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Congning Ni; Bhashithe Abeysinghe; Juanita Hicks – International Electronic Journal of Elementary Education, 2025
The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, offers a window into the state of U.S. K-12 education system. Since 2017, NAEP has transitioned to digital assessments, opening new research opportunities that were previously impossible. Process data tracks students' interactions with the…
Descriptors: Reaction Time, Multiple Choice Tests, Behavior Change, National Competency Tests
Cox, Troy L.; Brown, Alan V.; Thompson, Gregory L. – Language Testing, 2023
The rating of proficiency tests that use the Inter-agency Roundtable (ILR) and American Council on the Teaching of Foreign Languages (ACTFL) guidelines claims that each major level is based on hierarchal linguistic functions that require mastery of multidimensional traits in such a way that each level subsumes the levels beneath it. These…
Descriptors: Oral Language, Language Fluency, Scoring, Cues
Chen, Lei; Zechner, Klaus; Yoon, Su-Youn; Evanini, Keelan; Wang, Xinhao; Loukina, Anatassia; Tap, Jidong; Davis, Lawrence; Lee, Chong Min; Ma, Min; Mundowsky, Robert; Lu, Chi; Leong, Chee Wee; Gyawali, Binod – ETS Research Report Series, 2018
This research report provides an overview of the R&D efforts at Educational Testing Service related to its capability for automated scoring of nonnative spontaneous speech with the "SpeechRater"? automated scoring service since its initial version was deployed in 2006. While most aspects of this R&D work have been published in…
Descriptors: Computer Assisted Testing, Scoring, Test Scoring Machines, Speech Tests
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
Long, Avizia Y.; Shin, Sun-Young; Geeslin, Kimberly; Willis, Erik W. – Language Learning & Technology, 2018
In response to the need for examples of test validation from which everyday language programs can benefit, this paper reports on a study that used Bachman's (2005) assessment use argument (AUA) framework to examine evidence to support claims made about the intended interpretations and uses of scores based on a new web-based Spanish language…
Descriptors: Second Language Instruction, Second Language Learning, Spanish, Computer Assisted Testing
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
Liu, Ming; Li, Yi; Xu, Weiwei; Liu, Li – IEEE Transactions on Learning Technologies, 2017
Writing an essay is a very important skill for students to master, but a difficult task for them to overcome. It is particularly true for English as Second Language (ESL) students in China. It would be very useful if students could receive timely and effective feedback about their writing. Automatic essay feedback generation is a challenging task,…
Descriptors: Foreign Countries, College Students, Second Language Learning, English (Second Language)
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
Gallagher, Nancy – Delta Publishing Company, 2012
Although the TOEFL iBT does not have a discrete grammar section, knowledge of English sentence structure is important throughout the test. Essential Grammar for the iBT reviews the skills that are fundamental to success on tests. Content includes noun and verb forms, clauses, agreement, parallel structure, punctuation, and much more. The book may…
Descriptors: English (Second Language), Language Tests, Computer Assisted Testing, Grammar
Blanchard, Daniel; Tetreault, Joel; Higgins, Derrick; Cahill, Aoife; Chodorow, Martin – ETS Research Report Series, 2013
This report presents work on the development of a new corpus of non-native English writing. It will be useful for the task of native language identification, as well as grammatical error detection and correction, and automatic essay scoring. In this report, the corpus is described in detail.
Descriptors: Language Tests, Second Language Learning, English (Second Language), Writing Tests
Xi, Xiaoming; Higgins, Derrick; Zechner, Klaus; Williamson, David – Language Testing, 2012
This paper compares two alternative scoring methods--multiple regression and classification trees--for an automated speech scoring system used in a practice environment. The two methods were evaluated on two criteria: construct representation and empirical performance in predicting human scores. The empirical performance of the two scoring models…
Descriptors: Scoring, Classification, Weighted Scores, Comparative Analysis
Thompson, Carrie A. – ProQuest LLC, 2013
The Missionary Training Center (MTC), affiliated with the Church of Jesus Christ of Latter-day Saints, needs a reliable and cost effective way to measure the oral language proficiency of missionaries learning Spanish. The MTC needed to measure incoming missionaries' Spanish language proficiency for training and classroom assignment as well as to…
Descriptors: Religious Cultural Groups, Second Language Learning, Second Language Instruction, Interviews
Chapelle, Carol A.; Chung, Yoo-Ree; Hegelheimer, Volker; Pendar, Nick; Xu, Jing – Language Testing, 2010
This study piloted test items that will be used in a computer-delivered and scored test of productive grammatical ability in English as a second language (ESL). Findings from research on learners' development of morphosyntactic, syntactic, and functional knowledge were synthesized to create a framework of grammatical features. We outline the…
Descriptors: Test Items, Grammar, Developmental Stages, Computer Assisted Testing
Yoon, Su-Youn – ProQuest LLC, 2009
This dissertation provides an automated scoring method of speech fluency for second language learners of English (L2 learners) based that uses speech recognition technology. Non-standard pronunciation, frequent disfluencies, faulty grammar, and inappropriate lexical choices are crucial characteristics of L2 learners' speech. Due to the ease of…
Descriptors: Phonemes, Second Language Learning, Scoring, Correlation
Peer reviewedSmalley, Alan – Language Learning Journal, 1996
Analyzes the computer program, "Question Mark," produced in England and designed to be a testing tool for large second-language classes. Using this tool, it is possible to create and edit up to 500 questions using any one of 8 different question types. The program also can provide a running score for students using it. Notes that student…
Descriptors: Computer Assisted Testing, Computer Software, Dutch, Editing
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