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Haberman, Shelby J. – ETS Research Report Series, 2020
Best linear prediction (BLP) and penalized best linear prediction (PBLP) are techniques for combining sources of information to produce task scores, section scores, and composite test scores. The report examines issues to consider in operational implementation of BLP and PBLP in testing programs administered by ETS [Educational Testing Service].
Descriptors: Prediction, Scores, Tests, Testing Programs
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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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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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Attali, Yigal – ETS Research Report Series, 2007
This study examined the construct validity of the "e-rater"® automated essay scoring engine as an alternative to human scoring in the context of TOEFL® essay writing. Analyses were based on a sample of students who repeated the TOEFL within a short time period. Two "e-rater" scores were investigated in this study, the first…
Descriptors: Construct Validity, Computer Assisted Testing, Scoring, English (Second Language)