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Showing 1 to 15 of 16 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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Rotou, Ourania; Rupp, André A. – ETS Research Report Series, 2020
This research report provides a description of the processes of evaluating the "deployability" of automated scoring (AS) systems from the perspective of large-scale educational assessments in operational settings. It discusses a comprehensive psychometric evaluation that entails analyses that take into consideration the specific purpose…
Descriptors: Computer Assisted Testing, Scoring, Educational Assessment, Psychometrics
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Hao, Jiangang; Liu, Lei; Kyllonen, Patrick; Flor, Michael; von Davier, Alina A. – ETS Research Report Series, 2019
Collaborative problem solving (CPS) is an important 21st-century skill that is crucial for both career and academic success. However, developing a large-scale and standardized assessment of CPS that can be administered on a regular basis is very challenging. In this report, we introduce a set of psychometric considerations and a general scoring…
Descriptors: Scoring, Psychometrics, Cooperation, Problem Solving
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Chukharev-Hudilainen, Evgeny; Ockey, Gary J. – ETS Research Report Series, 2021
This paper describes the development and evaluation of Interaction Competence Elicitor (ICE), a spoken dialog system (SDS) for the delivery of a paired oral discussion task in the context of language assessment. The purpose of ICE is to sustain a topic-specific conversation with a test taker in order to elicit discourse that can be later judged to…
Descriptors: Intercultural Communication, Oral Language, Communicative Competence (Languages), Error Analysis (Language)
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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
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Bruno, James V.; Cahill, Aoife; Gyawali, Binod – ETS Research Report Series, 2016
We present an annotation scheme for classifying differences in the outputs of syntactic constituency parsers when a gold standard is unavailable or undesired, as in the case of texts written by nonnative speakers of English. We discuss its automated implementation and the results of a case study that uses the scheme to choose a parser best suited…
Descriptors: Documentation, Classification, Differences, Syntax
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Yoon, Su-Youn; Lee, Chong Min; Houghton, Patrick; Lopez, Melissa; Sakano, Jennifer; Loukina, Anastasia; Krovetz, Bob; Lu, Chi; Madani, Nitin – ETS Research Report Series, 2017
In this study, we developed assistive tools and resources to support TOEIC® Listening test item generation. There has recently been an increased need for a large pool of items for these tests. This need has, in turn, inspired efforts to increase the efficiency of item generation while maintaining the quality of the created items. We aimed to…
Descriptors: Natural Language Processing, Language Tests, Item Banks, Pilot Projects
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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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Heilman, Michael; Breyer, F. Jay; Williams, Frank; Klieger, David; Flor, Michael – ETS Research Report Series, 2015
Graduate school recommendations are an important part of admissions in higher education, and natural language processing may be able to provide objective and consistent analyses of recommendation texts to complement readings by faculty and admissions staff. However, these sorts of high-stakes, personal recommendations are different from the…
Descriptors: Natural Language Processing, College Admission, Admission Criteria, Referral
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Bejar, Isaac I.; VanWinkle, Waverely; Madnani, Nitin; Lewis, William; Steier, Michael – ETS Research Report Series, 2013
The paper applies a natural language computational tool to study a potential construct-irrelevant response strategy, namely the use of "shell language." Although the study is motivated by the impending increase in the volume of scoring of students responses from assessments to be developed in response to the Race to the Top initiative,…
Descriptors: Responses, Language Usage, Natural Language Processing, Computational Linguistics
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Deane, Paul; Lawless, René R.; Li, Chen; Sabatini, John; Bejar, Isaac I.; O'Reilly, Tenaha – ETS Research Report Series, 2014
We expect that word knowledge accumulates gradually. This article draws on earlier approaches to assessing depth, but focuses on one dimension: richness of semantic knowledge. We present results from a study in which three distinct item types were developed at three levels of depth: knowledge of common usage patterns, knowledge of broad topical…
Descriptors: Vocabulary, Test Items, Language Tests, Semantics
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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
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Sukkarieh, Jane Z.; von Davier, Matthias; Yamamoto, Kentaro – ETS Research Report Series, 2012
This document describes a solution to a problem in the automatic content scoring of the multilingual character-by-character highlighting item type. This solution is language independent and represents a significant enhancement. This solution not only facilitates automatic scoring but plays an important role in clustering students' responses;…
Descriptors: Scoring, Multilingualism, Test Items, Role
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Burstein, Jill; Shore, Jane; Sabatini, John; Moulder, Brad; Holtzman, Steven; Pedersen, Ted – ETS Research Report Series, 2012
In the United States, English learners (EL) often do not have the academic language proficiency, literacy skills, cultural background, and content knowledge necessary to succeed in kindergarten through 12th grade classrooms. This leads to large achievement gaps. Also, classroom texts are often riddled with linguistically unfamiliar elements,…
Descriptors: English Language Learners, Scaffolding (Teaching Technique), Educational Technology, Computer Oriented Programs
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Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Hemat, Ramin; Zuckerman, Daniel – ETS Research Report Series, 2006
This paper describes the development, implementation, and evaluation of an automated system for predicting the acceptability status of candidate reading-comprehension stimuli extracted from a database of journal and magazine articles. The system uses a combination of classification and regression techniques to predict the probability that a given…
Descriptors: Automation, Prediction, Reading Comprehension, Classification
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