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Fan Zhang; Xiangyu Wang; Xinhong Zhang – Education and Information Technologies, 2025
Intersection of education and deep learning method of artificial intelligence (AI) is gradually becoming a hot research field. Education will be profoundly transformed by AI. The purpose of this review is to help education practitioners understand the research frontiers and directions of AI applications in education. This paper reviews the…
Descriptors: Learning Processes, Artificial Intelligence, Technology Uses in Education, Educational Research
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
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
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
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
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
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)
Sarab Tej Singh; Satish Kumar; Vishal Singh – Journal of Education and Learning (EduLearn), 2025
The current research is the study of academic buoyancy in relation to emotional intelligence and parenting styles. Academic buoyancy is a strength in a student's life to deal with the routine problems in classroom study like low grades, negative feedback by teachers, and difficulties in understanding of concepts. For the studying the relationship…
Descriptors: Parenting Styles, Emotional Intelligence, Predictor Variables, Academic Achievement
Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing
Keith J. Topping; Ed Gehringer; Hassan Khosravi; Srilekha Gudipati; Kaushik Jadhav; Surya Susarla – International Journal of Educational Technology in Higher Education, 2025
This paper surveys research and practice on enhancing peer assessment with artificial intelligence. Its objectives are to give the structure of the theoretical framework underpinning the study, synopsize a scoping review of the literature that illustrates this structure, and provide a case study which further illustrates this structure. The…
Descriptors: Peer Evaluation, Artificial Intelligence, Grades (Scholastic), Feedback (Response)
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
Kaylee Castleberry; Alexandra Amato; Carlos R. Benítez-Barrera – Journal of Speech, Language, and Hearing Research, 2025
Purpose: This registered report aimed to replicate previous findings showing that years of music training predicts speech-perception-in-noise (SPIN) skills in children. In addition, it aimed to investigate whether the musician SPIN advantage is influenced by cognitive factors such as general intelligence or working memory. Method: Following…
Descriptors: Music Education, Incidence, Musical Instruments, Short Term Memory
Xijing Wang; Hongbiao Yin – International Journal of STEM Education, 2025
A significant tension exists between the necessity for teachers to regulate their emotions and the tendency to overlook these emotions in STEM education. Teachers' emotion regulation is inherently context-sensitive and discipline-specific. Therefore, it is crucial for researchers to explore the particularities of teachers' emotion regulation in…
Descriptors: Emotional Response, Self Control, Psychological Patterns, STEM Education
Chan Aristella Lu – TechTrends: Linking Research and Practice to Improve Learning, 2025
This paper explores Stanford University's evolution in artificial intelligence (AI) education, emphasizing its interdisciplinary approach and collaboration with Silicon Valley. Building upon the university's foundational integration of liberal arts and industry partnerships, Stanford has facilitated frontier research in AI domains. Key initiatives…
Descriptors: Universities, Institutional Research, Artificial Intelligence, Educational Technology
Man Huang – Education and Information Technologies, 2025
As educational technology advances, the role of artificial intelligence (AI) in enhancing language education becomes increasingly prominent. However, there is a scarcity of empirical research assessing how AI integration influences student engagement and contributes to the language learning performance. This mixed-methods study seeks to fill the…
Descriptors: Foreign Countries, Middle School Students, Artificial Intelligence, Learner Engagement

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