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Download full textJingyu Xiao; Goudarz Alibakhshi; Alireza Zamanpour; Mohammad Amin Zarei; Shapour Sherafat; Seyyed-Fouad Behzadpoor – International Review of Research in Open and Distributed Learning, 2024
Artificial intelligence (AI) has contributed to various facets of human lives for decades. Teachers and students must have competency in AI and AI-empowered applications, particularly when using online electronic platforms such as learning management systems (LMS). This study investigates the structural relationship between AI literacy, academic…
Descriptors: Artificial Intelligence, Technological Literacy, Educational Attainment, Electronic Learning
Innab, Adnan; Albloushi, Monirah; Alruwaili, Mohammed; Alqahtani, Naji; Alenazi, Latifah; Alkathiri, Alwah – International Review of Research in Open and Distributed Learning, 2022
The COVID-19 pandemic has caused a sudden shift to distance learning. For many nursing students, distance learning is a new experience and an essential requirement if they hope to complete their programs. Two challenges that nursing students could face during e-learning are the lack of social presence and low satisfaction. This study aimed to…
Descriptors: Nursing Students, Electronic Learning, Distance Education, Sense of Community
Datt, Gopal; Singh, Gagan – International Review of Research in Open and Distributed Learning, 2021
This paper explores learners' awareness of and satisfaction with the e-services that an open university provides its learners through its Website. The paper further highlights the influence of age, gender, and education levels on learners' awareness and satisfaction levels. A case-study approach was adopted and an online survey was used to collect…
Descriptors: Student Satisfaction, College Students, Open Universities, Distance Education
Li, Fengliang; Wang, Liang – International Review of Research in Open and Distributed Learning, 2021
Few empirical studies have analyzed the return to distance higher education in different academic disciplines. This study used quantitative methods, data from a nationwide survey, and Mincerian earnings function to analyze the return to distance higher education among different disciplines in China's labor market. Results were compared with the…
Descriptors: Foreign Countries, Distance Education, Intellectual Disciplines, Labor Market
