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Andrew Kemp; Edward Palmer; Peter Strelan; Helen Thompson – British Journal of Educational Technology, 2024
Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of…
Descriptors: College Students, Educational Technology, Models, Student Attitudes
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Chengliang Wang; Xiaojiao Chen; Zhebing Hu; Sheng Jin; Xiaoqing Gu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, as a cutting-edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Computer Uses in Education
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Weikang Lu; Chenghua Lin – Education and Information Technologies, 2025
Artificial intelligence is increasingly integrated into daily life, and modern educated individuals should have the ability to use AI tools correctly to improve work, study, and life efficiency. In this context, artificial intelligence literacy has been proposed. Due to the lack of consensus on the constructs of artificial intelligence literacy,…
Descriptors: Artificial Intelligence, Digital Literacy, Student Attitudes, College Students
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Manuela Farinosi; Claudio Melchior – European Journal of Education, 2025
Artificial intelligence (AI) tools have the potential to revolutionise educational practices, but their use raises ethical and organisational concerns for higher education institutions (HEIs). We investigated Italian students' perception and usage of AI tools at the University of Udine using questionnaires (N = 531) with fixed and open-ended items…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Attitudes, Computer Attitudes
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Yulu Cui; Hai Zhang – Education and Information Technologies, 2025
With the development of artificial intelligence technology, it has become increasingly difficult to distinguish between Artificial Intelligence Generated Content (AIGC) and non-AIGC. Inaccuracies in identifying AIGC in higher education may lead to academic misconduct and risks, and the credibility of AIGC is also subject to certain doubts. Users…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Identification
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Chun-Mei Chou; Tsu-Chuan Shen; Tsu-Chi Shen – Education and Information Technologies, 2025
AR-supported instruction has been verified to improve students' problem-solving skills. This study investigated 1041 university students and developed an empirical research model that combined technology acceptance, self-regulation, and AR-supported learning effectiveness with the structural equation model (SEM). At the same time, content analysis…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Adoption (Ideas)
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Matt Marino – Journal of Research Initiatives, 2024
This article explores the disconnect between student and educator perspectives regarding practical technology usage in higher education. As technology continues to play an increasingly prominent role in the educational landscape, understanding the differing viewpoints of students and educators is crucial for designing impactful technology…
Descriptors: College Students, College Faculty, Teacher Attitudes, Student Attitudes
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Kamil Çelik; Ahmet Ayaz – Educational Technology Research and Development, 2025
Technological advancements in recent years have accelerated the development of information and communication technologies, introducing numerous innovations. One prominent innovation is the concept of the metaverse, which has gained significant popularity and is increasingly influencing various sectors, including the economy, art, entertainment,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Computer Science Education
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Izida I. Ishmuradova; Alexey A. Chistyakov; Tatyana A. Brodskaya; Nikolay N. Kosarenko; Natalia V. Savchenko; Natalya N. Shindryaeva – Contemporary Educational Technology, 2025
This investigation aimed to ascertain latent profiles of university students predicated on fundamental factors influencing their intentions to acquire knowledge in artificial intelligence (AI). The study scrutinized four dimensions: supportive social norms, facilitating conditions, selfefficacy in AI learning, and perceived utility of AI. Through…
Descriptors: Artificial Intelligence, Technology Uses in Education, College Students, Electronic Learning
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Michelle Xin Yi Tan; Yao Qu; Jue Wang – Higher Education Quarterly, 2025
The rapid adoption of generative artificial intelligence (GenAI) in higher education has raised questions about student use, academic integrity, and institutional regulation. This study examines students' perceptions of and compliance with GenAI regulations in higher education, using a Singaporean university as a case study. Adopting a…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Computer Uses in Education
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Clara Rispler; Michal Mashiach Eizenberg; Gila Yakov – Journal of Teaching and Learning for Graduate Employability, 2025
As artificial intelligence (AI) transforms workplaces, understanding how future graduates engage with AI technologies is crucial for enhancing employability. This study investigates higher education students' familiarity with and perceptions of generative artificial intelligence (GenAI) in their learning. Using the Technology Acceptance Model…
Descriptors: Foreign Countries, College Students, Student Surveys, Online Surveys
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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
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Perez, Melissa; Garcia, Patricia – ACM Transactions on Computing Education, 2023
Norms and values in computing education are constantly changing as dominant narratives about the role of computing in society evolve over time. Within the current evolving landscape of computing education, researchers and practitioners have advocated for ensuring people from all backgrounds, and particularly women, non-binary, and Black,…
Descriptors: Females, Computer Science Education, Student Experience, Attitudes
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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
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Meral Yavuz Kartal; Dinçay Koksal – Novitas-ROYAL (Research on Youth and Language), 2025
Using technology in foreign language learning can provide a variety of possibilities, significant opportunities, and significant benefits. Considering that Generation Z is a generation born into technology and grew up with it, it is critical to understand the intentions of Generation Z students to use technology in learning English and to find out…
Descriptors: English (Second Language), Second Language Learning, Technology Uses in Education, Student Attitudes
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