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Direct linkRasha Noureddine; David Boote; Laurie O. Campbell – Education and Information Technologies, 2025
A meta-analytic study was conducted of the "Unified Theory of Acceptance and Use of Technology" to understand higher education instructors use of technology in teaching and learning. Through broad searches of the years 2003-2023, 117 records were identified for initial review. After reviewing the studies and removing those studies that…
Descriptors: College Faculty, Teacher Attitudes, Technological Literacy, Computer Literacy
Iddrisu Salifu; Francis Arthur; Bernard Yaw Sekyi Acquah; Ernest Opoku; Sharon Abam Nortey; Eric Boateng – Discover Education, 2025
This study based on an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, examines factors influencing graduate students' behavioural intention towards adoption and actual use of generative artificial intelligence (GenAI). Using a cross-sectional data from 415 graduate students in Ghana, this study employed the partial…
Descriptors: Graduate Students, Technology Uses in Education, Artificial Intelligence, Foreign Countries
Madina Bekturova; Saule Tulepova; Altnay Zhaitapova – Education and Information Technologies, 2025
The advancement of technologies has resulted in the boost of a popular chatbot software -- ChatGPT. It is ripe with potential, yet has introduced various challenges, especially in the world of education. This paper aims to explore how TEFL (Teaching English as a foreign language) students perceive the usefulness and ease of using ChatGPT in regard…
Descriptors: Foreign Countries, Predictor Variables, Second Language Learning, English (Second Language)
Mohan Yang; Shiyan Jiang; Belle Li; Kristin Herman; Tian Luo; Shanan Chappell Moots; Nolan Lovett – British Journal of Educational Technology, 2025
Generative artificial intelligence brings opportunities and unique challenges to nontraditional higher education students, stemming, in part, from the experience of the digital divide. Providing access and practice is critical to bridge this divide and equip students with needed digital competencies. This mixed-methods study investigated how…
Descriptors: Nontraditional Students, Artificial Intelligence, Technology Uses in Education, Man Machine Systems
Linda J. Sax; Kaitlyn N. Stormes; Maxx F. Pereyra – ACM Transactions on Computing Education, 2025
To cultivate more computing talent (including more diverse talent), it is important to understand how college students experience their computing courses and if such experiences vary based on students' gender and racial/ethnic identities. In this paper, we focus on course modality to understand whether taking courses in-person, online, or a hybrid…
Descriptors: Computer Science Education, Electronic Learning, Online Courses, Delivery Systems
