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Showing 1 to 15 of 18 results Save | Export
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Joshua Kloppers – International Journal of Computer-Assisted Language Learning and Teaching, 2023
Automated writing evaluation (AWE) software is an increasingly popular tool for English second language learners. However, research on the accuracy of such software has been both scarce and largely limited in its scope. As such, this article broadens the field of research on AWE accuracy by using a mixed design to holistically evaluate the…
Descriptors: Grammar, Automation, Writing Evaluation, Computer Assisted Instruction
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
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Neha Biju; Nasser Said Gomaa Abdelrasheed; Khilola Bakiyeva; K. D. V. Prasad; Biruk Jember – Language Testing in Asia, 2024
In recent years, language practitioners have paid increasing attention to artificial intelligence (AI)'s role in language programs. This study investigated the impact of AI-assisted language assessment on L2 learners' foreign language anxiety (FLA), attitudes, motivation, and writing skills. The study adopted a sequential exploratory mixed-methods…
Descriptors: Artificial Intelligence, Computer Software, Computer Assisted Testing, Second Language Instruction
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Potter, Andrew; Wilson, Joshua – Educational Technology Research and Development, 2021
Automated Writing Evaluation (AWE) provides automatic writing feedback and scoring to support student writing and revising. The purpose of the present study was to analyze a statewide implementation of an AWE software (n = 114,582) in grades 4-11. The goals of the study were to evaluate: (1) to what extent AWE features were used; (2) if equity and…
Descriptors: Computer Assisted Testing, Writing Evaluation, Feedback (Response), Scoring
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Bateson, Gordon – International Journal of Computer-Assisted Language Learning and Teaching, 2021
As a result of the Japanese Ministry of Education's recent edict that students' written and spoken English should be assessed in university entrance exams, there is an urgent need for tools to help teachers and students prepare for these exams. Although some commercial tools already exist, they are generally expensive and inflexible. To address…
Descriptors: Test Construction, Computer Assisted Testing, Internet, Writing Tests
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Khuder, Baraa; Harwood, Nigel – Written Communication, 2019
This mixed-methods study investigates writers' task representation and the factors affecting it in test-like and non-test-like conditions. Five advanced-level L2 writers wrote two argumentative essays each, one in test-like conditions and the other in non-test-like conditions where the participants were allowed to use all the time and online…
Descriptors: Second Language Learning, Task Analysis, Advanced Students, Essays
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Ebadi, Saman; Rahimi, Masoud – Computer Assisted Language Learning, 2019
Drawing on Vygotskian sociocultural theory of mind and social constructivism, and adopting a sequential exploratory mixed-methods approach, this study explored the impact of online dynamic assessment (DA) on EFL learners' academic writing skills through one-on-one individual and online synchronous DA sessions over Google Docs. It also investigated…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Sociocultural Patterns
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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
White, Sheida; Kim, Young Yee; Chen, Jing; Liu, Fei – National Center for Education Statistics, 2015
This study examined whether or not fourth-graders could fully demonstrate their writing skills on the computer and factors associated with their performance on the National Assessment of Educational Progress (NAEP) computer-based writing assessment. The results suggest that high-performing fourth-graders (those who scored in the upper 20 percent…
Descriptors: National Competency Tests, Computer Assisted Testing, Writing Tests, Grade 4
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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
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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent – ETS Research Report Series, 2012
Scoring models for the "e-rater"® system were built and evaluated for the "TOEFL"® exam's independent and integrated writing prompts. Prompt-specific and generic scoring models were built, and evaluation statistics, such as weighted kappas, Pearson correlations, standardized differences in mean scores, and correlations with…
Descriptors: Scoring, Prompting, Evaluators, Computer Software
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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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McCurry, Doug – Assessing Writing, 2010
This article considers the claim that machine scoring of writing test responses agrees with human readers as much as humans agree with other humans. These claims about the reliability of machine scoring of writing are usually based on specific and constrained writing tasks, and there is reason for asking whether machine scoring of writing requires…
Descriptors: Writing Tests, Scoring, Interrater Reliability, Computer Assisted Testing
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Lee, Yong-Won; Gentile, Claudia; Kantor, Robert – Applied Linguistics, 2010
The main purpose of the study was to investigate the distinctness and reliability of analytic (or multi-trait) rating dimensions and their relationships to holistic scores and "e-rater"[R] essay feature variables in the context of the TOEFL[R] computer-based test (TOEFL CBT) writing assessment. Data analyzed in the study were holistic…
Descriptors: Writing Evaluation, Writing Tests, Scoring, Essays
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Coniam, David – ReCALL, 2009
This paper describes a study of the computer essay-scoring program BETSY. While the use of computers in rating written scripts has been criticised in some quarters for lacking transparency or lack of fit with how human raters rate written scripts, a number of essay rating programs are available commercially, many of which claim to offer comparable…
Descriptors: Writing Tests, Scoring, Foreign Countries, Interrater Reliability
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