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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
Suzhen Duan; Marisa Exter; Qing Li – TechTrends: Linking Research and Practice to Improve Learning, 2024
Preservice teachers' beliefs regarding technology integration significantly influence their future teaching practices. This qualitative study examines the beliefs and intentions of 51 preservice teachers within the context of technology integration in their envisioned teaching scenarios. Thematic analysis identified three primary themes. Firstly,…
Descriptors: Preservice Teachers, Student Attitudes, Beliefs, Technology Integration
Laurie O. Campbell; Caitlin Frawley – Educational Technology Research and Development, 2024
Higher education faculty members incorporate technologies into their teaching and learning practices in higher education for the benefit of their learners. Hence, general technologies, such as presentation software, online classrooms, and learning management systems are ubiquitous in higher education teaching practices. However, emerging…
Descriptors: College Faculty, Intention, Technology Integration, Educational Technology
Mengrong Han; Hasri Mustafa; Saira Kharuddin – Journal of Pedagogical Research, 2025
This study investigates the adoption and usage of artificial intelligence (AI) technologies among Chinese undergraduate accounting students, focusing on the roles of Social Influence (SI), Behavioral Intention (BI), and Actual Usage (AU), while examining the mediating effect of BI and the moderating effect of Voluntariness of Use (VOU). By…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Accounting
Jiaming Cheng; Jacob A. Hall; Qiu Wang; Jing Lei – Education and Information Technologies, 2024
Using pre-service teachers' (PSTs) technological, pedagogical, content knowledge (TPACK) survey responses, this study's cluster analysis identified five distinct learning profiles: Pedagogical Content Knowledge Specialists, Technological Forerunners, Pedagogically Minded, Balanced Integrators, and TPACK Lingerers. Instead of using a single…
Descriptors: Preservice Teachers, Teacher Education, Technology Uses in Education, Educational Technology
Mussa Saidi Abubakari; Gamal Abdul Nasir Zakaria; Juraidah Musa – Cogent Education, 2024
Various factors, including technical, organisational, cultural, and individual, can influence how people adopt digital technologies (DT). However, different contexts have produced similar yet distinct results when researchers integrated these various factors into the technology acceptance model (TAM). Two critical factors in the Islamic…
Descriptors: Foreign Countries, Higher Education, Islam, Religious Education
Kaspul Anwar; Juraidah Musa; Sallimah M. Salleh – Education and Information Technologies, 2025
This study examines the factors influencing preservice teachers' (PSTs) technology integration during teaching practice in teacher preparation programs. Utilizing a multidimensional framework, the study integrates models such as TPACK, UTAUT, and the Triple-E evaluation rubric, among others. The research involved a Qualtrics survey of 1,217 PSTs…
Descriptors: Preservice Teachers, Technology Uses in Education, Technology Integration, Preservice Teacher Education
Tony Robinson – Journal of Educational Technology, 2025
Generative artificial intelligence (AI) is increasingly transforming higher education by enhancing teaching methodologies, automating administrative tasks, and supporting research initiatives. Faculty adoption of generative AI is crucial for maximizing its potential benefits; however, its acceptance remains inconsistent due to factors such as…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Technology Integration
Fairuz Anjum Binte Habib – Education and Information Technologies, 2025
The incorporation of artificial intelligence (AI) into education is becoming more important over time, although faculty viewpoints on this integration are not well recognized. To analyze educators' attitudes towards AI tools in Bangladesh, this research built a modified model that included components from the technology acceptance model (TAM),…
Descriptors: Teacher Attitudes, Intention, Artificial Intelligence, Technology Uses in Education
Linlin Hu; Hao Wang; Yunfei Xin – Education and Information Technologies, 2025
Although Generative Artificial Intelligence (GAI) has demonstrated significant potential in education, there is a lack of research on pre-service teachers' behavioral intentions toward GAI. This study is based on the UTAUT2 model and, for the first time, introduces perceived risk as a key variable to systematically investigate the factors…
Descriptors: Foreign Countries, Preservice Teachers, Computer Attitudes, Technology Integration
Lisana, Lisana – Education and Information Technologies, 2023
Adopting technology by its intended users is one of the most important contributors to that technology's success. Therefore, the success of mobile learning (ML) depends on the students' acceptance of the method. Regarding this point, this quantitative research aims to identify factors that affect switching intention to adopt ML among university…
Descriptors: Handheld Devices, Telecommunications, Technology Integration, Intention
Guillén-Gámez, Francisco D.; Ruiz-Palmero, Julio; García, Melchor Gómez – Education and Information Technologies, 2023
All spheres of our life are being affected using technology, particularly its integration in the research processes carried out by teachers. The success of the integration of specific digital resources in research work can be affected by several factors, such as: digital skills for finding information, managing it, analyzing it, and communicating…
Descriptors: Technological Literacy, Teacher Competencies, Teacher Researchers, Educational Technology
Sasha Nikolic; Isabelle Wentworth; Lynn Sheridan; Simon Moss; Elisabeth Duursma; Rachel A. Jones; Montserrat Ros; Rebekkah Middleton – Australasian Journal of Educational Technology, 2024
The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching…
Descriptors: College Faculty, Teacher Attitudes, Intention, Teacher Behavior
Yuan-Hsuan Lee; Huang-Yao Hong – Interactive Learning Environments, 2024
Integrating Information and Communication Technologies (ICT) for meaningful constructivist instruction has become essential in teacher education. This study investigated preservice teachers' intention to integrate ICT for constructivist learning from the perspectives of their Internet epistemic beliefs (IEB) and Internet-based learning…
Descriptors: Preservice Teachers, Information Technology, Technology Integration, Constructivism (Learning)
Max C. Anderson; Cindy S. York; Angie Hodge-Zickerman; Yoon Soo Park; Jason Rhode – Technology, Knowledge and Learning, 2024
This non-experimental quantitative study investigated medical school faculty members' behavioral intention to use and actual usage behavior of technology in inquiry-based learning activities in medical schools in the United States by applying the unified theory of acceptance and use of technology (UTAUT). In medical education, situational problems…
Descriptors: Medical Education, Medical School Faculty, Intention, Teacher Behavior