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Steven Holtzman; Jonathan Steinberg; Jonathan Weeks; Christopher Robertson; Jessica Findley; David Klieger – ETS Research Report Series, 2024
At a time when institutions of higher education are exploring alternatives to traditional admissions testing, institutions are also seeking to better support students and prepare them for academic success. Under such an engaged model, one may seek to measure not just the accumulated knowledge and skills that students would bring to a new academic…
Descriptors: Law Schools, College Applicants, Legal Education (Professions), College Entrance Examinations
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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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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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Haberman, Shelby J. – ETS Research Report Series, 2008
In educational testing, subscores may be provided based on a portion of the items from a larger test. One consideration in evaluation of such subscores is their ability to predict a criterion score. Two limitations on prediction exist. The first, which is well known, is that the coefficient of determination for linear prediction of the criterion…
Descriptors: Scores, Validity, Educational Testing, Correlation
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Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David M. – ETS Research Report Series, 2008
This report presents the results of a research and development effort for SpeechRater? Version 1.0 (v1.0), an automated scoring system for the spontaneous speech of English language learners used operationally in the Test of English as a Foreign Language™ (TOEFL®) Practice Online assessment (TPO). The report includes a summary of the validity…
Descriptors: Speech, Scoring, Scoring Rubrics, Scoring Formulas
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Stricker, Lawrence J.; Rock, Donald A. – ETS Research Report Series, 2008
This study assessed the invariance in the factor structure of the "Test of English as a Foreign Language"™ Internet-based test (TOEFL® iBT) across subgroups of test takers who differed in native language and exposure to the English language. The subgroups were defined by (a) Indo-European and Non-Indo-European language family, (b)…
Descriptors: Factor Structure, English (Second Language), Language Tests, Computer Assisted Testing
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Attali, Yigal – ETS Research Report Series, 2007
Because there is no commonly accepted view of what makes for good writing, automated essay scoring (AES) ideally should be able to accommodate different theoretical positions, certainly at the level of state standards but also perhaps among teachers at the classroom level. This paper presents a practical approach and an interactive computer…
Descriptors: Computer Assisted Testing, Automation, Essay Tests, Scoring