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Sulaimon Adewale – International Journal of Information and Learning Technology, 2025
Purpose: This study aimed to explore the experiences of female academics and researchers in tertiary institutions in South Africa as a means of bridging the gaps in research productivity. Design/methodology/approach: The study adopted a qualitative research design of a phenomenological type to explore the experiences of purposively selected 20…
Descriptors: Foreign Countries, Females, Higher Education, Artificial Intelligence
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Félix González-Carrasco; Felipe Espinosa Parra; Izaskun Álvarez-Aguado; Sebastián Ponce Olguín; Vanessa Vega Córdova; Miguel Roselló-Peñaloza – British Journal of Learning Disabilities, 2025
Background: The study focuses on the need to optimise assessment scales for support needs in individuals with intellectual and developmental disabilities. Current scales are often lengthy and redundant, leading to exhaustion and response burden. The goal is to use machine learning techniques, specifically item-reduction methods and selection…
Descriptors: Artificial Intelligence, Intellectual Disability, Developmental Disabilities, Individual Needs
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Yoon Lee; Gosia Migut; Marcus Specht – British Journal of Educational Technology, 2025
Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI…
Descriptors: Artificial Intelligence, Cognitive Processes, Student Behavior, Cues
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Barbara Bordalejo; Davide Pafumi; Frank Onuh; A. K. M. Iftekhar Khalid; Morgan Slayde Pearce; Daniel Paul O'Donnell – International Journal of Educational Technology in Higher Education, 2025
This paper explores the growing complexity of detecting and differentiating generative AI from other AI interventions. Initially prompted by noticing how tools like Grammarly were being flagged by AI detection software, it examines how these popular tools such as Grammarly, EditPad, Writefull, and AI models such as ChatGPT and Microsoft Bing…
Descriptors: Artificial Intelligence, Writing (Composition), Quality Control, Writing Evaluation
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Yunjo An; Ji Hyun Yu; Shadarra James – International Journal of Educational Technology in Higher Education, 2025
This study examined the guidelines issued by the top 50 U.S. universities regarding the use of Generative AI (GenAI) in academic and administrative activities. Employing a mixed methods approach, the research combined topic modeling, sentiment analysis, and qualitative thematic analysis to provide a comprehensive understanding of institutional…
Descriptors: Higher Education, Artificial Intelligence, Educational Policy, School Policy
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Maria Ijaz Baig; Elaheh Yadegaridehkordi – International Journal of Educational Technology in Higher Education, 2025
Generative Artificial Intelligence (GenAI) tools hold significant promises for enhancing teaching and learning outcomes in higher education. However, continues usage behavior and satisfaction of educators with GenAI systems are still less explored. Therefore, this study aims to identify factors influencing academic staff satisfaction and…
Descriptors: Influences, College Faculty, Satisfaction, Technology Uses in Education
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Radek Pelánek – International Journal of Artificial Intelligence in Education, 2025
While the potential of personalized education has long been emphasized, the practical adoption of adaptive learning environments has been relatively slow. Discussion about underlying reasons for this disparity often centers on factors such as usability, the role of teachers, or privacy concerns. Although these considerations are important, I argue…
Descriptors: Educational Environment, Modeling (Psychology), Barriers, Adjustment (to Environment)
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Gale Macleod; Marshall Dozier; Rosa Marvell; Gerri Matthews-Smith; Malcolm R. Macleod; Jing Liao – Oxford Review of Education, 2024
This research aimed to describe and evaluate research on the Postgraduate Taught (PGT) sector in the UK from January 2008 to October 2019. The focus on PGT allowed a detailed analysis of an often overlooked part of the HE sector. Methodologically, the research is original in its use of an innovative machine learning approach to a systematic…
Descriptors: Research, Artificial Intelligence, Masters Programs, Foreign Countries
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Helen Crompton; Diane Burke – TechTrends: Linking Research and Practice to Improve Learning, 2024
ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA…
Descriptors: Artificial Intelligence, Barriers, Technology Uses in Education, Natural Language Processing
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Fletcher Wadsworth; Josh Blaney; Matthew Springsteen; Bruce Coburn; Nischal Khanal; Tessa Rodgers; Chase Livingston; Suresh Muknahallipatna – International Journal of Technology in Education and Science, 2024
Artificial Intelligence (AI) and, more specifically, Machine Learning (ML) methodologies have successfully tailored commercial applications for decades. However, the recent profound success of large language models like ChatGPT and the enormous subsequent funding from governments and investors have positioned ML to emerge as a paradigm-shifting…
Descriptors: Secondary School Students, Artificial Intelligence, High School Teachers, College Faculty
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Denchai Panket; Panita Wannapiroon; Prachyanun Nilsook – Higher Education Studies, 2024
This research aims to design an intelligent platform architecture for electronic asset supply chains for digital higher education and to evaluate the architecture of the intelligent platform for electronic asset supply chains for digital higher education. The sample group consists of evaluations of the intelligent platform architecture for the…
Descriptors: Supply and Demand, Information Management, Artificial Intelligence, Higher Education
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Ziqing Peng; Yan Wan – Education and Information Technologies, 2024
Understanding preferences surrounding artificial intelligence (AI) and human teaching assistants (TAs) helps managers improve AI TAs, effectively deploying AI and human TAs, and providing better services to learners. The literature has explored how AI TAs' characteristics affect students' use intention, neglecting students' comparative behaviors…
Descriptors: Artificial Intelligence, Teaching Assistants, Student Attitudes, Anxiety
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Sinan Hopcan; Gamze Türkmen; Elif Polat – Education and Information Technologies, 2024
With the advancement of artificial intelligence (AI) and machine learning (ML) techniques, attitudes towards these two fields have begun to gain importance in different professions. One of the affected professions is undoubtedly the teaching profession. Increasing the levels of concern for artificial intelligence and attitudes towards machine…
Descriptors: Artificial Intelligence, Educational Technology, Anxiety, Preservice Teachers
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Sadhu Prasad Kar; Amit Kumar Das; Rajeev Chatterjee; Jyotsna Kumar Mandal – Education and Information Technologies, 2024
Technology Enabled Learning (TEL) has a major impact on the learning adaptability of the learners. During the COVID-19 pandemic, there has been a drastic change in the learning methodology. The adaptability of learners from the various domains, levels and age has been a significant component of research in context to education. In this paper, the…
Descriptors: Online Courses, Artificial Intelligence, Technology Uses in Education, Student Adjustment
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Ozgun Uyanik Aktulun; Koray Kasapoglu; Bulent Aydogdu – Journal of Baltic Science Education, 2024
Identifying student teachers' attitudes and anxiety toward artificial intelligence (AI) in regard to their field of study might be helpful in determining whether and how AI will be employed in their future classrooms. Hence, this study aims to compare pre-service STEM and non-STEM teachers' attitudes and anxiety toward AI. In this quantitative…
Descriptors: Foreign Countries, Preservice Teachers, STEM Education, Student Attitudes
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