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Showing 1 to 15 of 72 results Save | Export
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Yu-xi Wang; Li-ping Chen; Jia-yin Han – Education and Information Technologies, 2024
The study of students' willingness to use translation technology can motivate students to use the translation technology and improve their translation efficiency. This paper reports on a survey which collected 716 valid questionnaires from students in the Master-level Program in Translation and Interpreting. Structural equation modeling (SEM) was…
Descriptors: Student Attitudes, Graduate Students, Translation, Information Technology
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Pengfei Yang; Shaowen Qian – SAGE Open, 2025
E-learning has revolutionized the educational landscape, changing how knowledge is imparted to students and enhancing the learning process. Despite the growing popularity of e-learning worldwide, a lingering question remains regarding the behavioral intentions of Physical Education students toward its use. This study endeavors to address this…
Descriptors: Foreign Countries, Physical Education, Intention, Electronic Learning
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Teng Ma; Ahmad Samed Al-Adwan; Na Li; Erick Purwanto; Wan Meng; Hai-Ning Liang – IEEE Transactions on Education, 2025
Contribution: This study has proposed a hybrid framework of acceptance and self-determination for the use of digital textbooks in higher education programming courses. The intertwined relationships between acceptance and self-determination factors, and their joint effects on student's engagement and learning performance are all examined.…
Descriptors: Textbooks, Electronic Publishing, College Students, Programming
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Md.Abu Issa Gazi; Muhammad Khalilur Rahman; Mohammad Bin Amin; Md Arafat Hossain; Moniya Sultana; Abdul Rahman bin S Senathirajah; Veronika Fenyves – Educational Process: International Journal, 2025
Background/purpose: The crisis caused by the COVID-19 pandemic has altered the direction of education worldwide, emphasizing the prospects and problems of using online learning platforms. This study aims to investigate the dual aspects of COVID-19 (positive and negative) on facilitating conditions for learning quality that affect students'…
Descriptors: COVID-19, Pandemics, Student Attitudes, Online Courses
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Shuaiyao Ma; Lei Lei – Asia Pacific Journal of Education, 2024
This study, rooted in the Technology Acceptance Model (TAM), investigates the multifaceted factors that influence teacher education students in Information-Based Teaching to embrace artificial intelligence technologies. To enrich the TAM framework, we have incorporated elements such as Artificial Intelligence Literacy (AIL), Subjective Norms (SN),…
Descriptors: Preservice Teachers, Artificial Intelligence, Technology Uses in Education, Educational Technology
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Fengyao Sun; Peiyao Tian; Daner Sun; Yanhua Fan; Yuqin Yang – British Journal of Educational Technology, 2024
In the ever-evolving AI-driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre-service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers'…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Preservice Teachers
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Feng Zhang; Gege Li; Heng Luo – Educational Technology & Society, 2025
With the development of virtual reality technology, 3D multi-user virtual environments (MUVEs) have attracted increasing research attention and are thought to bring many learning benefits in higher education. However, the widespread and sustained application of MUVEs in higher education lies in learners' intention to use them, but the mechanism…
Descriptors: Student Attitudes, Intention, College Students, Educational Technology
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Mohammed A. E. Suliman; Wenlan Zhang; Kamal Abubker Abrahim Sleiman – Innovations in Education and Teaching International, 2024
This study set out to determine what variables led students to choose mobile learning during COVID-19 and to study the direct impact of the perceived fear of COVID-19 (PCF) on undergraduate learners' intentions to adopt m-learning in developing countries such as Sudan. It utilizes the Technology Acceptance Model (TAM) as a foundation and uses PCF…
Descriptors: Educational Technology, Technology Uses in Education, Telecommunications, Handheld Devices
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Sajuddin Saifi; Shaista Tanveer; Mohd Arwab; Dori Lal; Nabila Mirza – Education and Information Technologies, 2025
The current study is an attempt to bring to light the influence of Open AI adoption among users regarding the Indian Higher Education system by incorporating the TCT and TTF models. A questionnaire was designed to collect the data from 571 participants associated with higher education in India. The developed model with Perceived usefulness,…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Higher Education
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Baji, Fatima; Azadeh, Fereydoun; Sabaghinejad, Zivar; Zalpour, Amir – Journal of Global Education and Research, 2022
E-learning can address some of the unmet needs of learners and educational communities; however, not all learners and educators accept e-learning as a delivery modality. This research endeavored to study the factors which affect e-learning acceptance among Iranian post-graduate students using the Davis Technology Acceptance Model (TAM) and to…
Descriptors: Foreign Countries, Electronic Learning, Educational Technology, Graduate Students
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Salimon, Maruf Gbadebo; Mokhtar, Sany Sanuri Mohd; Aliyu, Olayemi Abdullateef; Yusr, Maha Mohammed; Perumal, Selvan – Journal of Applied Research in Higher Education, 2023
Purpose: E-learning system has been widely acknowledged to have positive impacts on the learning process. Nevertheless, the intention to use it is globally low, thereby constituting puzzles to be solved. This study aims to proffer some insights to solve the puzzles. Design/methodology/approach: The data of the study were collected through an…
Descriptors: Foreign Countries, Electronic Learning, Educational Technology, Intention
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Alam, Syed Shah; Masukujjaman, Mohammad; Ahmad, Maisarah; Jaffor, Romlah – Education and Information Technologies, 2023
Nowadays, the teaching methods are changed from offline to online primarily for the advent of the internet facility. The Industrial Revolution 4.0 ("Education 4.0") stresses offering online courses at the university level. The study aims to find out the factors influencing students' intentions to admit to online distance learning…
Descriptors: Online Courses, Student Attitudes, Intention, Distance Education
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Joseph Lobo; Francisco Gabriel Prevandos; Jem Cloyd Tanucan; Edi Setiawan – Journal of Learning for Development, 2024
Research shows that videoconferencing tools can be used for delivering high-quality instruction in real-time to a large number of students simultaneously during and even in the aftermath of the pandemic. However, there is a lack of data on how favourable it is among students, particularly in the Philippine setting, in the field of Physical…
Descriptors: Videoconferencing, Educational Technology, Physical Education, Student Attitudes
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Muhammad Ittefaq; Ali Zain; Rauf Arif; Taufiq Ahmad; Laeeq Khan; Hyunjin Seo – Journal of International Students, 2025
GenAI has revolutionized higher education across the globe. One group that is particularly impacted is international students. We examined the factors influencing international students' intentions to use GenAI. We recruited participants studying in the U.S. through an online survey. Our results suggest that attitudes toward GenAI use, PEU, PU,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Foreign Students, Student Attitudes
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Ifenthaler, Dirk; Sahin, Muhittin – Interactive Technology and Smart Education, 2023
Purpose: This study aims to focus on providing a computerized classification testing (CCT) system that can easily be embedded as a self-assessment feature into the existing legacy environment of a higher education institution, empowering students with self-assessments to monitor their learning progress and following strict data protection…
Descriptors: College Students, Classification, Self Evaluation (Individuals), Progress Monitoring
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