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Akmarzhan Nogaibayeva; Gaukhar Yersultanova – Contemporary Educational Technology, 2025
This study explores secondary school teachers' perspectives on artificial intelligence (AI)- supported tools through qualitative in-depth interviews with 16 teachers of English as a foreign language in Kazakhstan. The research aimed to understand teachers' views on pedagogy, their knowledge of AI, and their perceptions of its opportunities and…
Descriptors: Foreign Countries, Teacher Attitudes, Secondary School Teachers, Artificial Intelligence
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Behnam Behforouz; Ali Al Ghaithi – Technology in Language Teaching & Learning, 2025
This study aimed to utilise artificial intelligence (AI) tools to create animations to assess the impact of AI-created cartoons on vocabulary growth and motivation levels among learners. For this purpose, 80 Omani EFL learners with a pre-intermediate level of English proficiency were randomly assigned to an experimental and a control group, each…
Descriptors: Foreign Countries, Artificial Intelligence, Animation, English (Second Language)
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Muhammed Murat Gümüs; Mehmet Kara – Australasian Journal of Educational Technology, 2025
Research on artificial intelligence (AI) in education has mainly focused on the measurement instruments relevant to learning about AI and framing AI literacy as learning about AI. The present study's focus, however, was on developing and validating a scale pertinent to learning with generative artificial intelligence (GenAI) in higher education.…
Descriptors: Foreign Countries, Artificial Intelligence, Measures (Individuals), Test Validity
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Maya Usher; Miri Barak; Sibel Erduran – International Journal of STEM Education, 2025
Background: The rapid advancement of artificial intelligence (AI) has raised significant ethical concerns, prompting higher education institutions to reconsider how they prepare future STEM professionals to navigate such concerns responsibly. Despite growing efforts to integrate AI ethics into higher education, a lack of consensus and standardized…
Descriptors: Artificial Intelligence, Ethics, Ethical Instruction, Higher Education
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Bo Sun; Yadian Du; Zhiyu Yao; Asta Rauduvaite – European Journal of Education, 2025
As artificial intelligence (AI) technologies become increasingly integrated into educational settings, understanding the factors that influence teachers' acceptance or resistance to AI is critical, particularly in the STEM education sector. Despite growing interest in AI in education, few studies have examined the psychological and cultural…
Descriptors: Resistance (Psychology), Artificial Intelligence, Cultural Awareness, STEM Education
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Chun Li; Mehdi Solhi; Yongxiang Wang – European Journal of Education, 2025
The crucial role of teachers' interpersonal communication skills in diverse aspects of second language (L2) education has been endorsed by prior scholarship. Such significance multiplies in artificial intelligence (AI)-mediated education in which interaction fosters understanding and using content and feedback. Nevertheless, the literature has…
Descriptors: Foreign Countries, Language Teachers, English (Second Language), Teacher Student Relationship
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Sarah Seeley; Michael Cournoyea – Teaching & Learning Inquiry, 2025
Qualitative studies that examine the impact of generative AI technologies on higher education remain scant. Whether it is the ethical dimensions of modeling human emotions within these technologies or the authentic emotional reactions to these technologies and their outputs--emotionality is at the centre of generative AI discourse. This paper…
Descriptors: Robotics, Artificial Intelligence, Technology Uses in Education, Psychological Patterns
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Amy M. Cedrone – Teaching and Learning Excellence through Scholarship, 2025
In this descriptive study I wanted to see how including an assignment which required students to use generative artificial intelligence (AI) would affect students' perceptions of generative AI, including their own assessment and grading of generative AI-created content. I theorized that more than half the students would assess the generative AI's…
Descriptors: Business Education, Ethics, Artificial Intelligence, Decision Making
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Mai Dong Tran; Khanh Huy Nguyen; Huyen Trang Nguyen; Thi Hong Nhung Dinh; Hoang Huy Vu Leng; Thanh Tra Tran; Anh Ho; Thi Bich Tram Ho; Dinh Nhan Nguyen – Higher Education, Skills and Work-based Learning, 2025
Purpose: The study explores the acceptance of AI-driven virtual teaching assistants (VTAs) in Vietnam's online learning. It aims to identify factors influencing students' intention and actual use of these emerging technologies. Design/methodology/approach: Using an extended Unified Theory of Acceptance and Use of Technology (UTAUT2), the research…
Descriptors: Artificial Intelligence, Technology Uses in Education, Robotics, College Students
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Sabine Seufert; Niklas Eulitz – International Association for Development of the Information Society, 2025
The widespread adoption of generative AI is transforming academic writing in higher education, rendering traditional, product-focused assessment models obsolete. These methods fail to capture the iterative and tool-mediated nature of modern writing processes, creating an urgent need for new evaluation approaches. This paper addresses this gap by…
Descriptors: Artificial Intelligence, Academic Language, Writing Processes, Models
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Kensuke Akao; Mohammad Nehal Hasnine; Mirai Yamada; Hiroshi Ueda – International Association for Development of the Information Society, 2025
In recent years, the rapid technological development and widespread adoption of chatbots equipped with generative artificial intelligence (GenAI) based on Large Language Models (LLMs) have brought dramatic changes in the field of education. In e-learning, flexible progression and real-time feedback enabled by human-like interaction with artificial…
Descriptors: Artificial Intelligence, Technology Uses in Education, Vocabulary, Sentences
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Kaitlin Gili; Kyle Heuton; Astha Shah; David Hammer; Michael C. Hughes – Physical Review Physics Education Research, 2025
Advances in machine learning (ML) offer new possibilities for science education research. We report on early progress in the design of an ML-based tool to analyze students' mechanistic sensemaking, working from a coding scheme that is aligned with previous work in physics education research (PER) and that is amenable to recently developed ML…
Descriptors: Physics, Science Education, Educational Research, Artificial Intelligence
Yuan, Shuaihang – ProQuest LLC, 2023
Recently, with the advancement in 2D imaging techniques and 3D visual sensors such as LiDAR, RGB-D cameras, etc. The use of 2D and 3D data is ubiquitous in various fields like autonomous driving, AR, and VR. Therefore, we are faced with an ever-increasing demand for approaches toward the automatic processing and analysis of data from multiple…
Descriptors: Computer Simulation, Geometry, Artificial Intelligence, Data Analysis
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Shimmei, Machi; Matsuda, Noboru – International Educational Data Mining Society, 2023
We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…
Descriptors: Artificial Intelligence, Training, Natural Language Processing, Educational Research
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Rohani, Narjes; Gal, Kobi; Gallagher, Michael; Manataki, Areti – International Educational Data Mining Society, 2023
Massive Open Online Courses (MOOCs) make high-quality learning accessible to students from all over the world. On the other hand, they are known to exhibit low student performance and high dropout rates. Early prediction of student performance in MOOCs can help teachers intervene in time in order to improve learners' future performance. This is…
Descriptors: Prediction, Academic Achievement, Health Education, Data Science
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