NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Teachers1
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 33 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Doewes, Afrizal; Kurdhi, Nughthoh Arfawi; Saxena, Akrati – International Educational Data Mining Society, 2023
Automated Essay Scoring (AES) tools aim to improve the efficiency and consistency of essay scoring by using machine learning algorithms. In the existing research work on this topic, most researchers agree that human-automated score agreement remains the benchmark for assessing the accuracy of machine-generated scores. To measure the performance of…
Descriptors: Essays, Writing Evaluation, Evaluators, Accuracy
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
Peer reviewed Peer reviewed
Direct linkDirect link
Miguel Blázquez-Carretero – ReCALL, 2023
In 2016, Lawley proposed an easy-to-build spellchecker specifically designed to help second language (L2) learners in their writing process by facilitating self-correction. The aim was to overcome the disadvantages to L2 learners posed by generic spellcheckers (GSC), such as that embedded in Microsoft Word. Drawbacks include autocorrection,…
Descriptors: Second Language Learning, Spanish, Spelling, Error Correction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lynette Hazelton; Jessica Nastal; Norbert Elliot; Jill Burstein; Daniel F. McCaffrey – Journal of Response to Writing, 2021
In writing studies research, automated writing evaluation technology is typically examined for a specific, often narrow purpose: to evaluate a particular writing improvement measure, to mine data for changes in writing performance, or to demonstrate the effectiveness of a single technology and accompanying validity arguments. This article adopts a…
Descriptors: Formative Evaluation, Writing Evaluation, Automation, Natural Language Processing
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Christina Andrade; Amber Roshay – CATESOL Journal, 2023
Giving effective writing feedback can be a challenge for any English instructor. Teaching students how to provide peer feedback can be problematic as well. Both these challenges may seem even more apparent when teaching online during a pandemic. Using Google Docs for collaborative writing feedback is one effective method for addressing both these…
Descriptors: Computer Software, Collaborative Writing, English (Second Language), Second Language Learning
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Woodworth, Johanathan; Barkaoui, Khaled – TESL Canada Journal, 2020
While feedback is widely considered essential for second language (L2) writing development (Bitchener & Ferris, 2012), teachers may not always be able to provide their learners with immediate and frequent corrective feedback. Automated writing evaluation (AWE) systems can help respond to this challenge by providing L2 learners with written…
Descriptors: Writing Evaluation, Feedback (Response), Error Correction, Second Language Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Unnam, Abhishek; Takhar, Rohit; Aggarwal, Varun – International Educational Data Mining Society, 2019
Email has become the most preferred form of business communication. Writing "good" email has become an essential skill required in the industry. "Good" email writing not only facilitates clear communication, but also makes a positive impression on the recipient, whether it be one's colleague or a customer. The aim of this paper…
Descriptors: Grading, Electronic Mail, Feedback (Response), Written Language
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
Godwin-Jones, Robert – Language Learning & Technology, 2018
This article provides an update to the author's overview of developments in second language (L2) online writing that he wrote in 2008. There has been renewed interest in L2 writing through the wide use of social media, along with the rising popularity of computer-mediated communication (CMC) and telecollaboration (class-based online exchanges).…
Descriptors: Second Language Learning, Computer Mediated Communication, Second Language Instruction, Writing Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Krishnan, Rathi – NADE Digest, 2016
This paper is based on a presentation made at NADE 2016, in Anaheim, California, entitled "Turnitin--An Extraordinary Teaching and Feedback Tool in the Writing Classroom" which discussed the value and benefits of using Turnitin (TII), a subscription-based software/website available to universities that serves as an audio-visual feedback…
Descriptors: Plagiarism, Writing Evaluation, Feedback (Response), Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Eckhouse, Barry; Carroll, Rebecca – Business Communication Quarterly, 2013
Although relatively little attention has been given to the voice assessment of student work, at least when compared with more traditional forms of text-based review, the attention it has received strongly points to a promising form of review that has been hampered by the limits of an emerging technology. A fresh review of voice assessment in light…
Descriptors: Undergraduate Students, Graduate Students, Business Administration Education, Student Surveys
Previous Page | Next Page »
Pages: 1  |  2  |  3