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Phil Seok Oh; Gyeong-Geon Lee – Science & Education, 2025
How and why science education scholars and practitioners might use artificial intelligence (AI) in the classroom has been a controversial agenda for decades. ChatGPT, a state-of-the-art (SOTA) AI released in November 2022, has attracted global interest for its exceptionally high performance in generating human-like natural language answers to…
Descriptors: Science Education, Artificial Intelligence, Cognitive Processes, Affective Behavior
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William Billingsley – Science & Education, 2025
This article explores the epistemological trade-offs that practical and technology design fields make by exploring past philosophical discussions of design, practitioner research, and pragmatism. It argues that as technologists apply Artificial Intelligence (AI) and machine learning (ML) to more domains, the technology brings this same set of…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Technology Integration
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Julianna Lopez Kershen; Brianne Johnson – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2025
This conceptual article makes the argument that the fields of English language arts and composition studies require a more robustly elaborated theoretical perspective on the identity development of preservice teachers as teachers of writing due to the rapid proliferation of AI-assisted technologies in learning spaces. Thus, the authors utilized…
Descriptors: Writing Teachers, Artificial Intelligence, Theories, Technology Uses in Education
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Flora Ji-Yoon Jin; Bhagya Maheshi; Wenhua Lai; Yuheng Li; Danijela Gasevic; Guanliang Chen; Nicola Charwat; Philip Wing Keung Chan; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Learning Analytics, 2025
This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Learning Analytics
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Chia-Ju Lin; Hsin-Yu Lee; Wei-Sheng Wang; Yueh-Min Huang; Ting-Ting Wu – Education and Information Technologies, 2025
With the promotion of STEM education and active practice, experiential learning has become a crucial instructional design strategy. Experiential learning emphasizes a student-centered learning model, encouraging students to explore unknown fields through individual and team collaborative efforts. Through practical activities, it promotes active…
Descriptors: STEM Education, Experiential Learning, Student Centered Learning, Artificial Intelligence
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Lori L. Montalbano; Sharon Stoerger – Assessment Update, 2025
The post-pandemic expectations of today's students require greater innovation in teaching and learning. Rapidly changing technologies and software applications will drastically change how higher education is structured and disseminated. In this article, the authors examine the use of micro-credentialing, the potential and challenges of Artificial…
Descriptors: Artificial Intelligence, Teaching Methods, Evaluation Methods, Educational Trends
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Éva Gál – Psychology in the Schools, 2025
Previous studies indicated that when encountering academic difficulties, students with fixed intelligence mindset, experience higher levels of negative emotions and they also report significant drops in their self-esteem. Thus, the present study proposed to test whether priming students with unconditional self-acceptance (USA), reduces…
Descriptors: Intelligence, Self Esteem, Self Concept, Academic Achievement
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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
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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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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
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