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Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate

Mohammed Amin Almaiah, Raghad Alfaisal, Said A. Salloum, Fahima Hajjej, Rima Shishakly, Abdalwali Lutfi, Mahmaod Alrawad, Ahmed Al Mulhem, Tayseer Alkhdour, Rana Saeed Al-Maroof · 2022 · Electronics

Summary. This study examines how governmental institutions in the Gulf region adopt artificial intelligence applications in online learning environments. Using innovation diffusion theory, researchers found that adoption properties like trialability, observability, and compatibility positively influence ease of doing business and technology export. The findings suggest government authorities should prioritize implementation factors based on their significance to improve service delivery and user accessibility.

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Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Shishakly, R., Lutfi, A., Alrawad, M., Mulhem, A. A., Alkhdour, T., & Al-Maroof, R. S.. (2022). Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate. Electronics. https://doi.org/10.3390/electronics11203291

Details

DOI
10.3390/electronics11203291
Countries
Malaysia, United Kingdom
Regions
Asia, Europe
Categories
broadband-and-digital, innovation-theory, general-innovation
Added
2026-04-28