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Backman, Ylva; Reznitskaya, Alina; Gardelli, Viktor; Wilkinson, Ian A. G. – Written Communication, 2023
Current approaches used in educational research and practice to evaluate the quality of written arguments often rely on structural analysis. In such assessments, credit is awarded for the presence of structural elements of an argument, such as claims, evidence, and rebuttals. In this article, we discuss limitations of such approaches, including…
Descriptors: Writing Evaluation, Models, Persuasive Discourse, Evaluation Methods
Han Zhang; Jamie Costley; Matthew Courtney; Galina Shulgina; Mik Fanguy – Education and Information Technologies, 2025
Depending on the nature of comments made during peer review of academic writing, students may be able to evaluate and revise their performance. Therefore, it is essential to explore how the content of comments affects student writing. Since peer review is a process of interaction, it is critical to understand how comments affect student academic…
Descriptors: Graduate Students, Content Area Writing, Academic Language, Feedback (Response)
Barbara Bordalejo; Davide Pafumi; Frank Onuh; A. K. M. Iftekhar Khalid; Morgan Slayde Pearce; Daniel Paul O'Donnell – International Journal of Educational Technology in Higher Education, 2025
This paper explores the growing complexity of detecting and differentiating generative AI from other AI interventions. Initially prompted by noticing how tools like Grammarly were being flagged by AI detection software, it examines how these popular tools such as Grammarly, EditPad, Writefull, and AI models such as ChatGPT and Microsoft Bing…
Descriptors: Artificial Intelligence, Writing (Composition), Quality Control, Writing Evaluation
Julian F. Lohmann; Fynn Junge; Jens Möller; Johanna Fleckenstein; Ruth Trüb; Stefan Keller; Thorben Jansen; Andrea Horbach – International Journal of Artificial Intelligence in Education, 2025
Recent investigations in automated essay scoring research imply that hybrid models, which combine feature engineering and the powerful tools of deep neural networks (DNNs), reach state-of-the-art performance. However, most of these findings are from holistic scoring tasks. In the present study, we use a total of four prompts from two different…
Descriptors: Artificial Intelligence, Natural Language Processing, Essays, Writing Evaluation
Peer reviewedYang Zhong; Mohamed Elaraby; Diane Litman; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2024
This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…
Descriptors: Documentation, Writing (Composition), Reflection, Metadata
Jessica Nastal – Teaching English in the Two-Year College, 2024
In this article, I provide a chronological narrative to my ungrading choices in composition classes as a neurodiverse single mother from a working-class background. I discuss my positionality as a White person committed to justice and my experiences as an "assessment killjoy" (West-Puckett et al.) during the ethical turn in writing…
Descriptors: Writing Instruction, Grading, Student Evaluation, Ethics
Bouwer, Renske; Koster, Monica; van den Bergh, Huub – Assessment in Education: Principles, Policy & Practice, 2023
Assessing students' writing performance is essential to adequately monitor and promote individual writing development, but it is also a challenge. The present research investigates a benchmark rating procedure for assessing texts written by upper-elementary students. In two studies we examined whether a benchmark rating procedure (1) leads to…
Descriptors: Benchmarking, Writing Evaluation, Evaluation Methods, Elementary School Students
Ruth Li – Written Communication, 2025
Students are expected to interpret the complexities and nuances of literary texts yet might struggle with interpreting texts in ways that are valued in literary studies. Examining students' language choices can support instructors and students with developing concrete, explicit understandings of the ways language creates meanings in discourse.…
Descriptors: Linguistics, Writing (Composition), Literature Appreciation, Metalinguistics
Ivar Bråten; Ymkje E. Haverkamp; Natalia Latini; Helge I. Strømsø – Journal of Research in Reading, 2025
Background: A common approach to assessing students' integrated understanding of multiple documents is to analyse their post-reading written reports. This study investigated to what extent writing self-efficacy directly and indirectly (via integrative processing) contributed to multiple-document comprehension as assessed with an integrative…
Descriptors: Writing Instruction, Writing (Composition), Writing Evaluation, Self Efficacy
Shira Besser-Biron; Deborah Bergman Deitcher; Adi Elimelech; Dorit Aram – Reading and Writing: An Interdisciplinary Journal, 2025
Preschool teachers' literacy-related beliefs and literacy knowledge relate to their educational practices and preschoolers' literacy skills. In this light, we explored how preschool teachers' beliefs regarding early literacy and its promotion predict their knowledge, reflected in how they evaluate three young children's writing products and their…
Descriptors: Preschool Teachers, Teacher Attitudes, Beliefs, Literacy
Xiaomei Wang – Education and Information Technologies, 2025
Automated writing evaluation (AWE) provides an instant and cost-effective alternative to human feedback in assessing student writing, and therefore is widely used as a pedagogical supportive tool in writing instruction. However, studies on how students perceive the usage of AWE as a surrogate writing tutor in out-of-class autonomous learning are…
Descriptors: Student Attitudes, Automation, Writing Evaluation, Undergraduate Students
Qinghao Guan; Yangxi Han – Innovations in Education and Teaching International, 2025
As generative AI (GenAI) continues to permeate academia, distinguishing between student-authored essays and those by Large Language Models (LLMs) becomes crucial for maintaining academic integrity. This study conducted a survey on the ethical awareness of using generative AI tools among a group of STEM students (n=156). Also, we empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Intelligent Tutoring Systems
Kirkwood Adams; Maria G. Baker – Thresholds in Education, 2025
In response to (1) studies finding that essay feedback generated by ChatGPT might be useful for student writers and (2) studies observing ChatGPT's tendency to adhere to narrow genre definitions when producing writing, our study seeks to examine whether ChatGPT can provide useful feedback in a first-year writing learning environment that targets a…
Descriptors: Freshman Composition, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Hosnia M. M. Ahmed; Shaymaa E. Sorour – Education and Information Technologies, 2024
Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study…
Descriptors: Higher Education, Artificial Intelligence, Writing Evaluation, Natural Language Processing
Roger Lee – e-Journal of Business Education and Scholarship of Teaching, 2024
Reflective Learning Journals are used to engage students in the learning process. To motivate students to complete the Reflective Learning Journal it is common practice to allocate marks and it is in this area that problems arise. To address the problems rubrics have been used however, most rubrics are based on assigning marks to very…
Descriptors: Scoring Rubrics, Reflection, Journal Writing, Student Journals

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