETS Research Report Series, 2012
This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…
Descriptors: Models, Educational Change, Longitudinal Studies, Educational Development
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