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Godwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
UK Department for Education, 2024
This report sets out the findings of the technical development work completed as part of the Use Cases for Generative AI in Education project, commissioned by the Department for Education (DfE) in September 2023. It has been published alongside the User Research Report, which sets out the findings from the ongoing user engagement activity…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Software, Computational Linguistics
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Kaktinš, Louise – Ethics and Education, 2019
Australian universities are grappling with the challenge of plagiarism among students, particularly international students, with a reliance on software such as Turnitin. Measuring plagiarism in this way has limitations, with consequences for the internalisation of academic integrity by international students. An appraisal of such software…
Descriptors: Computer Software, Computational Linguistics, Writing Evaluation, Cheating
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Lu, Xiaofei – Language Testing, 2017
Research investigating corpora of English learners' language raises new questions about how syntactic complexity is defined theoretically and operationally for second language (L2) writing assessment. I show that syntactic complexity is important in construct definitions and L2 writing rating scales as well as in L2 writing research. I describe…
Descriptors: Syntax, Computational Linguistics, Second Language Learning, Writing Research
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Hunt, Jared; Tompkins, Patrick – Inquiry, 2014
The plagiarism detection programs SafeAssign and Turnitin are commonly used at the collegiate level to detect improper use of outside sources. In order to determine whether either program is superior, this study evaluated the programs using four standards: (1) the ability to detect legitimate plagiarism, (2) the ability to avoid false positives,…
Descriptors: Comparative Analysis, Computer Software, Plagiarism, Computational Linguistics
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Crossley, Scott A.; McNamara, Danielle S. – Journal of Second Language Writing, 2009
The purpose of this paper is to provide a detailed analysis of how lexical differences related to cohesion and connectionist models can distinguish first language (L1) writers of English from second language (L2) writers of English. Key to this analysis is the use of the computational tool Coh-Metrix, which measures cohesion and text difficulty at…
Descriptors: Second Language Learning, Discriminant Analysis, English (Second Language), Educational Technology
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Cotos, Elena – CALICO Journal, 2011
This paper presents an empirical evaluation of automated writing evaluation (AWE) feedback used for L2 academic writing teaching and learning. It introduces the Intelligent Academic Discourse Evaluator (IADE), a new web-based AWE program that analyzes the introduction section to research articles and generates immediate, individualized, and…
Descriptors: Evidence, Feedback (Response), Academic Discourse, Writing (Composition)