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Carmen Vallis; Stephanie Wilson; Alison Casey – Journal of Interactive Media in Education, 2025
In this paper, we advance the examination of generative AI (GenAI) in educational contexts in two distinct ways. First, we introduce and evaluate an innovative workshop model designed to explore GenAI metaphors, helping participants to articulate their own and their peers' responses to the technology. These workshops included students, academics…
Descriptors: Foreign Countries, Higher Education, Artificial Intelligence, Figurative Language
Granit Baca; Genc Zhushi – Higher Education, Skills and Work-based Learning, 2025
Purpose: This study aims to examine the integration of AI in student engagement and its benefits in the learning environment. Design/methodology/approach: The study employed a quantitative research method, analyzing data from a sample of 720 students. The econometric data analysis used the structural equation modeling (SEM) technique. Findings:…
Descriptors: Artificial Intelligence, Technology Integration, Technology Uses in Education, Higher Education
Eyvind Elstad; Harald Eriksen – Journal of Teacher Education and Educators, 2025
This study aims to explore the factors influencing Norwegian high school teachers' instructional resistance to artificial intelligence (AI) in terms of age, instructional AI efficacy, and collective AI beliefs among school staff. Grounded in a robust theoretical framework that integrates technology-use models, social cognitive theory, and…
Descriptors: Foreign Countries, High School Teachers, Artificial Intelligence, Teacher Attitudes
Hoora Dehghani; Amir Mashhadi – Education and Information Technologies, 2024
This study explores the factors influencing the acceptance of ChatGPT, an artificial intelligence chatbot, for English Language Teaching (ELT) among Iranian EFL (English as a Foreign Language) teachers. The research framework is grounded in the Technology Acceptance Model (TAM), augmented with external factors pertaining to system characteristics…
Descriptors: Foreign Countries, Language Teachers, English (Second Language), Teacher Attitudes
Taha Oruç; Özgen Korkmaz; Murat Kurt – International Journal of Technology in Education and Science, 2024
The aim of this study is to examine primary school students' views on artificial intelligence. Phenomenology design, one of the qualitative research methods, was used in the study. The study was conducted with 25 fourth grade students. The participants of the study were determined using the criterion sampling method, one of the purposeful sampling…
Descriptors: Foreign Countries, Elementary School Students, Grade 4, Student Attitudes
Ce Song – European Journal of Education, 2025
This study examines the role of AI-powered learning tools in influencing cognitive load, well-being and academic success among music education students, with a focus on technology acceptance as a key factor. Data were collected through a random sampling of 454 Chinese music students (192 males, 262 females) aged 18-24, with varying levels of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Music Education
Richard Brown; Elizabeth Sillence; Dawn Branley-Bell – Journal of Educational Technology Systems, 2025
We investigate perceptions of AI among university students and staff, focusing on sociodemographic predictors of use, attitudes and literacy. We follow an explanatory mixed-methods approach: an online survey (269 students and staff) capturing self-reported AI use, attitudes, and literacy, and 24 semi-structured online interviews exploring barriers…
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Student Attitudes
Sankaranarayanan Paleeri; Sneha Parambath – Journal of Educational Technology, 2025
This study explored the perceptions of learners, teachers, and administrators on the role of artificial intelligence (AI) in the higher secondary school education scenario of Kerala. The study was a comprehensive survey, and sample groups included 360 students, 60 teachers, and 5 administrators. Both qualitative methods and quantitative techniques…
Descriptors: Artificial Intelligence, Computer Uses in Education, Student Attitudes, Teacher Attitudes
Matthew Christopher Myers – ProQuest LLC, 2024
This study uses an experimental comparative design to accomplish two primary goals related teachers' perceptions of automated writing evaluation (AWE) performance. First, it quantitatively and qualitatively examines teachers' perceptions of the accuracy and trustworthiness of differentially performing AWE models. Second, it synthesizes interview…
Descriptors: Language Arts, Teacher Attitudes, English Teachers, Automation
Steven R. Frechette – ProQuest LLC, 2024
This study investigates student perceptions of artificial intelligence (AI). The study analyzed four independent variables -- age, gender, school, and employment -- to predict students' level of readiness to adopt AI within an educational setting. Using an instrument with two constructs, data was collected from a diverse, multicultural group of…
Descriptors: Community College Students, Community Colleges, Student Attitudes, Artificial Intelligence
Graham B. Slater – Review of Education, Pedagogy & Cultural Studies, 2024
Accelerating digitization, algorithmic computation, artificial intelligence, and machine learning, along with the increasing automation of work, communication, and everyday life, are central to critical studies of technology and political economy, as well as to public discourse concerning technology's role in creating futures. Ongoing…
Descriptors: Algorithms, Anxiety, Artificial Intelligence, Man Machine Systems
Anuj Gupta; Yasser Atef; Anna Mills; Maha Bali – Open Praxis, 2024
This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT. Given the pressing need to teach "critical AI literacy", discussion of metaphor provides an opportunity for inquiry and dialogue with space for…
Descriptors: Artificial Intelligence, Figurative Language, Natural Language Processing, Multiple Literacies

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