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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
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Jose Berengueres – Discover Education, 2025
GPT-based models have enabled the creation of natural language chatbots that support both Inquiry-Based and Structured Learning approaches. This study offers a direct comparison of these two paradigms within a UNIX Shell scripting course by means of two chatbots: a Lesson Plan-Driven chatbot that ensures all students cover the same topics…
Descriptors: Lesson Plans, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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John Mark R. Asio; Dante P. Sardina – Journal of Pedagogical Research, 2025
Artificial Intelligence (AI) is taking the educational system by storm due to its various implications and endless possibilities. Nevertheless, the teachers, the schools, and most importantly, the students have different perspectives on using AI in their learning experience, especially when gender is involved. In this study, the proponents delve…
Descriptors: Gender Differences, Artificial Intelligence, Technology Uses in Education, Anxiety
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Silvia Ortiz-Bonnin; Joanna Blahopoulou – Social Psychology of Education: An International Journal, 2025
Academic dishonesty remains a persistent concern for educational institutions, threatening the reputation of universities. The emergence of Artificial Intelligence (AI) tools exacerbates this challenge as they can be used for chatting but also for cheating. Several scientific papers have analyzed the advantages and risks of using AI tools like…
Descriptors: Artificial Intelligence, Technology Uses in Education, Cheating, Risk
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Jeremie Bouchard – Education and Information Technologies, 2025
ChatGPT is now widely understood in academia and the media as a 'game changer' in education. Detractors see it as fostering ethically problematic educational practices and a threat to the development of critical thinking skills, while fans see it as improving education by, in part, creating a more personalized educational experience. Meanwhile,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Practices, Ethics
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Sarah Burriss; Blaine Smith; Amanda Yoshiko Shimizu; Melanie Hundley; Emily Pendergrass; Ole Molvig – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2025
Generative artificial intelligence (AI) models are increasingly able to produce and combine sophisticated text, image, and audio. These advancements are challenging composers and teachers, as they work to reimagine and resist ways that composition and creative work are changing. This paper reports on one analysis in a larger study on multimodal…
Descriptors: Ethics, Artificial Intelligence, Writing (Composition), Computer Uses in Education
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Marianne Miserandino – Teaching of Psychology, 2025
Introduction: Artificial intelligence (AI) presents challenges and opportunities for higher education. The challenge is to incorporate the benefits of AI while minimizing its potential for misuse and undermining of learning. The opportunity is that AI allows instructors to assess learning authentically by fostering creative, engaging, realistic,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Evaluation Methods, Undergraduate Study
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Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
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Muhammad Bilal Saqib; Saba Zia – Journal of Applied Research in Higher Education, 2025
Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation
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Weikang Lu; Chenghua Lin – Education and Information Technologies, 2025
Artificial intelligence is increasingly integrated into daily life, and modern educated individuals should have the ability to use AI tools correctly to improve work, study, and life efficiency. In this context, artificial intelligence literacy has been proposed. Due to the lack of consensus on the constructs of artificial intelligence literacy,…
Descriptors: Artificial Intelligence, Digital Literacy, Student Attitudes, College Students
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Abdullah Al-Abri – Education and Information Technologies, 2025
This study explores the impact of ChatGPT, an advanced Large Language Model (LLM), as a virtual tutor in online education across five key dimensions: answering questions, writing assistance, study resources, exam preparation, and availability. Utilizing an experimental design, 68 undergraduate students from a public university interacted with…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Intelligent Tutoring Systems
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Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
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Merryn D. Constable; Francis Xiatian Zhang; Tony Conner; Daniel Monk; Jason Rajsic; Claire Ford; Laura Jillian Park; Alan Platt; Debra Porteous; Lawrence Grierson; Hubert P. H. Shum – Advances in Health Sciences Education, 2025
Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances -- both good and bad -- provides an opportunity for interdisciplinary research collaborations that…
Descriptors: Data Use, Artificial Intelligence, First Aid, Ethics
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Jiahui Luo; Chrysa Pui Chi Keung; Hei-hang Hayes Tang – Assessment & Evaluation in Higher Education, 2025
This study uses the concept of dilemmatic space to unpack the complexities of teachers' work when it comes to assessing students in the GenAI age. A key idea of dilemmatic space is that dilemmas are not 'out there' but constructions based on individuals' priorities, knowledge and values. Therefore, studying what teachers perceive as 'dilemmatic'…
Descriptors: Artificial Intelligence, College Faculty, Student Evaluation, Computer Uses in Education
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Christine E. Bell; Oana Birceanu – Advances in Physiology Education, 2025
One of the identified points of confusion and a barrier to students using generative artificial intelligence (GenAI) is knowing what their professor would consider appropriate use of GenAI in a classroom setting or course framework. This creates points of friction for instructors and students as they try to navigate an ever-changing landscape,…
Descriptors: Scaffolding (Teaching Technique), Artificial Intelligence, Physiology, Pharmacology
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