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Norizan Mat Diah; Syahirul Riza; Suzana Ahmad; Norzilah Musa; Shakirah Hashim – Journal of Education and Learning (EduLearn), 2025
Sudoku is a puzzle that has a unique solution. No matter how many methods are used, the result will always be the same. The player thought that the number of givens or clues, the initial value on the Sudoku puzzles, would significantly determine the difficulty level, which is not necessarily correct. This research uses two search algorithms,…
Descriptors: Puzzles, Artificial Intelligence, Problem Solving, Algorithms
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Leonidas Zotos; Hedderik van Rijn; Malvina Nissim – International Educational Data Mining Society, 2025
In an educational setting, an estimate of the difficulty of Multiple-Choice Questions (MCQs), a commonly used strategy to assess learning progress, constitutes very useful information for both teachers and students. Since human assessment is costly from multiple points of view, automatic approaches to MCQ item difficulty estimation are…
Descriptors: Multiple Choice Tests, Test Items, Difficulty Level, Artificial Intelligence
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Xiaoqing Xu; Lifang Qiao; Nuo Cheng; Hongxia Liu; Wei Zhao – British Journal of Educational Technology, 2025
The rapid development of generative artificial intelligence (GenAI) has brought opportunities and new challenges to higher education. Students need a high level of self-regulated learning to adapt to this change. However, it is difficult for students to persist in self-regulation without guidance. Metacognitive support has a significant advantage…
Descriptors: Independent Study, Learning Experience, Artificial Intelligence, Technology Uses in Education
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Sacip Toker; Mahir Akgun – Innovations in Education and Teaching International, 2025
This study examines whether assessments focused on higher-order cognitive skills can help reduce AI-driven plagiarism in educational settings. A total of 123 participants completed three tasks of increasing complexity, aligned with Bloom's taxonomy, across four groups: control, e-textbook, Google, and ChatGPT. Results from repeated-measures ANOVA…
Descriptors: Artificial Intelligence, Plagiarism, Intervention, Difficulty Level
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Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
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Kaitlyn Tracy; Ourania Spantidi – IEEE Transactions on Learning Technologies, 2025
Virtual reality (VR) has emerged as a transformative educational tool, enabling immersive learning environments that promote student engagement and understanding of complex concepts. However, despite the growing adoption of VR in education, there remains a significant gap in research exploring how generative artificial intelligence (AI), such as…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Simulation, Educational Technology
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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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Xiaodong Wei; Lei Wang; Lap-Kei Lee; Ruixue Liu – Journal of Educational Computing Research, 2025
Notwithstanding the growing advantages of incorporating Augmented Reality (AR) in science education, the pedagogical use of AR combined with Pedagogical Agents (PAs) remains underexplored. Additionally, few studies have examined the integration of Generative Artificial Intelligence (GAI) into science education to create GAI-enhanced PAs (GPAs)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Science Education
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Chih-Hung Wu; Vu Tran Ho – Education and Information Technologies, 2025
The present study investigated the potential of ChatGPT in enhancing the learning outcomes and engagement. Data were gathered from a survey of 687 university personnel and higher education students who utilized ChatGPT for educational purposes. The conceptual framework of the study was validated and analyzed using partial least squares structural…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Learner Engagement
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Linling Shen; Jessica Kane-Cabello; Patricia Y. Candelaria; Dianne Stratford; Nathan H. Clemens – Learning Disabilities Research & Practice, 2025
Reading practice is crucial for students with reading difficulties, but locating texts for reading practice can be time-consuming for teachers. Artificial intelligence (AI) tools (e.g., ChatGPT) can rapidly create text according to specified parameters, but the application of creating content for reading intervention has not been examined. We used…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reading Materials, Readability
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Hamza Rababa; Ali Al-Omari – Educational Process: International Journal, 2025
Background/purpose: This study aimed to measure the level of scientific concepts acquisition among basic-stage students in light of their teachers' use of artificial intelligence (AI) applications. Materials/methods: A scientific concepts acquisition test was developed to collect data. The study sample consisted of 396 tenth-grade students,…
Descriptors: Scientific Concepts, Concept Formation, Secondary School Students, Grade 10
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Saso Koceski; Natasa Koceska; Limonka Koceva Lazarova; Marija Miteva; Biljana Zlatanovska – Journal of Technology and Science Education, 2025
This study aims to evaluate ChatGPT's capabilities in certain numerical analysis problem: solving ordinary differential equations. The methodology which is developed in order to conduct this research takes into account the following mathematical abilities (defined according to National Centre for Education Statistics): Conceptual Understanding,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Number Concepts, Problem Solving
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Giulia Cosentino; Jacqueline Anton; Kshitij Sharma; Mirko Gelsomini; Michail Giannakos; Dor Abrahamson – British Journal of Educational Technology, 2025
This study explores the role of generative AI (GenAI) in providing formative feedback in children's digital learning experiences, specifically in the context of mathematics education. Using multimodal data, the research compares AI-generated feedback with feedback from human instructors, focusing on its impact on children's learning outcomes.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Mathematics Education
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Chia-Jung Li; Gwo-Jen Hwang; Ching-Yi Chang; Hui-Chi Su – British Journal of Educational Technology, 2025
In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prompting, Academic Achievement
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Syed Mujahid Hussain; Aqdas Malik; Nisar Ahmad; Sheraz Ahmed – Journal of Educational Technology Systems, 2025
This study assesses the performance of ChatGPT in comparison with that of undergraduate students in 60 multiple-choice questions (MCQs) of Corporate Finance exams that sought to measure students' abilities to solve different types of questions (descriptive and numerical) and of varying difficulty levels (basic and intermediate). Our results…
Descriptors: Business Education, Finance Occupations, Undergraduate Students, Multiple Choice Tests
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