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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
Marta Modrego-Alarcón; Héctor Morillo; Daniel Campos; María Teresa Navarro-Gil; Jesús Montero-Marín; Alicia Monreal-Bartolomé; Javier García-Campayo; Yolanda López-Del-Hoyo – Journal of Computing in Higher Education, 2025
Mindfulness practices have proven to be effective for improving the mental health of many populations, including university students. However, these practices can be challenging for naive meditators. Virtual reality (VR) can create virtual scenarios that facilitate the practice of mindfulness. This study presents secondary data from a randomized…
Descriptors: Computer Simulation, Metacognition, Technology Uses in Education, Universities
Rachel Bancroft; Rachel Challen; Rosemary Pearce – Journal of Learning Development in Higher Education, 2024
Digital confidence has been increasingly cited as key for staff and student development in tertiary education, often alongside concepts of digital competence or digital capabilities. In the past three years it has formed part of the discussion in our sector (higher education) around adapting to this time of rapid change, especially during the…
Descriptors: Digital Literacy, Self Efficacy, College Faculty, College Students
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
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
Seo Yeon Cho; Tami Im – Education and Information Technologies, 2024
The purpose of this study is to identify the structural relationships among online class related factors, zoom fatigue, learning engagement, perceived achievement, and class satisfaction in a university distance learning context. The study analyzed 265 responses from K University in Korea. The key findings of the study are first, situational…
Descriptors: Foreign Countries, Electronic Learning, College Students, Distance Education
Sivo, Stephen Anthony; Ku, Cheng-Hsin; Acharya, Parul – Australasian Journal of Educational Technology, 2018
The purpose of this empirical research was to use the perceived resources and technology acceptance model (PRATAM; Ku, 2009) to observe and measure students' beliefs on using the WebCT online learning system (OLS) in two WebCT courses offered at a large university in the south-eastern United States. PRATAM was replicated from previous research to…
Descriptors: College Students, Student Attitudes, Electronic Learning, Online Courses
Zhang, Jie; Russo, Theresa J.; Fallon, Moira A. – International Journal of Technology in Teaching and Learning, 2015
As a part of a larger study, the purpose of this exploratory study was to assess college students' stress levels of using technology. Forty-four males (11.3%) and 345 females (88.5%) participated in the study by filling out an online survey voluntarily and anonymously. This was an exploratory survey of college students' feelings about technology,…
Descriptors: College Students, Stress Variables, Technology Uses in Education, Influence of Technology
Romero, Marc; Guitert, Montse; Sangra, Albert; Bullen, Mark – International Review of Research in Open and Distance Learning, 2013
Some authors have stated that university students born after 1982 have been profoundly influenced by digital technologies, showing different characteristics when compared to previous generations. However, it is worth asking if that is a current observable phenomenon. Are those students born after the 80s really more familiar with ICT tools than…
Descriptors: Generational Differences, Technology Uses in Education, Profiles, Computer Use
Cooper, Kenneth J. – Diverse: Issues in Higher Education, 2009
By the professor's rule, students in the English classes of Dr. Mark Bauerlein at Emory University must take notes by hand. Laptops must be turned off, he says, to ensure students focus on what's happening in the room, rather than on what's floating around cyberspace. In an age of instant communication via computers, cell phones and personal…
Descriptors: Information Technology, Technology Uses in Education, Higher Education, Influence of Technology
Emanuel, Richard; Adams, Jim; Baker, Kim; Daufin, E. K.; Ellington, Coke; Fitts, Elizabeth; Himsel, Jonathan; Holladay, Linda; Okeowo, David – International Journal of Listening, 2008
This study sought to assess how college students spend their time communicating and what impact, if any, communications devices may be having on how that time is spent. Undergraduates (N = 696) at four southeastern colleges were surveyed. Results revealed that listening comprises 55.4% of the total average communication day followed by reading…
Descriptors: College Students, Interpersonal Communication, Listening, Time

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