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Eunsung Park; Jongpil Cheon – Journal of Educational Computing Research, 2025
Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…
Descriptors: Undergraduate Students, Programming, Computer Software, Troubleshooting
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Hatoon S. AlSagri; Faiza Farhat; Shahab Saquib Sohail; Abdul Khader Jilani Saudagar – Journal of Academic Ethics, 2025
The rapid evolution of scientific research has created a pressing need for efficient and versatile tools to aid researchers. While using artificial intelligence (AI) to write scientific articles is unethical and unreliable due to the potential for inaccuracy, AI can be a valuable tool for assisting with other aspects of research, such as language…
Descriptors: Artificial Intelligence, Computer Software, Comparative Analysis, Technical Writing
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Ted K. Mburu; Kangxuan Rong; Campbell J. McColley; Alexandra Werth – Journal of Engineering Education, 2025
Background: This study investigates the use of large language models to create adaptive, contextually relevant survey questions, aiming to enhance data quality in educational research without limiting scalability. Purpose: We provide step-by-step methods to develop a dynamic survey instrument, driven by artificial intelligence (AI), and introduce…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Computational Linguistics
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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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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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Yanping Geng; Reem Alshahrani; Hana Mohammed Mujlid – European Journal of Education, 2025
The Fuzzy Analytic Hierarchy Process (FAHP) was employed to evaluate and rank language-learning applications based on criteria such as engagement, interactivity, feedback, content quality and usability. A pairwise comparison matrix was constructed, fuzzy logic was applied to convert qualitative judgements into numerical values, and these values…
Descriptors: Second Language Learning, Social Media, Handheld Devices, Computer Software
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Meria Ultra Gusteti; Widdya Rahmalina; Suci Wulandari; Khairul Azmi; Asrina Mulyati; Rahmatul Hayati; Rana Gustina; Vifit Nor Cahyati – International Journal of Education in Mathematics, Science and Technology, 2025
This study aims to test the effectiveness of GeoGebra Augmented Reality in improving students' mathematical problem-solving skills. The method used is a quasi-experiment with a posttest-only control group design. The research population is students of the Mathematics Education Study Program at a private university in Indonesia, with a sample of 32…
Descriptors: Computer Software, Computer Simulation, Mathematics Instruction, Problem Solving
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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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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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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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Gerard Dummer; Elwin Savelsbergh; Paul Drijvers – Informatics in Education, 2025
Programmed control systems are ubiquitous in the present-day world. In current educational practice, however, these systems are hardly being addressed, and little is known about children's spontaneous understandings about such systems. Therefore, we explored pupils' understandings prior to instruction in three concrete settings: a car park, an…
Descriptors: Elementary School Students, Grade 3, Grade 6, Computer Science Education
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Daniel R. Fredrick; Thomas P. Corbin Jr.; Gregory VanderPyl – Athens Journal of Education, 2025
This paper analyzes essay writing in AI (ChatGPT) and high school students, focusing on their use of specific details. Discussing the writing examples from Waltzer, Cox, and Heyman's study, we employ Aristotle's rhetorical theory to explore how clarity is achieved through specificity in writing. The analysis reveals both ChatGPT and students…
Descriptors: Artificial Intelligence, Technology Integration, Computer Software, Essays
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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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Guohui Xing; Xiaofeng Luo – International Journal of Distance Education Technologies, 2025
This study discusses the value of applying the practical strategy of top-level design of artificial intelligence (AI) in the ideological and political theory courses (IPC) in China universities, aiming at improving the ideological and political literacy (PA) of college students. The research first implements IPC through AI network media, then…
Descriptors: Instructional Innovation, Artificial Intelligence, Political Attitudes, Computer Software
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