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Brady D. Lund; Tae Hee Lee; Nishith Reddy Mannuru; Nikhila Arutla – Journal of Academic Ethics, 2025
The emergence of generative artificial intelligence tools, such as ChatGPT, presents new challenges impacting student perceptions of academic integrity. While extensive research exists on academic misconduct and student perceptions of various infractions, there is limited understanding of how AI tools impact these views and whether their use…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Student Attitudes
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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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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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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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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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Marrone, Rebecca; Cropley, David H.; Wang, Z. – Creativity Research Journal, 2023
Creativity is now accepted as a core 21st-century competency and is increasingly an explicit part of school curricula around the world. Therefore, the ability to assess creativity for both formative and summative purposes is vital. However, the "fitness-for-purpose" of creativity tests has recently come under scrutiny. Current creativity…
Descriptors: Automation, Evaluation Methods, Creative Thinking, Mathematics Education
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Tim Humphry; Amy L. Fuller – Journal of Chemical Education, 2023
ChatGPT is a brand new, free AI chatbot that has the potential to produce a seismic shift in chemistry education, especially in written lab reports. An example is explored in which ChatGPT is used to write the discussion portion of a lab report. Ways to detect the use of ChatGPT are also discussed.
Descriptors: Artificial Intelligence, Natural Language Processing, Undergraduate Students, Chemistry
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Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
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Anson, Chris M. – Composition Studies, 2022
Student plagiarism has challenged educators for decades, with heightened paranoia following the advent of the Internet in the 1980's and ready access to easily copied text. But plagiarism will look like child's play next to new developments in AI-based natural-language processing (NLP) systems that increasingly appear to "write" as…
Descriptors: Plagiarism, Artificial Intelligence, Natural Language Processing, Writing Assignments
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Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
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