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Nathan Lindberg – Writing Center Journal, 2025
In this essay, I suggest that we should embrace generative artificial intelligence (GenAI) writing tools, particularly chatbots (e.g., ChatGPT, Copilot, Claude), because they can enable linguistic equity by leveling the academic playing field for English as an additional language students. As writing experts, we can find ways to use this…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Hyeongdon Moon; Richard Lee Davis; Seyed Parsa Neshaei; Pierre Dillenbourg – International Educational Data Mining Society, 2025
Knowledge tracing models have enabled a range of intelligent tutoring systems to provide feedback to students. However, existing methods for knowledge tracing in learning sciences are predominantly reliant on statistical data and instructor-defined knowledge components, making it challenging to integrate AI-generated educational content with…
Descriptors: Artificial Intelligence, Natural Language Processing, Automation, Information Management
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Victor-Alexandru Padurean; Tung Phung; Nachiket Kotalwar; Michael Liut; Juho Leinonen; Paul Denny; Adish Singla – International Educational Data Mining Society, 2025
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses…
Descriptors: Automation, Student Writing Models, Feedback (Response), Programming
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Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – International Journal of STEM Education, 2025
Background: Technology-enhanced classrooms now integrate a range of educational apps designed to improve student outcomes. The effectiveness of these applications is influenced by multiple factors related to the courses and the applications themselves. A critical factor is student engagement, which involves interacting with the course content…
Descriptors: Natural Language Processing, Handheld Devices, Computer Oriented Programs, Learner Engagement
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James G. Caling; Joanna Kyla T. Antonio; Ma. Fe. L. Dimatatac; Mitz D. Sabellano; Victoria Dhane R. Vicencio; Justin M. Prias; John Carlo M. Ramos – Journal of Interdisciplinary Studies in Education, 2025
This study examines how 10 pre-service teachers from a teacher education institution in Manila integrate ChatGPT into their academic tasks and navigate the resulting moral dissonance. Through semistructured interviews, the findings reveal that while ChatGPT is employed for paraphrasing, organizing ideas, information retrieval, and simplifying…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Preservice Teachers
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Mickie De Wet; Margarita Oja Da Silva; René Bohnsack – Innovations in Education and Teaching International, 2025
This study explores the use of large language models (LLMs) to generate feedback on essay-type assignments in Higher Education. Drawing on a seminal feedback framework, it examines the pedagogical and psychological effectiveness of LLM-generated feedback across three cohorts of MBA, MSc, and undergraduate students. Methods included linguistic…
Descriptors: Higher Education, College Students, Artificial Intelligence, Writing Evaluation
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Lawrence Ibeh; Noah Cheruiyot Mutai; Olufunke Mercy Popoola; Nguyen Manh Cuong; Sandra Ejiofor – Research in Learning Technology, 2025
For this study, 350 university students in Germany were surveyed to understand how they perceive ChatGPT's educational advantages and challenges. Using a combination of quantitative and qualitative methods, it found out that students tend to see ChatGPT as helpful for academic performance (53.14%), writing (47.14%), and exam preparation (50.00%).…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Shimmei, Machi; Matsuda, Noboru – International Educational Data Mining Society, 2023
We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…
Descriptors: Artificial Intelligence, Training, Natural Language Processing, Educational Research
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Huawei, Shi; Aryadoust, Vahid – Education and Information Technologies, 2023
Automated writing evaluation (AWE) systems are developed based on interdisciplinary research and technological advances such as natural language processing, computer sciences, and latent semantic analysis. Despite a steady increase in research publications in this area, the results of AWE investigations are often mixed, and their validity may be…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Automation
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Suire, Cyrille; Sidère, Nicolas; Doucet, Antoine – Education for Information, 2023
In this article, we introduce an Open Education Resource (OER) on digital historical research with historical newspapers, intended to give students the means to understand the induced risks in working with large collections of digitised documents, as well as the keys to benefit from the advances of natural language processing over large…
Descriptors: Open Educational Resources, Newspapers, Electronic Publishing, Natural Language Processing
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Wang, Wei; Zhao, Yongyong; Wu, Yenchun Jim; Goh, Mark – International Journal of Science Education, Part B: Communication and Public Engagement, 2023
This study analyzed the influence of rhetoric in the endorsement text on the willingness of the crowd to participate in citizen science projects. Four categories of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using 1243 endorsement texts from 543 citizen science projects as the corpus, the effects…
Descriptors: Citizen Participation, Science Education, Rhetoric, Scientific Research
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Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
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Bozkurt, Aras – Asian Journal of Distance Education, 2023
Generative AI, specifically ChatGPT, represents a significant technological advancement in natural language processing (NLP) large language models (LLM) with far-reaching implications in many dimensions of our lives, including education. This paper discusses the prospects of generative AI in utilizing language and its potential role as a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Computer Mediated Communication
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Perlman-Arrow, Sara; Loo, Noel; Bobrovitz, Niklas; Yan, Tingting; Arora, Rahul K. – Research Synthesis Methods, 2023
The laborious and time-consuming nature of systematic review production hinders the dissemination of up-to-date evidence synthesis. Well-performing natural language processing (NLP) tools for systematic reviews have been developed, showing promise to improve efficiency. However, the feasibility and value of these technologies have not been…
Descriptors: Natural Language Processing, Screening Tests, COVID-19, Pandemics
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Lancaster, Thomas – International Journal for Educational Integrity, 2023
Text generation tools, often presented as a form of generative artificial intelligence, have the potential to pose a threat to the integrity of the educational system. They can be misused to afford students marks and qualifications that they do not deserve. The emergence of recent tools, such as ChatGPT, appear to have left the educational…
Descriptors: Artificial Intelligence, Natural Language Processing, Integrity, Educational Technology
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