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Ridvan Elmas; Merve Adiguzel-Ulutas; Mehmet Yilmaz – Education and Information Technologies, 2024
Many people use technological tools that are widely accessible, respond quickly, and have extensive information networks today. Due to recent technological advances in education and the increasing acceptance of Artificial Intelligence (AI) technologies, the issues regarding their implementation in education require identification and analysis.…
Descriptors: Artificial Intelligence, Science Education, Biochemistry, Information Dissemination
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Ayse Alkan; Ezgi Pelin Yildiz – International Journal of Research in Education and Science, 2024
The main goal of this study is to reveal special talented primary school students' perceptions of artificial intelligence, one of the popular concepts of recent times, through metaphors. In this study, the phenomenological design, which is within the scope of qualitative research, was used. In this study, Türkiye Science and Art Center included…
Descriptors: Foreign Countries, Gifted, Elementary School Students, Middle School Students
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Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
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Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
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Dan Shen; Wenjia Zhao – International Journal of Web-Based Learning and Teaching Technologies, 2024
With the development of internet technology, big data has been used to evaluate the singing and pronunciation quality of vocal students. However, current methods have several problems such as poor information fusion efficiency, low algorithm robustness, and low recognition accuracy under low signal-to-noise ratio. To address these issues, this…
Descriptors: Data, Music Education, Pronunciation, Singing
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Ye Sul Park – Art Education, 2024
The advent of large language models (LLMs) such as ChatGPT and text-to-image generation systems like DALL-E developed by OpenAI has raised critical questions in education and art communities, urging us not only to reconceptualize our understanding of creativity, authorship, and human--machine relations, but also to examine their social and ethical…
Descriptors: Artificial Intelligence, Cultural Education, Art Education, Racial Discrimination
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Thulasi M. Santhi; K. Srinivasan – IEEE Transactions on Learning Technologies, 2024
Cloud adoption in industrial sectors, such as process, manufacturing, health care, and finance, is steadily rising, but as it grows, the risk of targeted cyberattacks has increased. Hence, effectively defending against such attacks necessitates skilled cybersecurity professionals. Traditional human-based cyber-physical education is resource…
Descriptors: Artificial Intelligence, Information Security, Computer Security, Prevention
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Chandan Kumar Tiwari; Mohd. Abass Bhat; Shagufta Tariq Khan; Rajaswaminathan Subramaniam; Mohammad Atif Irshad Khan – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this paper is to identify the factors determining students' attitude toward using newly emerged artificial intelligence (AI) tool, Chat Generative Pre-Trained Transformer (ChatGPT), for educational and learning purpose based on technology acceptance model. Design/methodology/approach: The recommended model was empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
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Bryan Abendschein; Xialing Lin; Chad Edwards; Autumn Edwards; Varun Rijhwani – Journal of Computer Assisted Learning, 2024
Background: Education is often the primary arena for exploring and integrating new technologies. AI and human-machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written…
Descriptors: Students, Student Attitudes, Feedback (Response), Writing (Composition)
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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
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Edwin Chng – Journal of Science Education and Technology, 2024
With teachers continuing to report challenges in classroom management and difficulties in implementing scientific inquiry, the current manner in which science practical work is conducted in schools suggests the need for added teacher support. In this regard, we can leverage computer vision to provide instructional support by relieving teachers of…
Descriptors: Artificial Intelligence, Science Education, Computer Uses in Education, Science Teachers
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Jian Zhao; Elaine Chapman; Peyman G. P. Sabet – Education Research and Perspectives, 2024
The launch of ChatGPT and the rapid proliferation of generative AI (GenAI) have brought transformative changes to education, particularly in the field of assessment. This has prompted a fundamental rethinking of traditional assessment practices, presenting both opportunities and challenges in evaluating student learning. While numerous studies…
Descriptors: Literature Reviews, Artificial Intelligence, Evaluation Methods, Student Evaluation
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Amal Abdullah Alibrahim – South African Journal of Education, 2024
After ChatGPT was released late in 2022, many arguments about its accuracy and use in education arose. In this article, I seek to provide evidence of the accuracy and validity of ChatGPT's responses to users' queries in education by applying a systematic review methodology to analyse publications in specific databases following PRISMA guidelines…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reliability, Natural Language Processing
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Pan, Yiqin; Wollack, James A. – Journal of Educational Measurement, 2021
As technologies have been improved, item preknowledge has become a common concern in the test security area. The present study proposes an unsupervised-learning-based approach to detect compromised items. The unsupervised-learning-based compromised item detection approach contains three steps: (1) classify responses of each examinee as either…
Descriptors: Test Items, Cheating, Artificial Intelligence, Identification
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Pekrun, Reinhard – British Journal of Educational Psychology, 2023
Background and Aims: Traditionally, research in educational psychology has neglected the physiological foundations of motivation, emotion, engagement, and learning. Recent studies have made substantial progress to more fully consider physiological processes, as documented in the contributions to this special issue. In this commentary, I summarize…
Descriptors: Higher Education, Artificial Intelligence, Publications, Researchers
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