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Hilal Ugras; Mustafa Ugras; Stamatios Papadakis; Michail Kalogiannakis – Technology, Knowledge and Learning, 2025
This study aims to evaluate the integration of AI-supported ChatGPT into early childhood STEM education from the teachers' perspective. The study group comprised 18 teachers who had previously received training on the use of ChatGPT. A phenomenological approach was adopted within the qualitative research framework, utilising a semi-structured…
Descriptors: Artificial Intelligence, Technology Integration, Early Childhood Education, STEM Education
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Ruixun Dai; Matthew Krehl Edward Thomas; Shaun Rawolle – British Journal of Sociology of Education, 2025
This article applies Foucault's theories of surveillance, disciplinary power, and normalisation to examine the shifting power dynamics in AI-mediated education. Drawing on qualitative responses from 27 English and Chinese-speaking stakeholders, including students, teachers, administrators and parents with no geographical restrictions, this study…
Descriptors: Educational Philosophy, Power Structure, Artificial Intelligence, Technology Uses in Education
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Canfer Akbulut; Geoffrey Bird – Autism: The International Journal of Research and Practice, 2025
The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic community. In response to what was perceived as a misrepresentation of their interests, autistic individuals formed autistic self-advocacy groups, adopting the philosophy that autism advocacy should…
Descriptors: Social Media, Autism Spectrum Disorders, Advocacy, Organizations (Groups)
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Christian Coenen; Mirjam Pfenninger – New Directions for Teaching and Learning, 2025
This article examines the transformative impact of generative artificial intelligence (GenAI) in enhancing feedback quality in a Bachelor of Science course. It the challenges of providing personalized, timely feedback to students in larger educational settings, focusing on the use of GenAI to analyze and respond to student logbooks. These logbooks…
Descriptors: Learning Experience, Student Evaluation, Artificial Intelligence, Feedback (Response)
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Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
Mohammad Ghulam Ali – Online Submission, 2025
As the debate and discussions are rapidly growing about the implementation of Artificial Intelligence (AI) in higher education institutions (HEIs) as well as in other sectors, we have gone through a systematic review and research of the topics and progress of AI at the present time. We have surveyed much literature and prepared a research review…
Descriptors: Artificial Intelligence, Educational Benefits, Higher Education, Computer Software
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Stefan Küchemann; Karina E. Avila; Yavuz Dinc; Chiara Hortmann; Natalia Revenga; Verena Ruf; Niklas Stausberg; Steffen Steinert; Frank Fischer; Martin Fischer; Enkelejda Kasneci; Gjergji Kasneci; Thomas Kuhr; Gitta Kutyniok; Sarah Malone; Michael Sailer; Albrecht Schmidt; Matthias Stadler; Jochen Weller; Jochen Kuhn – npj Science of Learning, 2025
Recently, the option to use large language models as a middleware connecting various AI tools and other large language models led to the development of so-called large multimodal foundation models, which have the power to process spoken text, music, images and videos. In this overview, we explain a new set of opportunities and challenges that…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Intermode Differences
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Luis Medina-Gual; José-Luis Parejo – European Journal of Education, 2025
The present research explores AI's impact on education among Mexican undergraduate students through a non-experimental, correlational, cross-sectional study. A validated public questionnaire was distributed to 840 students via Google Forms from February to May 2024. Analysis revealed significant AI exposure and use patterns, primarily influenced…
Descriptors: Artificial Intelligence, Teaching Methods, Ethics, Learning Processes
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Yan Li; Xinyan Zhou; Hong-biao Yin; Thomas K. F. Chiu – Smart Learning Environments, 2025
Artificial Intelligence (AI) chatbots, with their ability to engage in conversations that resemble human interactions, have been increasingly applied to language teaching. Most recent review studies overlook student learning outcomes and the methods to achieve these outcomes in chatbot-supported language learning. Activity Theory (AT) offers a…
Descriptors: Artificial Intelligence, Educational Technology, Language Acquisition, Outcomes of Education
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Jiaxin Ren; Yee Hock Tan; Juncheng Guo – International Journal of Technology in Education, 2025
The metaverse is a virtual reality space that provides a novel and significant environment, fostering educational opportunities and serving as a rich platform for innovative forms of learning. This bibliometric analysis uses the Scopus database as a source for review, employing the PRISMA method to identify 270 articles, with visualisation…
Descriptors: Educational Research, Journal Articles, Computer Simulation, Artificial Intelligence
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Michael A. Smith – Information Systems Education Journal, 2025
Maloof & Associates (M&A), a well-regarded small auditing and accounting firm in Atlanta, kept a close eye on the media buzz surrounding ChatGPT. The partners knew that they must make decisions soon regarding the new technology, but they did not realize how soon until they lost a long-standing and substantial client to a rival that had…
Descriptors: Accounting, Barriers, Artificial Intelligence, Natural Language Processing
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Nan Xie; Zhengxu Li; Haipeng Lu; Wei Pang; Jiayin Song; Beier Lu – IEEE Transactions on Learning Technologies, 2025
Classroom engagement is a critical factor for evaluating students' learning outcomes and teachers' instructional strategies. Traditional methods for detecting classroom engagement, such as coding and questionnaires, are often limited by delays, subjectivity, and external interference. While some neural network models have been proposed to detect…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Educational Technology
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Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
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Mohamed Ali Nagy Elmaadaway; Mohamed Elsayed El-Naggar; Mohamed Radwan Ibrahim Abouhashesh – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) made substantial progress with language recognition. Proficiency in spoken English reading is a prerequisite for fluency in written English. However, research on its use, especially for non-native speakers, is lacking despite increased usage. Objectives: This study aimed to enhance the oral reading fluency…
Descriptors: Artificial Intelligence, Reading Fluency, Elementary School Students, Oral Reading
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Jan Gunis; L'ubomir Snajder; L'ubomir Antoni; Peter Elias; Ondrej Kridlo; Stanislav Krajci – IEEE Transactions on Education, 2025
Contribution: We present a framework for teachers to investigate the relationships between attributes of students' solutions in the process of problem solving or computational thinking. We provide visualization and evaluation techniques to find hidden patterns in the students' solutions which allow teachers to predict the specific behavior of…
Descriptors: Artificial Intelligence, Educational Games, Game Based Learning, Problem Solving
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