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Showing 1 to 15 of 49 results Save | Export
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Hongfeng Zhang; Fanbo Li; Xiaolong Chen – Journal of Educational Computing Research, 2025
This study addresses the gap in understanding graduate students' sustained engagement behavior (SEB) with generative artificial intelligence (GAI) by integrating the Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT), and Theory of Reasoned Action (TRA) into a comprehensive embedding model. It introduces the Technology…
Descriptors: Graduate Students, Artificial Intelligence, Learner Engagement, Foreign Countries
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Emmanuel Fokides; Eirini Peristeraki – Education and Information Technologies, 2025
This research analyzed the efficacy of ChatGPT as a tool for the correction and provision of feedback on primary school students' short essays written in both the English and Greek languages. The accuracy and qualitative aspects of ChatGPT-generated corrections and feedback were compared to that of educators. For the essays written in English, it…
Descriptors: Artificial Intelligence, Error Correction, Feedback (Response), Elementary School Students
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Alison M. O'Connor; Jennifer Gongola; Kaila C. Bruer; Thomas D. Lyon; Angela D. Evans – Applied Cognitive Psychology, 2025
The accurate detection of children's truthful and dishonest reports is essential as children can serve as important providers of information. Research using automated facial coding and machine learning found that children who were asked to lie about an event were more likely to look surprised when hearing the first question during an interview…
Descriptors: Deception, Nonverbal Communication, Recognition (Psychology), Children
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Xiaoming Zhai; Matthew Nyaaba; Wenchao Ma – Science & Education, 2025
This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four…
Descriptors: Artificial Intelligence, National Competency Tests, Elementary Secondary Education, Problem Solving
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Siyi Cao; Yizhong Xu; Tongquan Zhou; Siruo Zhou – Education and Information Technologies, 2025
ChatGPT has been demonstrated to possess significant capabilities in generating intricate human-like text, and recent studies have established that its performance in theory of mind (ToM) tasks is strikingly comparable to a nine-year-old child's. However, it remains unknown whether ChatGPT outperforms children of this age group in Chinese writing,…
Descriptors: Foreign Countries, Artificial Intelligence, Theory of Mind, Chinese
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Liuying Gong; Jingyuan Chen; Fei Wu – IEEE Transactions on Learning Technologies, 2025
The capabilities of large language models (LLMs) in language comprehension, conversational interaction, and content generation have led to their widespread adoption across various educational stages and contexts. Given the fundamental role of education, concerns are rising about whether LLMs can serve as competent teachers. To address the…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Comparative Analysis
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Ernst Bekkering; Patrick Harrington – Information Systems Education Journal, 2025
Generative AI has recently gained the ability to generate computer code. This development is bound to affect how computer programming is taught in higher education. We used past programming assignments and solutions for textbook exercises in our introductory programming class to analyze how accurately one of the leading models, ChatGPT, generates…
Descriptors: Higher Education, Artificial Intelligence, Programming, Textbook Evaluation
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Elizabeth L. Wetzler; Kenneth S. Cassidy; Margaret J. Jones; Chelsea R. Frazier; Nickalous A. Korbut; Chelsea M. Sims; Shari S. Bowen; Michael Wood – Teaching of Psychology, 2025
Background: Generative artificial intelligence (AI) represents a potentially powerful, time-saving tool for grading student essays. However, little is known about how AI-generated essay scores compare to human instructor scores. Objective: The purpose of this study was to compare the essay grading scores produced by AI with those of human…
Descriptors: Essays, Writing Evaluation, Scores, Evaluators
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Olena Bolgova; Paul Ganguly; Volodymyr Mavrych – Anatomical Sciences Education, 2025
Integrating artificial intelligence, particularly large language models (LLMs), into medical education represents a significant new step in how medical knowledge is accessed, processed, and evaluated. The objective of this study was to conduct a comprehensive analysis comparing the performance of advanced LLM chatbots in different topics of…
Descriptors: Comparative Analysis, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Karin Tengler; Gerhard Brandhofer – Discover Education, 2025
Generative Artificial Intelligence (GenAI) models have grown increasingly popular among pre-service teachers (PSTs) and have become their constant companions, primarily assisting them in scientific writing. This article presents a study that investigates the differences and benefits of GenAI in the scientific writing process. Essays generated by…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Writing (Composition)
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Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
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Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
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Muhammad Amin Nadim; Raffaele Di Fuccio – European Journal of Education, 2025
Higher education has witnessed remarkable technological advancements; however, the rapid rise of generative artificial intelligence (Gen AI) presents substantial challenges for teaching and research. This growing reliance has expanded educators' roles, underscoring the need for ethical and selective AI integration while preparing students and…
Descriptors: Artificial Intelligence, Teaching Methods, Learning Processes, Ethics
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Xavier Ochoa; Xiaomeng Huang; Yuli Shao – Journal of Learning Analytics, 2025
Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…
Descriptors: Learning Analytics, Artificial Intelligence, Computer Software, Scores
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Peter Daly; Emmanuelle Deglaire – Innovations in Education and Teaching International, 2025
AI-enabled assessment of student papers has the potential to provide both summative and formative feedback and reduce the time spent on grading. Using auto-ethnography, this study compares AI-enabled and human assessment of business student examination papers in a law module based on previously established rubrics. Examination papers were…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, College Faculty
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